CyberFlow [Probabilities] | FractalystWhat's the indicator's purpose and functionality?
CyberFlow quantifies, per chosen higher-timeframe “Period 1/2/3”, what happens after price first taps the midpoint (Mid) of the previous period’s range. Specifically, it estimates P(High first | Mid tap) versus P(Low first | Mid tap): which side (previous High “PH” or previous Low “PL”) is typically reached first after that mid activation.
It extends a previously shared OrderFlow concept that used market structure; here it conditions on higher‑timeframe previous‑period PH/PL with the Mid as the explicit trigger.
Note: It's specifically designed to exports raw probabilistic series for algorithmic/system developers to integrate a probabilistic layer into strategies and to build/backtest ideas directly from those series.
What is “Mid activation”?
The Mid is the average of the previous period’s PH and PL. Activation occurs on the first bar in the current period whose high–low range includes the Mid. The first bar of a new period cannot activate Mid; activation can only start from the second bar of the period onward.
What counts as “first hit” after activation?
After a Mid activation, the script waits for a subsequent bar that touches either the previous High (PH) or previous Low (PL). The first side touched after the activation bar is recorded as that period’s first hit. Once decided, the other side is ignored for first‑hit statistics.
Which periods does it use?
You can select three custom reference timeframes (Period 1/2/3) in the UI (defaults: D/W/M). All logic—PH/PL/Mid, activation, first‑hit stats—runs independently per selected period.
Do the display controls change the calculation?
No. The “Show” selector only controls visuals:
Period 1/2/3: show only that period’s plots/barcolors.
OFF: shows all periods. Statistics and exported series are unaffected by this selector.
What do the bar/line colors mean?
Activation (first Mid tap): yellow bar.
Delivered to previous High after activation: blue
Delivered to previous Low after activation: red
Plots stop showing PH/PL once delivery happens (for that side) within the period.
What do the status symbols in the table mean?
■ Inactive — Mid not tapped this period.
▶ Activated — Mid tapped; awaiting delivery to PH or PL.
● Delivered — PH or PL was hit first after the Mid tap.
How are probabilities computed?
For each period, the script counts samples where the Mid was tapped and one side was hit first. It reports:
P(High first | Mid tap) and P(Low first | Mid tap).
Two‑sided p‑value vs 50% (H0: p = 0.5). These appear in the stats table with detailed tooltips.
What is “Bias” in exports?
Bias is a ternary signal derived from P(High first | Mid tap):
Bias = 1 if > 0.5
Bias = -1 if < 0.5
Bias = 0 if exactly 0.5 or no sample Source can be per period or “Merged” (simple average of available period probabilities).
Note: the UI uses a simple average; no weighted option is exposed.
What is “Entry” in exports?
Entry = 1 on bars where the selected period’s Mid activates (first tap), else 0. “Merged” emits 1 if any of the three periods activates on the bar.
What is “Exit” in exports?
Exit is the previous period’s Mid price (PH/PL average) for the selected period. “Merged” is the average of the three previous‑period Mid prices.
How do I integrate this into strategies? How to use the indicator?
CyberFlow is designed for algorithmic/system developers to add a probabilistic layer for entries and market‑regime detection.
What CyberFlow exports
- Bias (−1, 0, 1): from P(High first | Mid tap) vs 50% per your chosen source (Period 1/2/3 or Merged simple average).
- Entry (0/1): 1 only on the bar where the selected period’s Mid first activates (the “mid tap” bar).
- Exit (price): the previous period’s Mid price (average of previous High/Low) for the selected source.
- These appear in the Data Window as series named Bias, Entry, and Exit.
Connecting from your strategy (input.source)
- Add inputs in your strategy so users can select CyberFlow’s outputs:
- Bias source input: pick the indicator’s Bias.
- Entry source input: pick the indicator’s Entry.
- Exit source input: pick the indicator’s Exit.
In TradingView’s UI, users link these inputs to CyberFlow’s plots via the source picker.
Does this use request.security?
No. CyberFlow reconstructs your selected higher timeframes (Period 1/2/3) directly on the chart without request.security().
It detects new period boundaries via timeframe.change(tf), rolls the last period’s extremes into Previous High/Low (PH/PL), computes their Mid, then waits for a “Mid activation” (a bar after the first bar of the period whose range crosses the Mid).
From activation onward, it records which side (PH or PL) is reached first to build conditional probabilities per period.
Because levels and events are derived locally from the live bar stream, there are no cross-timeframe fetch artifacts or repaint nuances from request.security().
The exported series (Bias −1/0/1, Entry 0/1, Exit price) are produced natively and can be wired into strategies via TradingView’s input.source() for robust, low-latency integration.
What markets and assets does the indicator Extension work best on?
CyberFlow is market- and timeframe‑agnostic: it computes conditional probabilities (which side of the prior range is reached first after a mid tap) directly from price, so it can be applied to crypto, FX, indices, equities, futures, and commodities across intraday to higher timeframes. In practice, robustness depends on liquidity and sample size: higher timeframes usually yield more stable estimates (fewer activations, lower noise), while lower timeframes give more activations but can be noisier (spreads/fees matter more).
Because the study itself provides probabilities—not PnL—assess profitability in your context by integrating the exported series (Bias −1/0/1, Entry 0/1, Exit price) into your strategy via TradingView’s input.source(), then backtest with your fills, costs, and risk model to measure performance efficiency on your specific markets and settings.
What makes this script unique?
Custom higher-timeframes (beyond D/W/M)
You can pick any three reference periods (Period 1/2/3), not just Daily/Weekly/Monthly. The script rebuilds these periods directly on the chart and analyzes each independently.
True conditional probability (why it matters)
It measures P(High first | Mid tap) vs P(Low first | Mid tap) — i.e., “after the previous period’s midpoint is first tapped, which side is typically reached first?”
Conditioning on the mid‑tap event isolates the path that follows a specific trigger. Unconditioned counts (e.g., “how often PH/PL is hit”) mix pre‑ and post‑activation behavior and can be misleading. This conditional framing turns vague hit‑rates into decision‑grade odds tied to a clear setup.
Statistical confidence in‑context (p‑value in tooltips)
Tooltips show a Wilson 95% confidence interval and a two‑sided p‑value versus 50/50. This helps you judge whether an observed edge is likely signal or noise at your chosen periods.
Exports built for algorithmic integration
Three clean outputs in the Data Window for strategies:
Bias (−1/0/1) from the conditional probability versus 50%.
Entry (0/1) on the activation bar (first mid tap).
Exit (price) as the previous period’s Mid.
Hook these into your backtests via TradingView’s input.source(), then evaluate profitability with your own fills, costs, and risk model. This turns the probabilities into measurable performance you can optimize.
Disclaimer
This tool provides statistical estimates only and is not financial advice. Historical probabilities are not guarantees of future results. Always backtest with your own costs, fills, and risk model before using in live trading.
Quanttrading
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
BeeQuant - Hive Bars🔶 OVERVIEW
The "Hive Bars" indicator is a truly revolutionary analytical instrument, meticulously engineered to transcend the limitations of conventional price charting and unveil the profound, underlying essence of market dynamics. Imagine possessing a sophisticated visual engine that intelligently reconstructs raw price data into unique, dynamically consolidated "Hive Bars." These specialized constructs intuitively reveal the dominant market momentum and highlight high-conviction signals often obscured by the ubiquitous noise of traditional candlesticks. This indicator acts as a precision filter, illuminating exactly when pivotal shifts are occurring by coloring these reconstructed units with an adaptive, unparalleled accuracy. It is expertly crafted for the discerning trader seeking an undeniable analytical advantage, offering a fresh, meticulously refined perspective that enables the discernment of concealed patterns, fostering more decisive and confident trading actions. Crucially, "Hive Bars" now feature proactive, real-time alert capabilities, ensuring no critical market inflection point ever goes unnoticed.
__________________________________________________________________________
🧠 CONCEPTS
At its intellectual core, the "Hive Bars" indicator operates upon an advanced, proprietary framework that fundamentally reinterprets market data. It presents this refined information through its unique "Hive Bars"—specialized visual constructs that dynamically encapsulate the consolidated spirit and true directional bias of price action, delivering unparalleled clarity.
⬜ Smart Bar Reconstruction: Hive Bars don’t follow time, they follow the market. They are derived through a sophisticated, multi-faceted internal process that precisely captures the dominant price influence and momentum over variable periods. This structure adapts dynamically to changing conditions, letting you see the real pressure behind price moves with consistency that time-based candles can’t match. This proprietary reconstruction creates a new, inherently consistent, and highly focused visual narrative of underlying market flow, effectively stripping away extraneous "noise" and revealing the market's authentic directional intent.
⬜ Multi-Layered Internal Analysis: A dynamic and live, adaptive line powers the core of Hive Bars. It recalibrates constantly, tracking market structure in real time. Every bar is formed in relation to this internal baseline, giving immediate context to price behavior. You choose the data that drives this line—open, close, high, low, or custom blends—to match your style.
⬜ Intelligent Bar Formation Sequences: Bars are created when the market speaks, not when the clock ticks. A built-in pattern engine reads the flow and waits for real structure to form. This allows the indicator to autonomously consolidate price action, presenting a cleaner, more coherent visualization of trend development as it truly unfolds, rather than fragmented snapshots based on time.
⬜ Visual Signal Precision: "Hive Bars" spring to life with an intuitively powerful coloring system. While primary colors (Green for upward bias, Red for downward bias) denote the prevailing market direction, the "Hive Bars" indicator introduces distinctively colored "Signal Hive Bars". These specialized bars emerge when the market price exhibits a particularly robust, high-conviction interaction with the adaptive internal baseline, standing out instantly and often mark key turning points or breakouts you want to act on.
⬜ Daily Reset Option: For intraday traders, there’s a reset feature that clears the internal build-up at the start of each new trading day. This ensures fresh, unbiased perspectives that are meticulously tailored to the distinct market dynamics and cyclic rhythms of the current trading day.
⬜ Adjustable Sensitivity: With Hive Smoothing, you’re in full control. This setting lets you fine-tune how sensitive the bars are to price movement. Want tighter, faster signals? Dial it down. Prefer broader, more filtered setups? Turn it up. You decide when a new Hive Bar forms—and when a Signal Bar confirms. It’s all based on how you trade and how your asset moves. No guesswork, no one-size-fits-all defaults. Hive Bars adapts to your strategy and trading style, not the other way around.
__________________________________________________________________________
✨ FEATURES
The "Hive Bars" indicator is equipped with a comprehensive suite of cutting-edge features, designed for unparalleled clarity, adaptive responsiveness, augmented analytical depth, seamless interoperability with your broader analytical toolkit, and proactive real-time notifications:
🔹Proprietary Hive Bar Reconstruction
Experience a uniquely advanced visual representation of price action that dynamically consolidates market data, leading to enhanced trend and momentum clarity that goes beyond standard charting and candlestick data.
🔹Customizable Internal Analysis Line
Gain precise control over the underlying adaptive baseline's calculation by selecting various internal price source options, ensuring its alignment with your specific analytical focus.
🔹 Smart Alerts for Key Events 🔔
Get notified in real time when:
◦ A new Hive Bar completes – signaling a fresh structural range reset
◦ A new Signal Hive Bar closes – identifying a potential overbought or oversold condition
Built-in alert conditions make it easy to stay ahead of shifts without watching every candle manually.
🔹Intelligent Bar Formation Sequencing
Diamond-shaped markers clearly indicate the start of the indicator's internal combination logic for enhanced visual understanding.
🔹High-Conviction "Signal Hive Bars" (Distinct Colors)
Receive specialized, uniquely colored visual alerts when Hive Bars exhibit strong, decisive movements relative to the adaptive baseline, indicating moments of heightened market conviction and potential opportunity.
🔹Session-Based Reconstruction
Opt for the "Daily New Start" to intelligently reset the indicator's perspective with each new trading day, providing fresh, session-aligned insights tailored for intraday precision.
🔹Unrivaled External Indicator Collaboration
A truly unique and powerful advantage of "Hive Bars" is its capability to seamlessly integrate and profoundly enhance the performance of other external indicators. By outputting clean, smoothed price data, it lets you feed a higher-quality source into tools like RSI, MACD, moving averages etc. Use close for indicators like RSI, and close for moving averages. The result is better clarity, fewer false signals, and a stronger edge across your setup. Hive Bars isn’t just an indicator, it’s an upgrade for everything you use.
🔹Non-Repainting Historical Integrity
Hive Bars never repaints. Each bar is locked in only after all internal conditions are fully met. This means you can trust every historical signal—it won’t shift or vanish after the fact. What you see in hindsight is exactly what was shown in real time.
🔹Universal Timeframe Compatibility
Whether you're scalping on the 1-minute chart or analyzing multi-month trends, Hive Bars delivers consistent, clean insights. Its architecture adapts to any timeframe without losing fidelity, making it a reliable tool for any strategy or style.
🔹Cross-Market Versatility
Hive Bars is engineered to perform with precision across all major markets—whether you're trading forex, commodities, stocks, or indices. Its adaptive logic automatically aligns with the unique volatility and structure of each asset class, delivering consistently reliable insights no matter where you trade.
__________________________________________________________________________
⚙️ USAGE
Integrating the "Hive Bars" indicator into your daily analytical regimen is an intuitive process that will profoundly enhance your ability to discern crucial market dynamics and spot high-conviction opportunities with unprecedented clarity:
💁 Effortless Application
Simply add the "Hive Bars" indicator to any chart within your TradingView platform. Note that it plots on a separate panel below your main price chart to provide its unique visual output without obscuring the primary price action.
📊 Strategic Calibration
Access the indicator's comprehensive settings panel to meticulously calibrate its powerful engines and unlock its full potential:
⚙ "Internal EMA Config"
Configure the internal adaptive baseline by choosing its source (e.g., CLOSE, HL/2) and its specific EMA length. This shapes the core reference point for the dynamic formation of the "Hive Bars."
🤖 "CONFIG Group"
Here, you decide if you want "Daily New Start" for session-based analytical resets (particularly beneficial for intraday strategies). The "Hive Smoothing" input allows you to control a further layer of consolidation for the "Hive Bars."
🟩🟥 "Color": Customize the appearance of both standard "Hive Bars" and "Signal Hive Bars" to suit your visual preferences, enhancing their immediate interpretability.
🧭 Empirical Exploration
Experimentation with these parameters is paramount. Dedicate time to exploring different combinations across various assets and timeframes to discover the optimal configuration that resonates with your unique trading methodology and the inherent volatility of the market being analyzed.
👀 Interpreting the Unveiled Market Reality: Once calibrated, the "Hive Bars" will present a strikingly clear and actionable picture of market dynamics:
+ Green/Red Hive Bars: These visually denote the consolidated directional bias of the market over the reconstructed period. A sustained sequence of Green "Hive Bars" suggests pervasive bullish pressure and an upward path of least resistance, while a series of Red "Hive Bars" indicates dominant bearish control and a clear downward momentum.
+ "Signal Hive Bars" (Distinct Colors): Pay close attention to these specially colored "Hive Bars." They signify critical moments where the reconstructed price action exhibits a particularly strong, high-conviction interaction with its adaptive internal baseline. These often precede or confirm significant market movements and serve as your clearest, most reliable visual triggers for potential shifts in market control.
⛓️ Intermittent Appearance: Observe that "Hive Bars" do not necessarily appear for every single native time unit of your chart. They are intelligently reconstructed and consolidated representations of price action, appearing only when specific internal conditions are met to present a coherent, high-impact view of distinct market phases.
🔗 Harnessing Advanced External Synergy: To unlock a new dimension of analytical power, profoundly enhance your existing indicator suite by integrating the output of "Hive Bars" as the data source for other external indicators. When adding or configuring indicators such as RSI, Stochastic Oscillators, various Moving Averages (EMA, SMA), or any other indicator that prompts for a 'source' input, you can now select the purified output of the "Hive Bars" as your desired data stream.
For oscillators (e.g., RSI, MACD), select the close or a similar relevant output from "Hive Bars" as your source. This allows the oscillator to react to the purified, consolidated momentum of the "Hive Bars" rather than the potentially noisy raw price data, leading to smoother and more meaningful oscillator signals.
For moving averages (e.g., EMA, SMA), utilize the close or other pertinent "Hive Bar" output as your source. This provides an exceptionally smooth, highly responsive, and less choppy average that precisely tracks the true underlying trend as identified by "Hive Bars." This unique capability allows for the construction of powerfully layered and synergistic trading strategies.
📢 Setting Up Proactive Alerts for Critical Events: Leverage the newly incorporated alert capabilities to maintain real-time awareness of pivotal market developments, even when not actively monitoring your charts.
You can now choose to be alerted specifically when a "New Hive Bar Closed" (signifying the definitive completion of a major market phase as identified by the indicator) or when a "New Signal Hive Bar Closed" (highlighting a high-conviction market event that warrants immediate attention due to its pronounced significance).
__________________________________________________________________________
⚠️ LIMITATIONS
While the "Hive Bars" indicator is an incredibly powerful and advanced tool for dissecting market dynamics, it is vital to understand its inherent design parameters and the prevailing platform-specific constraints for optimal and informed utilization:
👉 Visual Gaps in Plotting: Due to current platform limitations pertaining to custom candle plotting functionality, you may occasionally observe visual gaps or intermittent non-contiguous plotting between "Hive Bars" on the chart. They’re not missing data, but a result of strict plotting rules. A bar is only drawn when all internal conditions are met. This ensures accuracy, even if the chart shows some spacing.
👉 Complementary Tool: This indicator excels at providing high-conviction directional insights and identifying significant market phases. However, it is fundamentally designed as a sophisticated complementary tool to a broader trading strategy, not as a standalone, all-encompassing system. Its true power is unlocked when integrated with other analytical methods.
👉 Input Calibration Essential: The efficacy and depth of insights derived from the "Hive Bars" are highly dependent on the careful and thoughtful calibration of its input parameters, including the "Internal EMA Config," "Hive Smoothing" setting. Optimal results necessitate empirical user experimentation and fine-tuning to discover the configurations best suited for specific assets, analytical objectives, and market conditions.
👉 Exclusion of Auxiliary Data: The "Hive Bars" indicator's primary focus is exclusively on transforming and presenting price data. It does not natively incorporate other vital market information such as fundamental economic data, or news events. Integrating these additional analytical layers remains an essential aspect of constructing a truly comprehensive and robust trading strategy.
█ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 『•••• ✎ ••••』 ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ █
🎯 CONCLUSION
The "Hive Bars" indicator offers an unparalleled, intuitively accessible, and highly adaptable framework for instantly grasping true price momentum and direction through its intelligent, non-repainting reconstruction of market data. By transforming chaotic raw data into strikingly clear, high-conviction "Hive Bars" and dynamic signals, and now with proactive alerts to highlight critical moments, it empowers you to cut through distractions and identify market currents with unprecedented ease. Think of it as a custom lens for the market. It filters out the clutter and shows you the real structure—bars formed not by time, but by intent. It's about seeing the unseen, with enhanced clarity and a deeper understanding of market forces, now with the power to supercharge all your other tools and keep you informed. No fluff. No hype. Just an edge you can actually see—and use.
▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣
🚨 RISK DISCLAIMER
Engagement in financial market speculation inherently carries a substantial degree of inherent risk, and the potential for capital diminution, potentially exceeding initial deposits, is a pervasive and non-trivial consideration. All content, algorithmic tools, scripts, articles, and educational materials disseminated by "Hive Bars" are exclusively purposed for informational and pedagogical objectives, strictly for reference. Historical performance data, whether explicitly demonstrated or implicitly suggested, offers no infallible assurance or guarantee of future outcomes. Users bear sole and ultimate accountability for their individual trading decisions and are emphatically urged to meticulously assess their financial disposition, risk tolerance parameters, and conduct independent due diligence prior to engaging in any speculative activity.
BeeQuant - Hive Factra🔶 OVERVIEW
The "Hive Factra" is a groundbreaking analytical instrument designed to unveil the true essence of market movement, transforming complex price action into powerfully consolidated insights. Imagine having a specialized lens that intelligently reconstructs market periods into unique "Hive Factra Bars," revealing underlying momentum and high-conviction signals often obscured in traditional charts. This indicator cuts through the noise, showing you precisely when significant shifts are occurring by coloring these reconstructed bars with an adaptive precision. It's built for traders who seek unfiltered perspective that helps see hidden patterns and make more decisive moves.
__________________________________________________________________________
🧠 CONCEPTS
Markets move in impulses and compressions. Most trend indicators rely on single-frame slope logic, which often flips during minor pullbacks. Hive Factra takes a different route. At its core, the "Hive Factra" operates on a sophisticated framework that reinterprets market data, presenting it through its proprietary "Hive Factra Bars", unique visualizations that capture the consolidated spirit of price action.
⬜ The "Hive Factra" Reconstruction: Unlike standard candles, "Hive Factra Bars" are intelligently re-engineered representations of market activity. They are derived through a proprietary process that captures the dominant price influence over specific periods, presenting a clearer, more focused view of underlying momentum. These unique bars visually consolidate information, making the core directional bias immediately apparent.
⬜ The Adaptive Baseline: An internal, dynamic analysis line constantly adjusts to market flow, serving as a crucial reference point for the "Hive Factra Bars." This adaptive baseline provides real-time context, helping the indicator precisely determine the significance of each reconstructed bar's movement.
⬜ High-Conviction Coloring & Signal Bars: The "Factra Bars" come to life with a discerning coloring system. While they reflect the primary market direction (Green for upward bias, Red for downward bias), the "Hive Factra" introduces specialized "Signal Hive Bars" with distinct colors. These unique bars appear when the consolidated price action exhibits a particularly strong, high-conviction interaction with the adaptive baseline, acting as powerful visual alerts for moments of heightened significance.
⬜ Session-Aligned Insights: For intraday traders, the "Daily New Start" option provides a unique advantage. When enabled, the indicator can reset its internal reconstruction process with each new trading session, offering fresh, unbiased perspectives tailored to the day's distinct market dynamics.
⬜ Dynamic Sensitivity: A configurable "Offset" allows you to fine-tune the indicator's responsiveness and the thresholds for initiating these "Hive Factra Bars" and "Signal Hive Bars." This ensures the indicator aligns perfectly with your individual trading style and the volatility of the asset you're analyzing.
__________________________________________________________________________
✨ FEATURES
The "Hive Factra" is equipped with a suite of cutting-edge features, all meticulously designed for unparalleled clarity, adaptive responsiveness, and augmented analytical depth:
🔹 Proprietary Hive Factra Bars
Experience a unique visual representation of price action that consolidates market data for enhanced trend and momentum clarity.
🔹 Customizable Internal Analysis Line
Control the underlying adaptive baseline's calculation for precise alignment with market flow, utilizing various price source options.
🔹 High-Conviction "Signal Hive Bars" (Distinct Colors)
Receive specialized visual alerts when Factra Bars exhibit strong, decisive movements relative to the adaptive baseline, indicating moments of heightened market conviction.
🔹 Overbought/Oversold Visuals
Signal Hive Bars highlight areas of potential exhaustion, providing intuitive insight into stretched conditions
🔹 Session-Based Reconstruction
Opt for the "Daily New Start" to reset the indicator's perspective with each new trading day, providing fresh, session-aligned insights.
🔹 Dynamic Offset Control
Adjust the "Offset" parameter to fine-tune the sensitivity of the Factra Bar reconstruction and signal generation thresholds, tailoring the indicator to specific market conditions.
🔹 Non-Repainting Logic for Historical Reliability
Each "Hive Factra Bar" is plotted only when its internal reconstruction conditions are fully met and confirmed. This ensures that the historical display of Factra Bars does not repaint, providing a high degree of reliability and trust in past signals and visualizations.
🔹 Cross-Market Versatility
This indicator is engineered to perform with precision across all major markets—whether you're trading forex, commodities, stocks, or indices. Its adaptive logic automatically aligns with the unique volatility and structure of each asset class, delivering consistently reliable insights no matter where you trade.
🔹 Custom Range Start Marker
A subtle diamond-shaped symbol is plotted to indicate the start of the Hive Factra logic cycle. This marks the bar from which the internal price range begins accumulating until a new Hive Factra Bar is confirmed and displayed. Helps visualize the dynamic evaluation period used in Factra’s structural detection.
🔹 Smart Alerts for Key Events
Get notified in real time when:
◦ A new Hive Factra Bar completes – signaling a fresh structural range reset
◦ A new Signal Hive Bar closes – identifying a potential overbought or oversold condition
Built-in alert conditions make it easy to stay ahead of shifts without watching every candle manually.
🔹 Universal Timeframe Compatibility: The "Hive Factra" is meticulously engineered to perform flawlessly across all timeframes, from rapid intraday charts to long-term weekly and monthly views. This universal compatibility ensures you receive consistent, high-quality insights regardless of your analytical horizon.
🔹 Unrivaled External Indicator Collaboration: A truly unique advantage of the "Hive Factra" is its capability to seamlessly integrate and enhance the performance of other external indicators. Its meticulously processed output, can serve as a highly purified and consolidated 'source' for indicators that accept such inputs (e.g., RSI, StochRSI, moving averages), which allows for more insightful data stream into your favorite indicators, potentially unlocking new levels of responsiveness and signal accuracy for your entire analytical setup.
__________________________________________________________________________
⚙️ USAGE
Integrating the "Hive Factra" into your daily analytical regimen is intuitive and will profoundly enhance your ability to discern crucial market dynamics and spot high-conviction opportunities:
💁 Effortless Application
Simply add the "Hive Factra" indicator to any chart within your TradingView platform. Note that it plots on a separate panel below your main price chart to provide its unique visual output without obscuring price.
📊 Tailored Calibration: Access the indicator's settings to unlock its full potential:
⚙ "Internal EMA Config"
Configure the internal adaptive baseline by choosing its source (e.g., Close, HL/2) and length. This shapes the core reference point for the Factra Bars.
⚙ "Hive Factra"
Decide if you want "Daily New Start" for session-based analysis and choose the "Source" type for how the Factra Bars are built.
🤖 "Offset"
Experiment with the "Offset" percentage to adjust the sensitivity of the Factra Bar's reconstruction. A smaller offset will make the Factra Bars appear more frequently, while a larger one will highlight only more significant movements.
🟩🟥 Green/Red Hive Factra Bars
These indicate the consolidated directional bias of the market over the reconstructed period. A sequence of Green bars suggests sustained bullish pressure, while Red bars point to dominant bearish control.
🚀 "Signal Hive Bars" (Unique Colors)
Pay close attention to these specially colored Hive Factra Bars. They signify moments where the reconstructed price action exhibits a high-conviction interaction with its adaptive baseline, often preceding or confirming significant market moves. These are your clearest signals for potential shifts.
✨ Appearance of Hive Factra Bars
Notice that these Bars do not necessarily appear for every single time unit. They intelligently reconstruct and consolidate price action, appearing only when conditions align to present a coherent, high-impact view of market phases.
🪢 Harnessing External Synergy
To unlock a new dimension of analysis, consider integrating "Hive Factra" as the data source for other indicators:
1. When adding indicators like RSI, StochRSI, or others that prompt for a 'source' input, you can select the "Hive Factra" as the input.
2. For oscillators (e.g., RSI, Stochastic), choose the close or similar output from "Hive Factra" as your source. This allows the oscillator to react to the purified, consolidated momentum of the Factra Bars rather than raw price.
For moving averages (e.g., EMA, SMA), use the close or other relevant Factra Bar output as your source. This provides an exceptionally smooth and responsive average that tracks the true underlying trend.
__________________________________________________________________________
⚠️ LIMITATIONS
While the "Hive Factra" is an incredibly powerful tool for dissecting market dynamics, it's vital to understand its design parameters for optimal use. It does not attempt to front-run reversals or predict market turns. Instead, it focuses on framing price behavior so traders can react with context.
👉 Visual Gaps in Plotting: Due to Tradingview platform limitations with custom candle plotting functionality, you may observe visual gaps between "Hive Factra Bars" on the chart. This occurs because the indicator only plots a Hive Factra Bar when its internal conditions for reconstruction are fully met, and there isn't an 'offset' parameter for custom candles to bridge these visual discontinuities. Importantly, this behavior ensures that each plotted Factra Bar is confirmed and does not repaint, providing reliable historical analysis.
👉 Reconstructed Data, Not Raw Price: It's crucial to remember that "Hive Factra Bars" are not traditional candles. They are a derived visualization that intelligently consolidates price data.
👉 Complementary Tool: This indicator excels at providing high-conviction directional insights and identifying significant market phases. However, it is designed as a sophisticated complement to a broader trading strategy, not a standalone system.
👉 Input Calibration Essential: The effectiveness of the "Hive Factra" is highly dependent on careful calibration of its input parameters, especially the "Offset" and internal EMA settings. Optimal results require user experimentation to find settings best suited for specific assets and timeframes.
👉 Exclusion of Auxiliary Data: The "Hive Factra" focuses solely on transforming price data. It does not incorporate other vital market information such as trading volume, market breadth, or fundamental news. Integrating these additional analytical layers remains essential for a comprehensive trading strategy.
█ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 『•••• ✎ ••••』 ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ █
🎯 CONCLUSION
The "Hive Factra" offers an unparalleled, intuitive, and highly adaptable framework for instantly grasping true price momentum and direction through its intelligent reconstruction of market data. By transforming chaotic raw data into strikingly clear, high-conviction "Factra Bars" and dynamic signals, it empowers you to cut through distractions and identify critical market currents with ease. Its revolutionary capability for seamless collaboration with external indicators (like RSI, EMA, etc., by using its purified output as their source) means you can elevate the performance of your entire analytical suite to new levels of precision and clarity. Seamlessly integrate this advanced visual tool within your analytical framework to gain a sharper, more confident perspective, and elevate your strategic decision-making in the markets. It's about seeing the unseen, with enhanced clarity and a deeper understanding of market forces, now with the power to supercharge all your other tools.
▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣
🚨 RISK DISCLAIMER
Engagement in financial market speculation inherently carries a substantial degree of inherent risk, and the potential for capital diminution, potentially exceeding initial deposits, is a pervasive and non-trivial consideration. All content, algorithmic tools, scripts, articles, and educational materials disseminated by "Hive Factra" are exclusively purposed for informational and pedagogical objectives, strictly for reference. Historical performance data, whether explicitly demonstrated or implicitly suggested, offers no infallible assurance or guarantee of future outcomes. Users bear sole and ultimate accountability for their individual trading decisions and are emphatically urged to meticulously assess their financial disposition, risk tolerance parameters, and conduct independent due diligence prior to engaging in any speculative market activity.
BeeQuant - Hive Smoothing Average🔶 OVERVIEW
The "Hive Smoothing Average" is your gateway to crystal-clear market insights, a truly advanced tool that cuts through confusing price "noise" to reveal the true underlying trend. Imagine having a panoramic view of the market's true direction, unclouded by minor ups and downs. This powerful indicator dynamically filters out market distractions, presenting you with a highly refined line that not only shows you the genuine path of price but also changes color. It’s built for traders who demand clarity and want to confidently spot opportunities that others might miss in messy charts.
__________________________________________________________________________
🧠 CONCEPTS
At its heart, the "Hive Smoothing Average" employs a sophisticated multi-stage processing system to transform raw price data into an incredibly smooth and responsive smoothed moving average line. It's designed to give you an unparalleled view of market direction and momentum.
⬜ Synthesizes multiple smoothing layers to deliver a balanced representation of underlying price action.
⬜ Offers enhanced visual consistency by filtering volatility distortion without delay-based lag.
⬜ Presents color-coded transitions and signal markers to aid in directional conviction and structural flow.
⬜ Embeds a modular smoothing core adaptable across market environments and asset classes.
Hive Smoothing Average doesn't forecast, it refines. It provides a more coherent view of price evolution, allowing for higher-confidence discretion and more robust strategy overlays.
__________________________________________________________________________
✨ FEATURES
Hive Smoothing Average is loaded with flexibility and visual power to enhance your decision-making:
🔹Customizable Smoothing
Tailor the indicator’s core behavior using a wide range of smoothing algorithms — from classic to advanced — to match your trading tempo and asset dynamics.
🔹 Intelligent Color Feedback
The line color dynamically shifts to reflect meaningful trend transitions, offering at-a-glance clarity without crowding your chart.
🔹 Trend Signal Markers
Built-in arrow markers highlight potential transitions in price momentum, acting as subtle nudges to investigate further.
🔹 Multi-Timeframe Ready
Designed to operate cleanly across all timeframes, from scalping micro-trends to monitoring macro cycles.
🔹 External Source Collaboration
Hive Smoothing Average includes two flexible input channels that can seamlessly connect with other indicators on your chart.
🔹 Adaptive Bands
A powerful enhancement to the Hive framework, the optional Standard Deviation Bands add dynamic context to price behavior by highlighting how far price is moving relative to its recent average volatility.
Length: Controls the lookback period for volatility calculation.
Lower values (e.g., 20 – 50) make the bands highly reactive Higher values (e.g., 200 – 500) smooth out the bands (classic envelope systems )
These bands offer valuable visual cues for both volatility expansion and mean reversion potential, especially when combined with Hive’s core candle coloration logic.
🔹Non-Repainting Logic for Historical Reliability
Each "Hive Smoothing Average" is plotted only when its internal reconstruction conditions are fully met and confirmed. This ensures that the historical display of Hive Smoothing Average does not repaint, providing a high degree of reliability and trust in past signals and visualizations.
🔹Cross-Market Versatility
This indicator is engineered to perform with precision across all major markets—whether you're trading forex, commodities, stocks, or indices. Its adaptive logic automatically aligns with the unique volatility and structure of each asset class, delivering consistently reliable insights no matter where you trade.
__________________________________________________________________________
⚙️ USAGE
Getting started with Hive Smoothing Average is seamless and intuitive:
✨ Apply to Any Chart
Simply add the indicator to any asset or timeframe and see immediate transformation in chart clarity.
💹 Source Data Flexibility
Choose your preferred price data source for each smoothing stage (e.g., Close, Open, High, Low), providing complete control over the input feeding the sophisticated smoothing algorithms.
🛠️ Adjust Smoothing Behavior
Choose your preferred initial and final smoothing types (EMA, HMA, ALMA, etc.), and tweak lengths for desired responsiveness or smoothness.
📐 Use Bands for Confluence
Enable the Bands mode to visualize dynamic zones around your smoothed price. Useful for breakout validation and fade zones.
🟩 Green Smoother Line
Indicates strengthening bullish bias and upward progression.
🟥 Red Smoother Line
Suggests weakening or shifting trend toward bearish territory.
📈 Arrow Signals
Upward or downward triangles appear when directional bias changes — confirming subtle pivots in trend behavior.
🎯 Offset Adjustment
Fine-tune the visual positioning of the smoothed line and bands on your chart with a convenient "Offset" input.
📏 Lookback Filter
Activate the “Lookback Filter” setting to remove weaker signals based on custom historical logic. By checking recent candle behavior, it filters out low-quality transitions and only keeps strong, confirmed shifts — helping you avoid noise and stay focused on reliable breakouts.
Experiment with settings based on your trading timeframe. Short-term traders may prefer fast-reactive configurations, while swing or positional traders can explore higher-period smoothings for structural signals.
__________________________________________________________________________
⚠️ LIMITATIONS
While Hive Smoothing Average delivers incredible trend clarity, it’s essential to use it within its designed purpose:
👉 Visual Clarity, Not Trade Calls: This tool enhances visibility of market behavior, not automatic signals. Use it as a trusted lens — not a standalone system.
👉 Reactive, Not Predictive: Hive Smoothing Average responds to price action with refined smoothing. It is not a forecasting model.
👉 Config-Sensitive Output: Different smoothing setups can produce different levels of sensitivity or delay. Calibration matters — explore what fits your asset and style.
👉 Focuses on Price Action Only: It does not integrate volume, fundamentals, or external market influences. It’s engineered purely for price structure refinement.
█ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 『•••• ✎ ••••』 ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ █
🎯 CONCLUSION
Hive Smoothing Average provides a high-performance, low-noise framework to view price with remarkable clarity. With its adaptive smoothing layers, bands support, and intelligent signal markers, it becomes a powerful tool to enhance your trend confidence and charting efficiency. By furnishing immediate, data-driven feedback on the market's core momentum and signaling critical turning points, it profoundly empowers traders to rapidly ascertain nascent market shifts and identify pivotal directional changes. Seamlessly integrate this sophisticated visual tool within your pre-existing technical analysis architecture to acquire a sharper, more insightful perspective, and fundamentally elevate your strategic acumen, optimizing your decision-making processes to a degree previously unattainable. It's about experiencing the market's true rhythm.
▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣
🚨 RISK DISCLAIMER
Engagement in financial market speculation inherently carries a substantial degree of inherent risk, and the potential for capital diminution, potentially exceeding initial deposits, is a pervasive and non-trivial consideration. All content, algorithmic tools, scripts, articles, and educational materials disseminated by "Hive Smoothing Average" are exclusively purposed for informational and pedagogical objectives, strictly for reference. Historical performance data, whether explicitly demonstrated or implicitly suggested, offers no infallible assurance or guarantee of future outcomes. Users bear sole and ultimate accountability for their individual trading decisions and are emphatically urged to meticulously assess their financial disposition, risk tolerance parameters, and conduct independent due diligence prior to engaging in any speculative market activity.
BeeQuant - Hive HeikinAshi💠 OVERVIEW
The "Hive HeikinAshi" is your ultimate tool for simplifying the chaotic world of price charts. Imagine a specialized lens that cuts through all the market "noise" – those tiny, confusing movements – and reveals the clear, underlying current of price action. This indicator transforms standard, sometimes choppy, candlestick charts into a powerful, trend-focused visualization. It’s designed to help every trader, whether you're a discretionary trader seeking cleaner structures or a quant enthusiast looking for visual cues to complement models, Hive HeikinAshi provides a simplified yet highly informative lens through which to read price action.
Its main advantage lies in its seamless compatibility with external indicators — offering a next-level smoothing foundation that enhances the clarity and reliability of any existing trend, momentum, or signal-based system layered on top of it.
__________________________________________________________________________
🧠 CONCEPTS
At its core, the "Hive HeikinAshi" isn't just another way to look at candles; it's a profound re-interpretation of price dynamics. It employs a sophisticated internal process to distill raw market movements into a more coherent, trend-identifying display, making the market's story incredibly easy to read.
The "Hive" Transformation: Unlike traditional candlesticks that show every small price fluctuation, the "Hive HeikinAshi" candles are intelligently constructed to smooth out the data. They are derived from a multi-point calculation process, creating a new, more consistent visual representation of price. This transformation helps to reduce the "visual clutter" and make trend following a much more intuitive experience. You'll see the forest, not just the trees.
⬜ Highlights dominant price direction by filtering reactive fluctuations
⬜ Visually separates impulsive vs corrective behavior with clear color transitions
⬜ Enables quicker discretionary recognition of trend shifts without complex overlays
⬜ Ideal for confirming momentum zones and stable trending phases
⬜ The Intelligent Filter. An optional yet powerful "Filter" mechanism has been integrated, providing an additional layer of analytical discernment.
⬜ Designed to integrate natively with trend-following, oscillator, or signal indicators — enabling amplified precision across diverse trading systems
A significant advantage of the "Hive HeikinAshi" is its inherent ability to minimize distracting "noise" from typical candle wicks. While standard candles can often show long, confusing wicks that obscure the true body direction, our specialized candles are engineered to emphasize the core directional move. This intelligent design allows you to focus on the momentum generated by the candle's body, rather than getting sidetracked by fleeting price extremes, thereby providing a cleaner, more reliable visual of trend strength.
__________________________________________________________________________
✨ FEATURES
Hive HeikinAshi includes several key features designed for both clarity and functionality:
🔹Multi-Bar Averaging
Generates a visually balanced candle structure using averaged pricing across configurable recent bars.
🔹 Wickless Visualization
Candles are rendered without upper/lower shadows, enhancing trend detection and reducing signal confusion.
🔹 Signal Filter
Adaptive color filter using a dynamic high/low lookback logic
🔹 Directional Color Coding
Clean green/red coloring helps instantly interpret bullish or bearish pressure.
🔹 Adjustable History Depth
Customize how many bars are considered in the smoothing process to match your style and timeframe.
🔹 Invisible Price Feed Outputs
Underlying smoothed OHLC values are available for custom strategies or overlays.
🔹Non-Repainting Logic for Historical Reliability
Each "Hive HeikinAshi" is plotted only when its internal reconstruction conditions are fully met and confirmed. This ensures that the historical display of HeikinAshi does not repaint, providing a high degree of reliability and trust in past signals and visualizations.
🔹Cross-Market Versatility
This indicator is engineered to perform with precision across all major markets—whether you're trading forex, commodities, stocks, or indices. Its adaptive logic automatically aligns with the unique volatility and structure of each asset class, delivering consistently reliable insights no matter where you trade.
__________________________________________________________________________
⚙️ USAGE
Using Hive HeikinAshi is simple and effective:
📥 Add to Chart
Once access is granted, apply the indicator to any timeframe or asset directly from your TradingView invite-only indicators list.
⚙️ Tweak “No. of Bars”
This setting controls how far back the smoothing engine looks.
• Lower values = more responsive, shorter-term smoothing
• Higher values = steadier candles, better for macro trends
🎚️ Next, consider the "Filter" option:
Turn this on to activate the advanced filtering mechanism. Then, adjust the "lookback bars" (from 1 to 10). A smaller number here will make the filter more responsive to immediate "Hive HeikinAshi" candle extremes, while a larger number will require a more sustained breakout from the recent filtered range. Experiment to discover the optimal "sweet spot" that best reveals the underlying market flow for your specific strategy. The tooltip guides you to this optimal setting.
Disable "Filter": If turned off, the candles will revert to a more direct HeikinAshi coloration based purely on their calculated open and close, without the additional layer of range filtering.
🔍 Interpreting Candles
• 🟢 Green Candle: Bullish continuation zone
• 🔴 Red Candle: Bearish pressure dominates
• Lack of wick = strong directional conviction
Combine with your favorite indicators — Hive HeikinAshi acts as a foundation to reduce noise and enhance clarity across tools like EMAs, MACD, VWAP, and more.
__________________________________________________________________________
⚠️ LIMITATIONS
While Hive HeikinAshi provides clear visual advantages, it is important to understand its scope:
👉 Not a Signal Generator: This indicator excels at identifying and confirming trends, making it less suitable for pinpointing exact, high-frequency entry and exit points that require unadulterated real-time price. It prioritizes overall directional clarity.
👉 Lag by Design: Due to multi-bar data smoothing, candles reflect stable price behavior but not ultra-short-term fluctuations.
👉 No Volume or Macro Inputs: Hive HeikinAshi focuses purely on price structure — it does not include volume, news, or external conditions.
👉 Filter Calibration: While the "Filter" enhances clarity, its effectiveness is dependent on appropriate "lookback bars" calibration. Users should understand that adding filtering inherently balances responsiveness with a more refined signal, and finding the optimal setting is part of the analytical process.
█ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 『•••• ✎ ••••』 ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ █
🎯 CONCLUSION
Hive HeikinAshi is a powerful visual companion for modern traders seeking smoother, clearer price trends. By combining directional clarity with reduced chart clutter, it allows you to interpret the market with less noise and more confidence. Seamlessly integrate this advanced visual tool within your analytical framework to gain a sharper, more confident perspective, and elevate your strategic decision-making in the markets. It's about seeing the unseen, with clarity.
▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣
🚨 RISK DISCLAIMER
Engagement in financial market speculation inherently carries a substantial degree of inherent risk, and the potential for capital diminution, potentially exceeding initial deposits, is a pervasive and non-trivial consideration. All content, algorithmic tools, scripts, articles, and educational materials disseminated by "Hive HeikinAshi" are exclusively purposed for informational and pedagogical objectives, strictly for reference. Historical performance data, whether explicitly demonstrated or implicitly suggested, offers no infallible assurance or guarantee of future outcomes. Users bear sole and ultimate accountability for their individual trading decisions and are emphatically urged to meticulously assess their financial disposition, risk tolerance parameters, and conduct independent due diligence prior to engaging in any speculative market activity.
BeeQuant - Hive Visualizer💠 OVERVIEW
The " Hive Visualizer " is a game-changing, invite-only tool, expertly designed to give every trader, from beginner to experienced, instant and clear visual clues about what price is doing. Its main job is to easily show you the highest and lowest points price has reached recently. Think of it as a smart, automated helper that colors your candles to reveal powerful market moves. This helps you quickly see if prices are getting stronger or weaker right on your chart. It's a groundbreaking, high-quality tool that cuts through the noise, making it simple to spot key moments when the market is about to make a big move up or down, giving you an edge.
__________________________________________________________________________
🧠 CONCEPTS
The core philosophy behind Hive Visualizer is rooted in contextual volatility exposure and directional bias reinforcement. Through a sophisticated internal mechanism that evaluates local maxima/minima behavior within a compact temporal field, the indicator provides adaptive color‑based candle transitions that align with latent directional pressure.
1. Uses localized equilibrium breach detection to monitor directional intent and exhaustion points.
2. Embeds a dynamically updating framework that reacts to both trend continuation and structural reversals.
3. Avoids false positives by disregarding noisy fluctuations below system‑defined relevance thresholds.
4. Provides non‑repainting, fully forward‑confirmed visual outputs for reliable retrospective analysis.
Hive Visualizer is not designed to be predictive. Instead, it allows traders to observe the evolution of price structure in a cleaner and more digestible format, supporting high-confidence discretionary execution or automated model overlays.
__________________________________________________________________________
✨ FEATURES
The "Hive Visualizer" comes with a suite of smart features, all designed for amazing clarity, quick reactions, and deeper understanding, making your charting experience truly effortless:
🔹 Easy Range Customization
A super easy "Smoother" setting lets you perfectly adjust how the indicator reacts to recent price changes. This means you can fine-tune it to match exactly how you like to trade
🔹 Instant, Clear Signals
The simple Green and Red candles give you immediate, unmistakable visual cues about strong upward or downward moves, providing insights you can grasp in a heartbeat.
🔹 Smart Continuity in Quiet Times
The clever way it keeps the same color for candles that aren't breaking out offers valuable, subtle insights into those periods when the market is just moving sideways or finding its balance, helping you see the hidden dynamics.
🔹 Seamless Chart Integration
This indicator works like a transparent overlay, appearing directly on your price chart without getting in the way or changing your original candles. It fits perfectly, making your analysis smooth and uninterrupted.
🔹 Clean and Focused Visuals
The indicator’s simple design focuses only on coloring the main candle body and border to clearly highlight important breakouts. This keeps your chart clean and effective, showing you only what truly matters.
🔹 Cross-Market Versatility
This indicator is engineered to perform with precision across all major markets—whether you're trading forex, commodities, stocks, or indices. Its adaptive logic automatically aligns with the unique volatility and structure of each asset class, delivering consistently reliable insights no matter where you trade.
__________________________________________________________________________
⚙️ USAGE
Using and making the "Hive Visualizer" a part of your trading routine is incredibly simple and designed to significantly boost how you understand the market:
Getting Started: Once you have access, just add the "Hive Visualizer" indicator to any chart and timeframe you want on TradingView. It's that easy.
Tuning the "Smoother" Setting: Go into the indicator's settings and play with the "Smoother" number. This is a crucial step to make it react just right for you.
Smaller numbers (like 1-3 bars) will make the indicator very quick to react to the most recent, short-term ups and downs, perfect for fast trading.
Larger numbers (like 5-10+ bars) will give you a wider view, smoothing out small changes and highlighting bigger, more important breakouts, ideal for longer-term analysis. Spend a little time trying different settings to find what works best for your chosen asset and your trading style – it's like finding the perfect lens for your market view.
Understanding the Colors: Once you've set it up, here's how to quickly understand what the "Hive Visualizer" is telling you: New Green Candle: This means a strong sign that buyers are in control and prices are likely to keep moving up, giving you confidence in bullish moves.
New Red Candle: This indicates as a strong signal that sellers are dominating and prices are likely to keep moving down, preparing you for bearish shifts.
__________________________________________________________________________
⚠️ LIMITATIONS
👉 Visual Guide, Not a Bot: Use as part of a broader strategy—it won’t auto‑trade for you
👉 Retroactive Insight: It reflects past price action; it doesn’t predict the future.
👉 Setting‑Dependent: Effectiveness relies on your “Smoother” choice—too low = noise; too high = lag.
👉 Price‑Range Focused: Highlights trends and range only — doesn’t analyze volume, news, or other complex factors.
👉 This tool enhances trend validation but isn’t a standalone signal generator.
█ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 『•••• ✎ ••••』 ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ █
🎯 CONCLUSION
The "Hive Visualizer" offers an incredibly easy-to-use and adaptable way to see price strength and weakness with crystal clarity on your charts. By giving you instant, clear feedback on whether prices are powerfully breaking out or falling below a recent historical range, it truly empowers you to quickly understand market momentum and spot key turning points. Seamlessly add this smart visual tool into your current trading methods to gain a sharper, more insightful view, and elevate your trading decisions. It's about seeing the market with new eyes.
▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣
🚨 RISK DISCLAIMER
Engagement in financial market speculation inherently carries a substantial degree of inherent risk, and the potential for capital diminution, potentially exceeding initial deposits, is a pervasive and non-trivial consideration. All content, algorithmic tools, scripts, articles, and educational materials disseminated by "Hive Visualizer" are exclusively purposed for informational and pedagogical objectives, strictly for reference. Historical performance data, whether explicitly demonstrated or implicitly suggested, offers no infallible assurance or guarantee of future outcomes. Users bear sole and ultimate accountability for their individual trading decisions and are emphatically urged to meticulously assess their financial disposition, risk tolerance parameters, and conduct independent due diligence prior to engaging in any speculative market activity.
VWAP/VOL [Extension] | FractalystWhat's the indicator's purpose and functionality?
The VWAP/VOL Extension is designed specifically as a bias identification system for the Quantify Trading Model.
This extension uses volume-weighted average price analysis combined with institutional volume classification to automatically detect market bias without requiring optimization periods that lead to overfitting.
The system provides real-time bias signals (bullish/bearish/neutral) that integrate directly with Quantify's machine learning algorithms, enabling institutional-level backtesting and automated entry/exit identification based on genuine market structure rather than curve-fitted parameters.
How does this extension work with the Quantify Trading Model?
The VWAP/VOL Extension serves as the bias detection engine for Quantify's automated trading system.
Instead of manually selecting bias direction, this extension automatically identifies market bias using:
- Volume-weighted VWAP analysis with three-state detection (bullish/bearish/neutral)
- Institutional volume classification using relative volume thresholds without optimization
- Non-repainting architecture ensuring consistent bias signals for Quantify's machine learning
The extension outputs bias signals that Quantify uses as input through the `input.source()` function, allowing the Trading Model to focus on optimal entry/exit timing while the extension handles bias identification.
Why doesn't this use optimization periods like other indicators?
The VWAP/VOL Extension deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses:
- Fixed mathematical thresholds based on market structure principles rather than optimized parameters
- Relative volume analysis using standard 2.0x/0.5x ratios that work across all market conditions
- VWAP distance calculations based on percentage thresholds without curve-fitting
- Gap enforcement using fixed 5-bar minimums for disciplined bias detection
This approach ensures the bias signals remain robust across different market regimes without the performance degradation typical of over-optimized systems.
Can this extension be used independently for discretionary trading?
No, the VWAP/VOL Extension is specifically engineered to work as a component within the Quantify ecosystem. The extension is designed to:
- Provide bias input for Quantify's machine learning algorithms
- Enable automated backtesting through systematic bias identification
- Support institutional-level analysis when combined with Quantify's ML entry model
Using this extension independently would miss the primary value proposition of systematic entry/exit optimization that Quantify provides.
The extension handles bias detection so Quantify can focus on probability-based trade timing and risk management.
How does this enable institutional-level backtesting?
The extension transforms discretionary bias identification into systematic institutional analysis by:
- Eliminating subjective bias selection through automated VWAP/volume analysis
- Providing consistent historical signals with non-repainting architecture for accurate backtesting
- Integrating with Quantify's algorithms to identify optimal entry patterns based on objective bias states
- Enabling performance analysis across multiple market regimes without optimization bias
This combination allows Quantify to run institutional-grade backtests with consistent bias identification, generating reliable performance statistics and risk metrics that reflect genuine market edge rather than curve-fitted results.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both VWAP/VOL Extension and Quantify Trading Model to your chart
- Select VWAP/VOL Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, volume conviction, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the VWAP/VOL Extension work best on?
The VWAP/VOL Extension performs optimally on markets with consistent, high-volume participation since the system relies on institutional volume analysis for bias detection. Futures markets provide the most reliable performance due to their centralized volume data and continuous institutional participation.
Recommended Futures Markets:
- ES (S&P 500 E-mini) - Over 2 million contracts daily volume, excellent liquidity depth
- NQ (NASDAQ-100 E-mini) - Around 600,000 contracts daily, strong tech sector representation
- YM (Dow Jones E-mini) - Consistent institutional flow and volume patterns
- RTY (Russell 2000 E-mini) - Small-cap exposure with reliable volume data
- GC (Gold Futures) - High volume commodity with institutional participation
- CL (Crude Oil Futures) - Energy sector representation with strong volume consistency
Why Futures Markets Excel:
- Futures markets provide centralized volume reporting, ensuring the extension's volume classification system receives accurate institutional participation data. The standardized contract specifications and continuous trading hours create consistent volume patterns that the extension's algorithms can analyze effectively.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
The extension is specifically designed to integrate with Quantify's portfolio management system, allowing multiple strategies across different timeframes and assets to operate simultaneously while maintaining consistent bias identification methodology across the entire automated trading portfolio.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The VWAP/VOL Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides volume-weighted institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate volume-based analysis. The extension's performance depends on accurate volume data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate volume reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange volume reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, volume reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The VWAP/VOL Extension, including all proprietary algorithms, volume classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, volume classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, volume pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate volume-based analysis assumptions.
Terms of Service Acceptance
Continued use of the VWAP/VOL Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
QuantFrame | FractalystWhat’s the purpose of this indicator?
The purpose of QuantFrame is to provide traders with a systematic approach to analyzing market structure, eliminating subjectivity, and enhancing decision-making. By clearly identifying and labeling structural breaks, QuantFrame helps traders:
1. Refine Market Analysis: Transition from discretionary market observation to a structured framework.
2. Identify Key Levels: Highlight important liquidity and invalidation zones for potential entries, exits, and risk management.
3. Streamline Multi-Timeframe Analysis: Track market trends and structural changes across different timeframes seamlessly.
4. Enhance Consistency: Reduce guesswork by following a rule-based methodology for identifying structural breaks.
How Does This Indicator Identify Market Structure?
1. Swing Detection
• The indicator identifies key swing points on the chart. These are local highs or lows where the price reverses direction, forming the foundation of market structure.
2. Structural Break Validation
• A structural break is flagged when a candle closes above a previous swing high (bullish) or below a previous swing low (bearish).
• Break Confirmation Process:
To confirm the break, the indicator applies the following rules:
• Valid Swing Preceding the Break: There must be at least one valid swing point before the break.
3. Numeric Labeling
• Each confirmed structural break is assigned a unique numeric ID starting from 1.
• This helps traders track breaks sequentially and analyze how the market structure evolves over time.
4. Liquidity and Invalidation Zones
• For every confirmed structural break, the indicator highlights two critical zones:
1. Liquidity Zone (LIQ): Represents the structural liquidity level.
2. Invalidation Zone (INV): Acts as Invalidation point if the structure fails to hold.
What do the extremities show us on the charts?
When using QuantFrame for market structure analysis, the extremities—Liquidity Level (LIQ) and Invalidation Level (INV)—serve as critical reference points for understanding price behavior and making informed trading decisions.
Here's a detailed explanation of what these extremities represent and how they function:
Liquidity Level (LIQ)
Definition: The Liquidity Level is a key price zone where the market is likely to retest, consolidate, or seek liquidity. It represents areas where orders are concentrated, making it a high-probability reaction zone.
Purpose: Traders use this level to anticipate potential pullbacks or continuation patterns. It helps in identifying areas where price may pause or reverse temporarily due to the presence of significant liquidity.
Key Insight: If a candle closes above or below the LIQ, it results in another break of structure (BOS) in the same direction. This indicates that price is continuing its trend and has successfully absorbed liquidity at that level.
Invalidation Level (INV)
Definition: The Invalidation Level marks the threshold that, if breached, signifies a structural shift in the market. It acts as a critical point where the current market bias becomes invalid.
Purpose: This level is often used as a stop-loss or re-evaluation point for trading strategies. It ensures that traders have a clear boundary for risk management.
Key Insight: If a candle closes above or below the INV, it signals a shift in market structure:
A closure above the INV in a bearish trend indicates a shift from bearish to bullish bias.
A closure below the INV in a bullish trend indicates a shift from bullish to bearish bias.
What does the top table display?
The top table in QuantFrame serves as a multi-timeframe trend overview. Here’s what it provides:
1. Numeric Break IDs Across Multiple Timeframes:
• Each numeric break corresponds to a confirmed structural break on a specific timeframe, helping traders track the most recent breaks systematically.
2. Trend Direction via Text Color:
• The color of the text reflects the current trend direction:
• Blue indicates a bullish structure.
• Red signifies a bearish structure.
3. Higher Timeframe Insights Without Manual Switching:
• The table eliminates the need to switch between timeframes by presenting a consolidated view of the market trend across multiple timeframes, saving time and improving decision-making.
What is the Multi-Timeframe Trend Score (MTTS)?
MTTS is a score that quantifies trend strength and direction across multiple timeframes.
How does MTTS work?
1. Break Detection:
• Analyzes bullish and bearish structural breaks on each timeframe.
2. Trend Scoring:
• Scores each timeframe based on the frequency and quality of bullish/bearish breaks.
3. MTTS Calculation:
• Averages the scores across all timeframes to produce a unified trend strength value.
How is MTTS interpreted?
• ⬆ (Above 50): Indicates an overall bullish trend.
• ⬇ (Below 50): Suggests an overall bearish trend.
• ⇅ (Exactly 50): Represents a neutral or balanced market structure.
How to Use QuantFrame?
1. Implement a Systematic Market Structure Framework:
• Use QuantFrame to analyze market structure objectively by identifying key structural breaks and marking liquidity (LIQ) and invalidation (INV) zones.
• This eliminates guesswork and provides a clear framework for understanding market movements.
2. Leverage MTTS for Directional Bias:
• Refer to the MTTS table to identify the multi-timeframe directional bias, giving you the broader market context.
• Align your trading decisions with the overall trend or structure to improve accuracy and consistency.
3. Apply Your Preferred Entry Model:
• Once the market context is clear, use your preferred entry model to capitalize on the identified structure and trend.
• Manage trades dynamically as price delivers, using the provided liquidity and invalidation zones for risk management.
What Makes QuantFrame Original?
1. Objective Market Structure Analysis:
• Unlike subjective methods, QuantFrame uses a rule-based approach to identify structural breaks, ensuring consistency and reducing emotional decision-making.
2. Multi-Timeframe Integration:
• The MTTS table consolidates trend data across multiple timeframes, offering a bird’s-eye view of market trends without the need to switch charts manually.
• This unique feature allows traders to align strategies with higher-timeframe trends for more informed decision-making.
3. Liquidity and Invalidation Zones:
• Automatically marks Liquidity (LIQ) and Invalidation (INV) zones for every structural break, providing actionable levels for entries, exits, and risk management.
• These zones help traders define their risk-reward setups with precision.
4. Dynamic Trend Scoring (MTTS):
• The Multi-Timeframe Trend Score (MTTS) quantifies trend strength and direction across selected timeframes, offering a single, consolidated metric for market sentiment.
• This score is visualized with intuitive symbols (⬆, ⬇, ⇅) for quick decision-making.
5. Numeric Labeling of Breaks:
• Each structural break is assigned a unique numeric ID, making it easy to track, analyze, and backtest specific market scenarios.
6. Systematic Yet Flexible:
• While it provides a structured framework for market analysis, QuantFrame seamlessly integrates with any trading style. Traders can use it alongside their preferred entry models, adapting it to their unique strategies.
7. Enhanced Market Context:
• By combining structural insights with directional bias (via MTTS), the indicator equips traders with a complete market context, enabling them to make better-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Matrix Glitch | FractalystThe Matrix Glitch indicator is a visually engaging tool for traders, inspired by the iconic Matrix movie effects. It overlays price charts with dynamic, multi-colored glitches that sync with market data, creating a striking, almost surreal visual experience.
The indicator uses characters from various languages (e.g., Japanese, Chinese, Russian, English) to mimic the digital rain effect from the movies. Users can select a language, which activates a corresponding array of characters. These characters are randomly picked from the chosen array and displayed on the chart.
Underlying Calculations and Logic
Arrays in the Indicator
1- Character Management:
The script uses arrays to store sets of characters representing different symbols or alphabets. These arrays allow the indicator to dynamically select and update characters for display. Each element in these arrays corresponds to a specific character that will be used to populate the grid.
2- Current and Previous States:
Arrays are employed to keep track of the current state of characters that are displayed on the grid. Simultaneously, another set of arrays records the previous state of these characters. This dual-state management allows the script to smoothly transition between updates, handling changes in characters and visual effects like fading.
3- Transparency Control:
Transparency levels for each character in the grid are managed through arrays. These arrays store the opacity values, ensuring that each character has the appropriate level of transparency. By comparing the current and previous transparency states, the script can create effects like gradual fading or intensifying visibility.
4- Rain Effect Simulation:
To create the "rain" effect, the script maintains arrays that simulate the falling text by continuously updating the position and visibility of characters. As new characters enter the top of the grid, older ones are removed from the bottom, with their transparency levels adjusted to simulate movement.
5- Operational Flow:
Initialization : Arrays are initialized to manage both the characters and their transparency. This setup allows the script to handle the dynamic display efficiently.
Updates : During each cycle, new characters are selected and old characters are shifted accordingly. The arrays ensure that both the content and appearance of the grid are updated seamlessly.
Rendering : The arrays dictate how characters and their transparency are rendered on the grid, ensuring a cohesive and visually appealing effect.
Here's how to use the indicator step-by-step:
1- Apply the Indicator to Your Charts:
Begin by adding the indicator to your chart. This will activate the visual effect on your selected trading instrument or time frame.
Select Your Preferred Language of the Matrix Characters:
In the settings, choose the language or symbol set you want the matrix characters to display. This could be anything from traditional matrix-style characters to different alphabets or custom symbols.
2- Choose the Matrix Effect (Rain, Burst):
Decide on the type of visual effect you prefer. You can select from options like the classic "rain" effect, where characters fall from the top of the screen, or a "burst" effect, where characters explode outward or appear in a different dynamic pattern.
3- Adjust the Color According to Your Preference:
Customize the color of the matrix characters to suit your aesthetic or chart theme. You can select from a range of colors or even set up a gradient for more complex visual effects.
4- Adjust the Width and Height of the Matrix According to Your Screen:
Fine-tune the dimensions of the matrix display. Set the width and height so that the matrix fits perfectly on your screen, ensuring that it aligns well with other chart elements and doesn't obstruct your view.
------
What Makes the Matrix Glitch Indicator Unique?
Language Selection:
Customizable Language: Unlike many indicators that might offer static or limited visual elements, the Matrix Glitch Indicator allows users to choose from a variety of languages for the characters displayed. This feature not only personalizes the user experience but also adds a cultural or linguistic element to trading charts. Users can select languages like Japanese, Chinese, Russian, or English, and many more.
This flexibility ensures that traders from different backgrounds can feel a connection with their charts through familiar or exotic scripts.
Dynamic Effects:
Effect Modes: The indicator offers two distinct modes - Rain Mode and Burst Mode. In Rain Mode, characters fall from the top of the chart, mimicking the iconic digital rain from the Matrix films.
In Burst Mode, characters radiate outward from a central point, creating a unique visual effect that can be synchronized with market volatility.
This dual-mode functionality allows traders to choose how they want their data to be visually represented, providing both aesthetic variety and potentially different insights into market behavior.
Color Customization:
Full Color Control: The ability to fully customize the color of the characters is a standout feature. Traders can match the indicator's colors to their trading platform's theme, their mood, or even specific market conditions (e.g., red for downturns, green for upturns). This level of customization not only aids in creating a personalized trading environment but can also serve as a visual cue for different market states.
Universal Display Compatibility:
Adjustability for All Displays: The indicator is designed to be fully adjustable for various screen resolutions and sizes. This ensures that whether you're trading on a high-resolution monitor, a laptop, or even a mobile device, the Matrix Glitch effect remains clear and impactful without compromising on the functionality of the trading chart. This adaptability is crucial in an era where trading can happen anywhere, making the indicator a versatile tool for traders on the go or in a static setup.
------
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
OptiRange | FractalystWhat’s the purpose of this indicator?
This indicator is designed to integrate probabilities with liquidity levels, while also providing a mechanical method for identifying market structure by using Fractals by Williams.
----
How does this indicator identify market structure?
This script identifies breaks of market structure by analyzing candle closures above or below swing levels.
As soon as a candle has closed above or below the initial swing on your charts, the script validates that there is at least one swing preceding the break before confirming it as a structural break.
Once a break is occured then it assigns a numeric ID to the break starting from 1 and draws two extremities: one as liquidity and the other as invalidation (LIQ/INV).
----
What do the extremities show us on the charts?
you'll see two clear extremities on your charts:
1. The first extremity represents the structural liquidity level. (LIQ)
2. The other extremity indicates the level that, if price breaks through it, results in a structural shift to the opposite side. (INV)
----
How does it calculate probabilities?
Each break of market structure, denoted as X, is assigned a unique ID, starting from X1 for the first break, X2 for the second, and so on.
The probabilities are calculated based on breaks holding, meaning price closing through the liquidity level, rather than invalidation. This probability is then divided by the total count of similar numeric breaks.
For example, if 75 out of 100 bullish X1s become X2, then the probability of X1 becoming X2 on your charts will be displayed as 80% in the following format: ⬆ 75%
----
What are the Fractal blocks?
Fractal blocks refer to the most extreme swing candle within the latest break. They can serve as significant levels for price rejection and may guide movements toward the next break, often in confluence with probability analysis for added confirmation.
If the price retraces back to a bullish fractal block, we aim to look for buy/long positions. Conversely, if the price retraces back to a bearish fractal block, we aim to look for sell/short positions.
----
What are mitigations?
Mitigations refer to specific price action occurrences identified by the script:
1- When the price reaches the most recent fractal block and confirms a swing candle, the script automatically draws a line from the swing to the fractal block bar and labels it with a checkmark.
1- If the price wicks through the invalidation level and then retraces back to the fractal block while forming a swing candle, the script labels this as a double mitigation on the chart.
This level will serve as the next potential invalidation level if a break occurs in the same direction.
----
What does the bottom table display?
The bottom table presents numeric breaks across multiple timeframes, with the text color indicating the trend direction. Enabling traders to assess the higher timeframes market trend without needing to switch between timeframes manually.
----
How to use the indicator?
1. Add "OptiRange | Fractalyst" to your TradingView chart.
2. Choose the pair you want to analyze or trade.
3. Start with the 12-month timeframe.
4. Use the table bias with the maximal settings to find the lowest timeframe that’s showing you the mitigation (✓)
5. Confirm that the probability of the current liquidity is higher than 50%.
6. Place your limit order at the Fibonacci level of 0.618 of the mitigation candle.
7. Set your stop-loss at the mitigation level.
8. Determine your take profit based on the liquidity of the current timeframe, or if possible, the liquidity of a higher timeframe in the same direction; otherwise, use the liquidity of the current timeframe.
9. Risk adjustment and Trade management based on your personal preferences.
Example:
----
User-input settings and customizations
----
What makes this indicator original?
- This script leverages Fractals, a fundamental concept in many trading methodologies.
- For a break to be considered valid, price must have at least two swings:
a swing high followed by a swing low for bullish breaks and a swing low follow by a swing high for bearish breaks.
- This means that each swing point is confirmed by the formation of two candles on its left and two candles on its right, totaling 5 candles for each swing high and swing low, thus requiring 10 candles overall. (This strict rule ensures a thorough assessment of market structure before confirming a break.)
- The script assigns a unique numerical ID to each break of structure, starting from 1.
This numbering system enables the script to calculate the probability of the most recent break becoming the next break, while also factoring in the trend direction.
- Additionally, this script provides insights into higher timeframes' break IDs in the bottom/top centre table, keeping traders informed about the overall higher timeframe picture.
- By integrating these methodologies, the script introduces a unique and systematic method for identifying market structure, thereby enhancing its originality in guiding trading decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. By utilizing our charting tools, the buyer acknowledges that neither the seller nor the creator assumes responsibility for decisions made using the information provided. The buyer assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses. Therefore, by purchasing these charting tools, the customer acknowledges that neither the seller nor the creator is liable for any unfavorable outcomes resulting from the development, sale, or use of the products.
The buyer is responsible for canceling their subscription if they no longer wish to continue at the full retail price. Our policy does not include reimbursement, refunds, or chargebacks once the Terms and Conditions are accepted before purchase.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer.
Real Cummulative Delta (New TV Function)Thanks to the new TradingView indicator Up/Down Volume, it is now possible to get accurate information on Agression (market buying vs market selling)
However, as they only provide the value of delta, I've made this indicator to show the cummulative value, in the form of candles.
It is great to detect divergences in the macro and in the micro scale (As in divergences in each candle and divergences in higher or lower tops or bottoms)
Hope you can make good use of it!
Yield Trend Indicator - The Quant ScienceYield Trend Indicator - The Quant Science™ is a quantitative indicator representing percentage yields and average percentage yields of three different assets.
Percentage yields are fundamental data for all quantitative analysts. This indicator was created to offer immediate calculations and represent them through an indicator consisting of lines and columns. The columns represent the percentage yield of the current timeframe, for each asset. The lines represent the average percentage yield, of the current timeframe, for each asset.
The user easily adds tickers from the user interface and the algorithm will automatically create the quantitative data of the chosen assets.
The blue refers to the main asset, the main set on the chart.
The yellow refers to the second asset, added by the user interface.
The red refers to the third asset, added by the user interface.
The timeframe is for all assets the one set to the chart, if you use a chart with timeframe D, all data is processed on this timeframe. You can use this indicator on all timeframes without any restrictions.
The user can change the type of formula for calculating the average yield easily via the user interface. This software includes the following formulas:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. VWMA (Volume Weighted Moving Average)
The user can customize the indicator easily through the user interface, changing colours and many other parameters to represent the data on the chart.
Ethereum OnChain Data Indicator - The Quant ScienceEthereum On Chain Data Indicator - The Quant Science™ is a quantitative indicator created for mid-long term analysis.
The indicator uses quantitative statistics to recreate a model that represents the most important data from the on-chain analysis for the Ethereum blockchain.
The on-chain data used to create this model are:
1. Total weekly transactions
2. Total monthly transactions
3. Frequency of transactions per second on a daily scale
4. Frequency of transactions per second on a weekly scale
5. Amount of Ethereum burned on a daily scale
6. Amount of Ethereum burned on a weekly scale
7. Volume of short positions on a daily scale
8. Volume of short positions on a weekly scale
9. Volume of short positions more/less than average on a daily scale
10. Volume of short positions more/less than average on a weekly scale
All these data were extrapolated and manipulated using the mean and standard deviation.
The end result is a powerful tool that enables mid-long term investors and traders to analyze on-chain data through quantitative analysis.
FEATURES
The blue color area refers to the average change in data on a weekly scale. The light blue colored area indicates the monthly changes in the data. It is interesting to observe the correlation relationship between price and times when short-run data increases compared to long-run data and vice versa.
The more intense purple histograms refer to the standard deviation of the mean change in data on an annual scale. Histograms of less intense purple color refer to the standard deviation of the mean variation of data on a monthly scale. It is interesting to observe the ratio of the standard deviation between two different time periods.
This indicator can be used to perform statistical comparative analysis for manual and mid-long term investments. It can also be used to create auto trading strategies when used and integrated within an algorithm.
On-chain data are updated every 24 hours, so the timeframes to be used for analysis with this indicator are: D, 4H, 1H.
Prime Distance Frame Quant Model for Risk Reward & Pivot PointsIn this script we take all of the prime numbers up to 100 and plot them as olive lines and then consider the distance between two adjacent plots and color code these distances with the fill function. This allows us to find higher and lower prime gaps allowing us to make much more informed decisions on our risk reward for a given trade and the levels where we should consider taking profit.
The Script includes scaling for all assets and is intended to be used for crypto trading.
Terminal : Important U.S Indices Change (%) DataHello.
This script is a simple U.S Indices Data Terminal.
You can also set the period to look back manually in the menu.
In this way, an idea can be obtained about Major U.S Indices.
Features
Value changes on a percentage basis (%)
Recently, due to increasing interest, the NQNACE index has been added.
Index descriptions are printed on the information panel.
Sentiment NYSE ARCA and AMEX indices added.
Indices
SP1! : S&P 500 Futures Index
DJI : Dow Jones Industrial Average Index
NDX : Nasdaq 100 Index
RUT : Russell 2000 Index
NYA : NYSE Composite Index
OSX : PHLX Oil Service Sector Index
HGX : PHLX Housing Sector Index
UTY : PHLX Utility Sector Index
SOX : PHLX Semiconductor Sector Index
SPSIBI : S&P Biotechnology Select Industry Index
XNG : NYSE ARCA Natural Gas Index
SPGSCI : S&P Goldman Sachs Commodity Index
XAU : PHLX Gold and Silver Sector Index
SPSIOP : S&P Oil and Gas Exploration and Production Select Industry Index
GDM : NYSE ARCA Gold Miners Index
DRG : NYSE ARCA Pharmaceutical Index
TOB : NYSE ARCA Tobacco Index
DFI : NYSE ARCA Defense Index
NWX : NYSE ARCA Networking Index
XCI : NYSE ARCA Computer Technology
XOI : AMEX Oil Index
XAL : AMEX Airline Index
NQNACE : Nasdaq Yewno North America Cannabis Economy Index
Terminal : USD Based Stock Markets Change (%)Hello.
This script is a simple USD Based Stock Markets Change (%) Data Terminal.
You can also set the period to look back manually in the menu.
In this way, an idea can be obtained about Countries' Stock Markets.
And you can observe the stock exchanges of relatively positive and negative countries from others.
Features
Value changes on a percentage basis (%)
Stock exchange values are calculated in dollar terms.
Due to the advantage of movement, future data were chosen instead of spot values on the required instruments.
Stock Markets
Usa : S&P 500 Futures
Japan: Nikkei 225 Futures
England: United Kingdom ( FTSE ) 100
Australia: Australia 200
Canada: S&P / TSX Composite
Switzerland: Swiss Market Index
New Zealand: NZX 50 Index
China: SSE Composite (000001)
Denmark: OMX Copenhagen 25 Index
Hong-Kong: Hang Seng Index Futures
India: Nifty 50
Norway: Oslo Bors All Share Index
Russia: MOEX Russia Index
Sweden: OMX Stockholm Index
Singapore: Singapore 30
Turkey: BIST 100
South Africa: South Africa Top 40 Index
Spain: IBEX 35
France: CAC 40
Italy: FTSE MIB Index
Netherlands: Netherlands 25
Germany : DAX
Regards.
General Data TerminalHello.
This script is a simple General Data Terminal.
You can also set the period to look back manually in the menu.
In this way, an idea can be obtained about Global Markets.
Note : TIO = Iron Ore
Regards.
Basic Forex TerminalHello,
This script is a simple Forex terminal.
It serves the same purpose as Heatmaps.
You can also set the period to look back manually in the menu.
Major indicators are taken into account.
In this way, an idea can be obtained about all major and minor currencies.
Best regards.
Strategy Builder Crypto (Single Trend/Plots)Hi everyone
Big program for the daily indicator
This one will be free on trial only for a week because it has an immense value and required quite a lot of work. For more info to use it long-term, please DM me
That out of the way, let's dive right in...
This is a huge upgrade from that script Ultimate-Algorithm-Builder-Single-Trend
The Tradingview non-pro users will appreciate it because it allows to add the selected subsequent indicators as well. The Pro users too will likely like this feature equally, what the H*** I'm saying :)
This indicator will transform you into what I was in the past... into a quant trader. You'll build your own trading algorithm in a few clicks only
Which timeframe and which assets ?
Short answer : ALL and ALL
You'll have to define the configuration of the tool based on your capital, psychology. For custom configuration of the tool, please DM me directly so that we can discuss further
But a few words of advices anyway :
the bigger the timeframe, the lower the inputs (and vice-versa)
Think about how much $$ you want to make per trade and define your entries from there
Think about how much $$ you can afford to lose per trade and define the supertrend from there
...
Your golden configuration might not work for all assets.
You might have to create some tweaks - for instance you found a great config for BTCUSD but it's not working for ETHUSD, then you can create a copy of your BTCUSD chart and set a new config for ETHUSD
What are the indicators inside :
This fantastic tool that I personally use for my trading detects convergence between the following indicators :
Overlay - meaning if the price close above/below a moving average
Trend Signal - to detect if the the DOW law is broken and predict a possible reversal - en.wikipedia.org/wiki/Dow_theory
In other words, it detects if the higher highs or lower lows sequence is broken
MACD or MACD Zero Lag
MA Cross - Cross of moving averages
Ichimoku - if the price closes below/above the cloud
Supertrend - used to detect polarity zones
TSI Shadow -
Pullback
You'll also have the possibility to define a pullback on a given MA. That means basically that you'll get a convergence and it will only display a signal when it will pullback first
This will reduce your losses in case of invalidation and maximize your gains as it will enter the trade in a better position.
You can define your pullback either based an absolute value or based on a percent distance from the MA
+Example:
Pullback value = 100 means I want a 100 pip/USD distance between the MA pullback and the candle
Pullback percent = 2 means I want a 2% distance between the MA pullback and the candle
The percent option is more generic in my opinion but I let the other available for those who might like it
That's it ?
Almost....You can also setup alerts on the indicator signals so that you won't have to stay days in front of the chart to wait for a signal.
You receive the alert, you check real quick if we're not in front of a support/resistance, if no then take the trade. if yes, I advice waiting for a big pullback - better to be safe than sorry in trading
What If you want a custom version ?
Here are a few custom ideas I could add just for you :
re-enter everytime there is a convergence. So far the indicator is only taking the first convergence. This would give more entries
add the resistances/supports (fibo, pivot)
add the take profit targets and trailing stop loss
..
Please hit me up directly so we can discuss further. Any custom dev will require quite some time so it won't be free
Enjoy that one as I really think it will improve your analyst skills and trading and hopefully make you a few gains (which will make me very happy as I want to help most of you to at least not losing your capital)
Dave
Statistical Trend Length Analysis (Quant indicator)This is the only Quantitative type indicator I can find on TradingView (which means it uses automated back testing to determine probability in a mathematical way), although there could be some I just haven't seen them.
This indicator back-tests ALL of the data, calculates the length of all past trends, and does a statistical analysis of trend changes at different levels. The more recent data is more accurate as it learns as the indicator goes along.
These levels can be used in regression to the mean trading, as it gives you an idea of the statistical likeliness of a trend change or pullback occurring in each zone. An average trend length is a very good point to enter when trading a pullback within a trend, although without a complex analysis like this it would be impossible to determine where that is.
PM me for access, and more details on strategies that can be implemented using this indicator.
