Relative Price StrengthThe strength of a stock relative to the S&P 500 is key part of most traders decision making process. Hence the default reference security is SPY, the most commonly trades S&P 500 ETF.
Most profitable traders buy stocks that are showing persistence intermediate strength verses the S&P as this has been shown to work. Hence the default period is 63 days or 3 months.
在腳本中搜尋"美股标普500"
TICK Extremes IndicatorSimple TICK indicator, plots candles and HL2 line
Conditional green/red coloring for highs above 500, 900 and lows above 0, and for lows below -500, -900, and highs above 0
Probably best used for 1 - 5 min timeframes
Always open to suggestions if criteria needs tweaking or if something else would make it more useful or user-friendly!
Market direction and pullback based on S&P 500.A simple indicator based on www.swing-trade-stocks.com The link is also the guide for how to use it.
0 - nothing. If the indicator is showing 0 for a prolonged amount of time, it is likely the market is in "momentum mode" (referred to in the link above).
1 - indicates an uptrend based on SMA and EMA and also a place where a reversal to the upside is likely to occur. You should look only for long trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
-1 - indicates a downtrend based on SMA and EMA and also a place where a reversal to the downside is likely to occur. You should look only for short trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
Net DASH Margin PositionTotal DASH Longs minus DASH Shorts in order to give you the total outstanding DASH margin debt.
ie: If 500,000 DASH has been longed, and 400,000 DASH has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 DASH (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net NEO Margin PositionTotal NEO Longs minus NEO Shorts in order to give you the total outstanding NEO margin debt.
ie: If 500,000 NEO has been longed, and 400,000 NEO has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 NEO (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project.
Like I wrote the last time - my goal is to create a new strategy everyday
for the rest of 2016 and post it here on TradingView.
I'm a complete beginner so this is my way of learning about coding strategies.
I'll give myself between 15 minutes and 2 hours to complete each creation.
This is basically a repetition of the first strategy I wrote - a Moving Average Crossover,
but I added a tiny thing.
I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time."
(source: )
My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility
and because of this missed one nice bull run and a very nice bear run.
So I added this single line: if time("60", "1000-1600") regarding when to take exits:
if time("60", "1000-1600")
strategy.exit("Close Long", "Long", profit=2000, loss=500)
strategy.exit("Close Short", "Short", profit=2000, loss=500)
Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually.
Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility.
When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily.
On the other hand I'll have to test this on various stocks .
Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs
to read on this topic is very welcome!
Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated!
/pbergden
Self-Organized Criticality - Avalanche DistributionHere's all you need to know: This indicator applies Self-Organized Criticality (SOC) theory to financial markets, measuring the power-law exponent (alpha) of price drawdown distributions. It identifies whether markets are in stable Gaussian regimes or critical states where large cascading moves become more probable.
Self-Organized Criticality
SOC theory, introduced by Per Bak, Tang, and Wiesenfeld (1987), describes how complex systems naturally evolve toward critical (fragile) states. An example is a sand pile: adding grains creates avalanches whose sizes follow a power-law distribution rather than a normal distribution.
Financial markets exhibit similar behavior. Price movements aren't purely random walks—they display:
Fat-tailed distributions (more extreme events than Gaussian models predict)
Scale invariance (no characteristic avalanche size)
Intermittent dynamics (periods of calm punctuated by large cascades)
Power-Law Distributions
When a system is in a critical state, the probability of an avalanche of size s follows:
P(s) ∝ s^(-α)
Where:
α (alpha) is the power-law exponent
Higher α → distribution resembles Gaussian (large events rare)
Lower α → heavy tails dominate (large events common)
This indicator estimates α from the empirical distribution of price drawdowns.
Mathematical Method
1. Avalanche Detection
The indicator identifies local price peaks (highest point in a lookback window), then measures the percentage drawdown to the next trough. A dynamic ATR-based threshold filters out noise—small drops in calm markets count, but the bar rises in volatile periods.
2. Logarithmic Binning
Avalanche sizes are sorted into logarithmically-spaced bins (e.g., 1-2%, 2-4%, 4-8%) rather than linear bins. This captures power-law behavior across multiple scales - a 2% drop and 20% crash both matter. The indicator creates 12 adaptive bins spanning from your smallest to largest observed avalanche.
3. Bin-to-Bin Ratio Estimation
For each pair of adjacent bins, we calculate:
α ≈ log(N₁/N₂) / log(s₂/s₁)
Where N₁ and N₂ are avalanche counts, s₁ and s₂ are bin sizes.
Example: If 2% drops happen 4× more often than 4% drops, then α ≈ log(4)/log(2) ≈ 2.0.
We get 8-11 independent estimates and average them. This is more robust than fitting one line through all points—outliers can't dominate.
4. Rolling Window Analysis
Alpha recalculates using only recent avalanches (default: last 500 bars). Old data drops out as new avalanches occur, so the indicator tracks regime shifts in real-time.
Regime Classification
🟢 Gaussian α ≥ 2.8 Normal distribution behavior; large moves are rare outliers
🟡 Transitional 1.8 ≤ α < 2.8 Moderate fat tails; system approaching criticality
🟠 Critical 1.0 ≤ α < 1.8 Heavy tails; large avalanches increasingly common
🔴 Super-Critical α < 1.0 Extreme tail risk; system prone to cascading failures
What Alpha Tells You
Declining alpha → Market moving toward criticality; tail risk increasing
Rising alpha → Market stabilizing; returns to normal distribution
Persistent low alpha → Sustained fragility; heightened crash probability
Supporting Metrics
Heavy Tail %: Concentration of total drawdown in largest 10% of events
Populated Bins: Data coverage quality (11-12 out of 12 is ideal)
Avalanche Count: Sample size for statistical reliability
Limitations
This is a distributional measure, not a timing indicator. Low alpha indicates increased systemic risk but doesn't predict when a cascade will occur. Only that the probability distribution has shifted toward larger events.
How This Differs from the Per Bak Fragility Index
The SOC Avalanche Distribution calculates the power-law exponent (alpha) directly from price drawdown distributions - a pure mathematical analysis requiring only price data. The Per Bak Fragility Index aggregates external stress indicators (VIX, SKEW, credit spreads, put/call ratios) into a weighted composite score.
Technical Notes
Default settings optimized for daily and weekly timeframes on major indices
Requires minimum 200 bars of history for stable estimates
ATR-based dynamic sizing prevents scale-dependent bias
Alerts available for regime transitions and super-critical entry
References
Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of the 1/f noise. Physical Review Letters.
Sornette, D. (2003). Why Stock Markets Crash: Critical Events in Complex Financial Systems. Princeton University Press.
Z-score RegimeThis indicator compares equity behaviour and credit behaviour by converting both into z-scores. It calculates the z-score of SPX and the z-score of a credit proxy based on the HYG divided by LQD ratio.
SPX z-score shows how far the S&P 500 is from its rolling average.
Credit z-score shows how risk-seeking or risk-averse credit markets are by comparing high-yield bonds to investment-grade bonds.
When both z-scores move together, the market is aligned in either risk-on or risk-off conditions.
When SPX z-score is strong but credit z-score is weak, this may signal equity strength that is not supported by credit markets.
When credit z-score is stronger than SPX z-score, credit markets may be leading risk appetite.
The indicator plots the two z-scores as simple lines for clear regime comparison.
50 EMA Rejection Strategy V4 (Correct Signal Logic)//@version=6
indicator("50 EMA Rejection Strategy V4 (Correct Signal Logic)", overlay=true, max_labels_count=500)
//================ INPUTS ================//
group50 = "EMA 50 Trio"
ema50HighLen = input.int(50,"EMA50 High",group=group50)
ema50CloseLen = input.int(50,"EMA50 Close",group=group50)
ema50LowLen = input.int(50,"EMA50 Low",group=group50)
groupBase = "Additional EMAs"
ema10Len = input.int(10,"EMA10")
ema200Len = input.int(200,"EMA200")
ema600Len = input.int(600,"EMA600")
ema2400Len = input.int(2400,"EMA2400")
useTrendFilter = input.bool(false,"Use Higher Time EMA Filter")
groupRR = "Risk Reward Settings"
RR1 = input.float(1.0,"TP1 RR",step=0.5)
RR2 = input.float(2.0,"TP2 RR",step=0.5)
//================ CALCULATIONS ================//
Correlation Scanner📊 CORRELATION SCANNER - Financial Instruments Correlation Analyzer
🎯 ORIGINALITY AND PURPOSE
Correlation Scanner is a professional tool for analyzing correlation relationships between different financial instruments. Unlike standard correlation indicators that show the relationship between only two instruments, this script allows you to simultaneously track the correlation of up to 10 customizable instruments with a selected base asset.
The indicator is designed for traders working with cross-market analysis, portfolio diversification, and searching for related assets for arbitrage strategies.
🔧 HOW IT WORKS
The indicator uses the built-in ta.correlation() function to calculate the Pearson correlation coefficient between instrument closing prices over a specified period. Mathematical foundation:
1. Correlation Calculation: for each instrument, the correlation coefficient with the base asset is calculated over N bars (default 60)
2. Results Sorting: instruments are automatically ranked by absolute correlation value (from strongest to weakest)
3. Visualization: results are displayed in a table with color coding:
- Green: positive correlation (instruments move in the same direction)
- Red: negative correlation (instruments move in opposite directions)
- Color intensity depends on correlation strength
4. Correlation Strength Classification:
- Very Strong (💪💪💪): |r| > 0.8 — very strong relationship
- Strong (💪💪): |r| > 0.6 — strong relationship
- Medium (💪): |r| > 0.4 — medium relationship
- Weak: |r| > 0.2 — weak relationship
- Very Weak: |r| ≤ 0.2 — very weak relationship
📋 SETTINGS AND USAGE
MAIN PARAMETERS:
• Main Instrument — base instrument for comparison (default TVC:DXY - US Dollar Index)
• Correlation Period — calculation period in bars (10-500, default 60)
• Number of Instruments to Display — number of instruments to show (1-10)
• Table Position — table location on the chart
INSTRUMENT CONFIGURATION:
The indicator allows configuring up to 10 instruments for analysis. For each, you can specify:
• Instrument — instrument ticker (e.g., FX_IDC:EURUSD)
• Name — display name (emojis supported)
VISUAL SETTINGS:
• Show Chart Label with Correlation — display current chart's correlation with base instrument
• Table Header Color — table header color
• Table Row Background — table row background color
💡 USAGE EXAMPLES
1. DOLLAR IMPACT ANALYSIS: set DXY as the base instrument and track how dollar index changes affect currency pairs, gold, and cryptocurrencies
2. HEDGING ASSETS SEARCH: find instruments with strong negative correlation for risk diversification
3. PAIRS TRADING: identify assets with high positive correlation to find divergences and arbitrage opportunities
4. CROSS-MARKET ANALYSIS: track relationships between stocks, bonds, commodities, and currencies
5. SYSTEMIC RISK ASSESSMENT: identify periods of increased correlation between assets, which may indicate systemic risks
⚠️ IMPORTANT NOTES
• Correlation does NOT imply causation
• Correlation can change over time — regularly review the analysis period
• High past correlation doesn't guarantee the relationship will persist in the future
• Recommended to use the indicator in combination with fundamental analysis
🔔 ALERTS
The indicator includes a built-in alert condition: triggers when strong correlation (|r| > 0.8) is detected between the current chart and the base instrument.
2 MACD VISUEL — 4H / 1H / 15M + CONFIRMATION 5M//@version=6
indicator("MTF MACD VISUEL — 4H / 1H / 15M + CONFIRMATION 5M", overlay=true, max_labels_count=500)
// ─────────────────────────────
// Fonction MACD Histogram
// ─────────────────────────────
f_macd(src) =>
fast = ta.ema(src, 12)
slow = ta.ema(src, 26)
macd = fast - slow
signal = ta.ema(macd, 9)
hist = macd - signal
hist
// ─────────────────────────────
// MTF MACD HISTOGRAM
// ─────────────────────────────
h4 = request.security(syminfo.tickerid, "240", f_macd(close))
h1 = request.security(syminfo.tickerid, "60", f_macd(close))
h15 = request.security(syminfo.tickerid, "15", f_macd(close))
h5 = request.security(syminfo.tickerid, "5", f_macd(close))
// Signes
s4 = h4 > 0 ? 1 : h4 < 0 ? -1 : 0
s1 = h1 > 0 ? 1 : h1 < 0 ? -1 : 0
s15 = h15 > 0 ? 1 : h15 < 0 ? -1 : 0
s5 = h5 > 0 ? 1 : h5 < 0 ? -1 : 0
// Conditions
three_same = (s4 == s1) and (s1 == s15) and (s4 != 0)
five_same = three_same and (s5 == s4)
// BUY / SELL logiques
isBUY = five_same and s4 == 1
isSELL = five_same and s4 == -1
// ─────────────────────────────
// DASHBOARD VISUEL (en haut du graphique)
// ─────────────────────────────
var table dash = table.new(position.top_right, 4, 2, border_color=color.black)
table.cell(dash, 0, 0, "4H", bgcolor = s4 == 1 ? color.green : s4 == -1 ? color.red : color.gray)
table.cell(dash, 1, 0, "1H", bgcolor = s1 == 1 ? color.green : s1 == -1 ? color.red : color.gray)
table.cell(dash, 2, 0, "15M", bgcolor = s15 == 1 ? color.green : s15 == -1 ? color.red : color.gray)
table.cell(dash, 3, 0, "5M", bgcolor = s5 == 1 ? color.green : s5 == -1 ? color.red : color.gray)
table.cell(dash, 0, 1, s4 == 1 ? "↑" : s4 == -1 ? "↓" : "·", bgcolor=color.new(color.black, 0), text_color=color.white)
table.cell(dash, 1, 1, s1 == 1 ? "↑" : s1 == -1 ? "↓" : "·", bgcolor=color.new(color.black, 0), text_color=color.white)
table.cell(dash, 2, 1, s15 == 1 ? "↑" : s15 == -1 ? "↓" : "·", bgcolor=color.new(color.black, 0), text_color=color.white)
table.cell(dash, 3, 1, s5 == 1 ? "↑" : s5 == -1 ? "↓" : "·", bgcolor=color.new(color.black, 0), text_color=color.white)
// ─────────────────────────────
// SIGNES VISUELS SUR LE GRAPHIQUE
// ─────────────────────────────
plotshape(isBUY, title="BUY", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.large, text="BUY")
plotshape(isSELL, title="SELL", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.large, text="SELL")
// Histogramme du MACD 5M en couleur tendance
plot(h5, title="MACD Hist 5M", color = h5 >= 0 ? color.green : color.red, style=plot.style_columns)
// ─────────────────────────────
// Alerte Webhook (message constant OBLIGATOIRE)
// ─────────────────────────────
alertcondition(isBUY, title="Signal BUY Confirmé", message="MTF_MACD_BUY")
alertcondition(isSELL, title="Signal SELL Confirmé", message="MTF_MACD_SELL")
S&P Options Patterns Detector (6-20 Candles)Pattern detector for S&P options. Detects alerts for bullish or bearish signals for any stock in S&P 500
Global M2(USD) V2This indicator tracks the total Global M2 Money Supply in USD. It aggregates economic data from the world's four largest central banks (Fed, PBOC, ECB, BOJ). The script automatically converts non-USD money supplies (CNY, EUR, JPY) into USD using real-time exchange rates to provide a unified view of global liquidity.
Usage
Macro Analysis: Overlay this on assets like Bitcoin or the S&P 500 to see if price appreciation is driven by fiat currency debasement ("money printing").
Liquidity Trends: A rising orange line indicates expanding global liquidity (generally bullish for risk assets), while a falling line suggests monetary tightening.
Real-time Data: A label at the end of the line displays the exact raw total in USD for precise tracking.
该脚本旨在追踪以美元计价的全球 M2 货币供应总量。它聚合了四大央行（美联储、中国央行、欧洲央行、日本央行）的经济数据，并通过实时汇率将非美货币（人民币、欧元、日元）统一折算为美元，从而构建出一个标准化的全球流动性指标。
用法
宏观对冲： 将其叠加在比特币或股票图表上，用于判断资产价格的上涨是否由全球法币“大放水”推动。
趋势研判： 橙色曲线向上代表全球流动性扩张（通常利好风险资产），向下则代表流动性紧缩。
数据直观： 脚本会在图表末端生成一个标签，实时显示当前全球 M2 的具体美元总额。
STRAT - MTF Dashboard + FTFC + Reversals v2.7# STRAT Indicator - Complete Description
## Overview
A comprehensive multi-timeframe STRAT trading system indicator that combines market structure analysis, flip levels, Full Timeframe Continuity (FTFC), and reversal pattern detection across 12 timeframes.
## Core Features
### 1. **Multi-Timeframe STRAT Dashboard**
- Displays STRAT combos (1, 2u, 2d, 3) across 12 timeframes: 1m, 5m, 15m, 30m, 1H, 4H, 12H, Daily, Weekly, Monthly, Quarterly, Yearly
- Color-coded directional bias (green/red/doji)
- Inside bars (●) and Outside bars (●) highlighted
- Current timeframe marked with ★
### 2. **HTF Flip Levels with Smart Grouping**
- Displays higher timeframe (HTF) flip levels (open prices) as labels on the right side
- Automatically groups multiple timeframes at the same price level (e.g., "★ 1H/4H/D")
- Current timeframe flip level always displayed with ★ marker
- Color-coded: Green (above price) / Red (below price)
### 3. **Full Timeframe Continuity (FTFC)**
- User-selectable 4 timeframes for FTFC analysis (default: D, W, M, Q)
- Green line: FTFC Up (highest open of 4 timeframes)
- Red line: FTFC Down (lowest open of 4 timeframes)
- Identifies when price is above/below all 4 timeframe opens
### 4. **Hammer & Shooting Star Detection**
- **Hammer Pattern**: Long lower wick (≥2x body), small upper wick, signals potential bottom reversal
- **Shooting Star Pattern**: Long upper wick (≥2x body), small lower wick, signals potential top reversal
- Scans last 100 bars (adjustable) and marks ALL historical patterns
- Chart markers: 🔨 (Hammer) below bars, 🔻 (Shooting Star) above bars
- Dashboard column shows reversal patterns for each timeframe
- Adjustable wick-to-body ratio sensitivity (1.5 to 5.0)
### 5. **Debug Tables**
- **FTFC Debug**: Shows close vs. 4 timeframe opens, confirms all-green/all-red conditions
- **Reversal Debug**: Real-time analysis of current bar - body size, wick measurements, ratios, and pattern qualification
## Settings
### Display Settings
- Dashboard position (9 options: top-left to bottom-right)
- Dashboard text size (tiny to huge)
- Label offset and text size
- Toggle individual features on/off
### FTFC Settings
- Select 4 custom timeframes for continuity analysis
- Default: Daily, Weekly, Monthly, Quarterly
### Reversal Settings
- **Wick to Body Ratio**: Sensitivity for pattern detection (default 2.0)
- **Lookback Bars**: How many historical bars to scan (default 100, max 500)
- Show/hide reversal markers on chart
- Show/hide reversal debug table
## Use Cases
1. **Momentum Trading**: Identify STRAT setups (2-2, 2-1-2 reversals, 3-bar plays) across multiple timeframes
2. **Swing Trading**: Use HTF flip levels as support/resistance and FTFC for trend confirmation
3. **Reversal Trading**: Catch hammer/shooting star patterns at key levels for counter-trend entries
4. **Multi-Timeframe Analysis**: Confirm alignment across timeframes before entering trades
## How to Use
### For STRAT Traders
- Look for 2-1-2 reversal setups in the dashboard
- Watch for inside bars (●) at HTF flip levels for breakout trades
- Use outside bars (●) to identify potential volatility expansion
### For Reversal Traders
- 🔨 Hammers after downtrends = potential long entries
- 🔻 Shooting stars after uptrends = potential short entries
- Combine with HTF flip levels for high-probability setups
### For Trend Followers
- FTFC green line above = bullish structure
- FTFC red line below = bearish structure
- Enter when price breaks and holds above/below FTFC levels
## Visual Elements
- **Green Labels**: HTF flip levels above current price (resistance)
- **Red Labels**: HTF flip levels below current price (support)
- **Lime Line**: FTFC Up (highest timeframe open)
- **Red Line**: FTFC Down (lowest timeframe open)
- **🔨 Icon**: Hammer pattern (potential reversal up)
- **🔻 Icon**: Shooting Star pattern (potential reversal down)
- **★ Symbol**: Current timeframe or multiple timeframes grouped
## Performance Notes
This indicator performs 12 multi-timeframe security calls and may take 15-30 seconds to calculate on initial load. This is normal for comprehensive MTF analysis.
## Version
v2.7 - Simplified reversal detection, current TF labeling, optimized performance
---
**Perfect for**: STRAT traders, multi-timeframe analysts, reversal pattern traders, swing traders looking for high-probability setups with confluence across timeframes.
Buffett Quality Filter (TTM)//@version=6
indicator("Buffett Quality Filter (TTM)", overlay = true, max_labels_count = 500)
// 1. Get financial data (TTM / FY / FQ)
// EPS (TTM) for P/E
eps = request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE_BASIC", "TTM")
// Profitability & moat (annual stats)
roe = request.financial(syminfo.tickerid, "RETURN_ON_EQUITY", "FY")
roic = request.financial(syminfo.tickerid, "RETURN_ON_INVESTED_CAPITAL", "FY")
// Margins (TTM – rolling 12 months)
grossMargin = request.financial(syminfo.tickerid, "GROSS_MARGIN", "TTM")
netMargin = request.financial(syminfo.tickerid, "NET_MARGIN", "TTM")
// Balance sheet safety (quarterly)
deRatio = request.financial(syminfo.tickerid, "DEBT_TO_EQUITY", "FQ")
currentRat = request.financial(syminfo.tickerid, "CURRENT_RATIO", "FQ")
// Growth (1-year change, TTM)
epsGrowth1Y = request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE_BASIC_ONE_YEAR_GROWTH", "TTM")
revGrowth1Y = request.financial(syminfo.tickerid, "REVENUE_ONE_YEAR_GROWTH", "TTM")
// Free cash flow (TTM) and shares to build FCF per share for P/FCF
fcf = request.financial(syminfo.tickerid, "FREE_CASH_FLOW", "TTM")
sharesOut = request.financial(syminfo.tickerid, "TOTAL_SHARES_OUTSTANDING", "FQ")
fcfPerShare = (not na(fcf) and not na(sharesOut) and sharesOut != 0) ? fcf / sharesOut : na
// 2. Valuation ratios from price
pe = (not na(eps) and eps != 0) ? close / eps : na
pFcf = (not na(fcfPerShare) and fcfPerShare > 0) ? close / fcfPerShare : na
// 3. Thresholds (Buffett-style, adjustable)
minROE = input.float(15.0, "Min ROE %")
minROIC = input.float(12.0, "Min ROIC %")
minGM = input.float(30.0, "Min Gross Margin %")
minNM = input.float(8.0, "Min Net Margin %")
maxDE = input.float(0.7, "Max Debt / Equity")
minCurr = input.float(1.3, "Min Current Ratio")
minEPSG = input.float(8.0, "Min EPS Growth 1Y %")
minREVG = input.float(5.0, "Min Revenue Growth 1Y %")
maxPE = input.float(20.0, "Max P/E")
maxPFCF = input.float(20.0, "Max P/FCF")
// 4. Individual conditions
cROE = not na(roe) and roe > minROE
cROIC = not na(roic) and roic > minROIC
cGM = not na(grossMargin) and grossMargin > minGM
cNM = not na(netMargin) and netMargin > minNM
cDE = not na(deRatio) and deRatio < maxDE
cCurr = not na(currentRat) and currentRat > minCurr
cEPSG = not na(epsGrowth1Y) and epsGrowth1Y > minEPSG
cREVG = not na(revGrowth1Y) and revGrowth1Y > minREVG
cPE = not na(pe) and pe < maxPE
cPFCF = not na(pFcf) and pFcf < maxPFCF
// 5. Composite “Buffett Score” (0–10) – keep it on ONE line to avoid line-continuation errors
score = (cROE ? 1 : 0) + (cROIC ? 1 : 0) + (cGM ? 1 : 0) + (cNM ? 1 : 0) + (cDE ? 1 : 0) + (cCurr ? 1 : 0) + (cEPSG ? 1 : 0) + (cREVG ? 1 : 0) + (cPE ? 1 : 0) + (cPFCF ? 1 : 0)
// Strictness
minScoreForPass = input.int(7, "Min score to pass (0–10)", minval = 1, maxval = 10)
passes = score >= minScoreForPass
// 6. Visuals
bgcolor(passes ? color.new(color.green, 80) : na)
plot(score, "Buffett Score (0–10)", color = color.new(color.blue, 0))
// Info label on last bar
var label infoLabel = na
if barstate.islast
if not na(infoLabel)
label.delete(infoLabel)
infoText = str.format(
"Buffett score: {0}\nROE: {1,number,#.0}% | ROIC: {2,number,#.0}%\nGM: {3,number,#.0}% | NM: {4,number,#.0}%\nP/E: {5,number,#.0} | P/FCF: {6,number,#.0}\nD/E: {7,number,#.00} | Curr: {8,number,#.00}",
score, roe, roic, grossMargin, netMargin, pe, pFcf, deRatio, currentRat)
infoLabel := label.new(bar_index, high, infoText,
style = label.style_label_right,
color = color.new(color.black, 0),
textcolor = color.white,
size = size.small)
VB-MainLiteVB-MainLite – v1.0 Initial Release
Overview
VB-MainLite is a consolidated market-structure and execution framework designed to streamline decision-making into a single chart-level view. The script combines multi-timeframe trend, volatility, volume, and liquidity signals into one cohesive visual layer, reducing indicator clutter while preserving depth of information for active traders.
Core Architecture
Trend Backbone – EMA 200
Dedicated EMA 200 acts as the primary trend filter and higher-timeframe bias reference.
Serves as the “spine” of the system for contextualizing all secondary signals (swings, reversals, volume events, etc.).
Custom MA Suite (Envelope Ready)
Four configurable moving averages with flexible source, length, and smoothing.
Default configuration (preset idea: “8/89 Envelope”):
MA #1: EMA 8 on high
MA #2: EMA 8 on low
MA #3: EMA 89 on high
MA #4: EMA 89 on low
All four are disabled by default to keep the chart minimal. Users can toggle them on from the Custom MAs group for envelope or cloud-style configurations.
Nadaraya–Watson Smoother (Swing Framework)
Gaussian-kernel Nadaraya–Watson regression applied to price (hl2) to build a smooth synthetic curve.
Two layers of functionality:
Swing labels (▲ / ▼) at inflection points in the smoothed curve.
Optional curve line that visually tracks the turning structure over the last ~500 bars.
Designed to surface early swing potential before standard MAs react.
Hull Moving Average (Trend Overlay)
Optional Hull MA (HMA) for faster trend visualization.
Color-coded by slope (buy/sell bias).
Default: off to prevent overloading the chart; can be enabled under Hull MA settings.
Momentum, Exhaustion & Pattern Engine
CCI-Based Bar Coloring
CCI applied to close with configurable thresholds.
Overbought / oversold CCI zones map directly into candle coloring to visually highlight short-term momentum extremes.
RSI Top / Bottom Exhaustion Finder
RSI logic applied separately to high-driven (tops) and low-driven (bottoms) sequences.
Plots:
Top arrows where high-side RSI stretches into high-risk territory.
Bottom arrows where low-side RSI indicates exhaustion on the downside.
Useful as confluence around the Nadaraya swing turns and EMA 200 regime.
Engulfing + MA Trend Engine (“Fat Bull / Fat Bear”)
Detects bullish and bearish engulfing patterns, then combines them with MA trend cross logic.
Only when both pattern and MA regime align does the engine flag:
Fat Bull (Engulf + MA aligned long)
Fat Bear (Engulf + MA aligned short)
Candles are marked via conditional barcolor to highlight strong, structured shifts in control.
Fat Finger Detection (Wick Spikes / Stop Runs)
Identifies abnormal wick extensions relative to the prior bar’s body range with configurable tolerance.
Supports detection of potential liquidity grabs, stop runs, or “excess” that may precede reversals or mean-reversion behavior.
Volume & Liquidity Intelligence
Bull Snort (Aggressive Buy Spikes)
Flags events where:
Volume is significantly above the 50-period average, and
Price closes in the upper portion of the bar and above prior close.
Plots a labeled marker below the bar to indicate aggressive upside initiative by buyers.
Pocket Pivots (Accumulation Flags)
Compares current volume vs prior 10 sessions with a filter on prior “up” days.
Highlights pocket pivot days where current green candle volume outclasses recent down-day volumes, suggesting stealth accumulation.
Delta Volume Core (Directional Volume by Price)
Internal volume-by-price style engine over a user-defined lookback.
Splits volume into up-close and down-close buckets across dynamic price bins.
Feeds into S&R and ICT zone logic to quantify where buying vs selling pressure built up.
Structural Context: S&R and ICT Zones
S&R Power Channel
Computes local high/low band over a configurable lookback window.
Renders:
Upper and lower S&R channel lines.
Shaded support / resistance zones using boxes.
Adds Buy Power / Sell Power metrics based on the ratio of up vs down bars inside the window, displayed directly in the zone overlays.
Drops ◈ markers where price interacts dynamically with the top or bottom band, highlighting reaction points.
ICT-Style Premium / Discount & Macro Zones
Two tiered structures:
Local Premium / Discount zones over a shorter SR window.
Macro Premium / Discount zones over a longer macro window.
Each zone:
Uses underlying directional volume to annotate accumulation vs distribution bias.
Provides Delta Volume Bias shading in the mid-band region, visually encoding whether local power flows are net-buying or net-selling.
Enables traders to quickly see whether current trade location is in a local/macro discount or premium context while still respecting volume profile.
Positioning Intelligence: PCD (Stocks)
Position Cost Distribution (PCD) – Stocks Only
Available for stock symbols on intraday up to daily timeframe (≤ 1D).
Uses:
TOTAL_SHARES_OUTSTANDING fundamentals,
Daily OHLCV snapshot, and
A bucketed distribution engine
to approximate cost basis distribution across price.
Outputs:
Horizontal “PCD bars” to the right of current price, density-scaled by estimated share concentration.
Color-coding by profitability relative to current price (profitable vs unprofitable positions).
Labels for:
Current price
Average cost
Profit ratio (share % below current price)
90% cost range
70% cost range
Range overlap as a measure of clustering / concentration.
Multi-Timeframe Trend: Two-Pole Gaussian Dashboard
Two-Pole Gaussian Filter (Line + Cloud)
Smooths a user-selected source (default: close) using a two-pole Gaussian filter with tunable alpha.
Plots:
A thin Gaussian trend line, and
A thick Gaussian “cloud” line with transparency, colored by slope vs past (offsetG).
Functions as a responsive trend backbone that is more sensitive than EMA 200 but less noisy than raw price.
Multi-Timeframe Gaussian Dashboard
Evaluates Gaussian trend direction across up to six timeframes (e.g., 1H / 2H / 4H / Daily / Weekly).
Renders a compact bottom-right table:
Header: symbol + overall bias arrow (up / down) based on average trend alignment.
Row of colored cells per timeframe (green for uptrend, magenta for downtrend) with human-readable TF labels (e.g., “60M”, “4H”, “1D”).
Gives an immediate read on whether intraday, swing, and higher-timeframe flows are aligned or fragmented.
Default Configuration & Usage Guidance
Default state after adding the script:
Enabled by default:
EMA 200 trend backbone
Nadaraya–Watson swing labels and curve
CCI bar coloring
RSI top/bottom arrows
Fat Bull / Fat Bear engine
Bull Snort & Pocket Pivots
S&R Power Channel
ICT Local + Macro zones
Two-pole Gaussian line + cloud + dashboard
PCD engine for stocks (auto-active where data is available)
Disabled by default (opt-in):
Custom MA suite (4x MAs, preset as EMA 8/8/89/89)
Hull MA overlay
How traders can use VB-MainLite in practice:
Use EMA 200 + Gaussian dashboard to define top-down directional bias and avoid trading directly against multi-TF trend.
Use Nadaraya swing labels, RSI exhaustion arrows, and CCI bar colors to time entries within that higher-timeframe bias.
Use Fat Bull / Fat Bear events as structured confirmation that both pattern and MA regime have flipped in the same direction.
Use Bull Snort, Pocket Pivots, and S&R / ICT zones to align execution with liquidity, volume, and location (premium vs discount).
On stocks, use PCD as a positioning map to understand trapped supply, support zones near crowded cost basis, and where profit-taking is likely.
MTF RSI Stacked + AI + Gradient MTF RSI Stacked + AI + Gradient
Quick-start guide & best-practice rules
What the indicator does
Multi-Time-Frame RSI in one pane
• 10 time-frames (1 m → 1 M) are stacked 100 points apart (0, 100, 200 … 900).
• Each RSI is plotted with a smooth red-yellow-green gradient:
– Red = RSI below 30 (oversold)
– Yellow = RSI near 50
– Green = RSI above 70 (overbought)
• Grey 30-70 bands are drawn for every TF so you can see extremities at a glance.
Built-in AI (KNN) signal
• On every close of the chosen AI-time-frame the script:
– Takes the last 14-period RSI + normalised ATR as “features”
– Compares them to the last N bars (default 1 000)
– Votes of the k = 5 closest neighbours → BUY / SELL / NEUTRAL
• Confidence % is shown in the badge (top-right).
• A thick vertical line (green/red) is printed once when the signal flips.
How to read it
• Gradient colour tells you instantly which TFs are overbought/obove sold.
• When all or most gradients are green → broad momentum up; look for shorts only on lower-TF pullbacks.
• When most are red → broad momentum down; favour longs only on lower-TF bounces.
• Use the AI signal as a confluence filter, not a stand-alone entry:
– If AI = BUY and 3+ higher-TF RSIs just crossed > 50 → consider long.
– If AI = SELL and 3+ higher-TF RSIs just crossed < 50 → consider short.
• Divergences: price makes a higher high but 1 h/4 h RSI (gradient) makes a lower high → possible reversal.
Settings you can tweak
AI timeframe – leave empty = same as chart, or pick a higher TF (e.g. “15” or “60”) to slow the signal down.
Training bars – 500-2 000 is the sweet spot; bigger = slower but more stable.
K neighbours – 3-7; lower = more signals, higher = smoother.
RSI length – 14 is standard; 9 gives earlier turns, 21 gives fewer false swings.
Practical trading workflow
Open the symbol on your execution TF (e.g. 5 m).
Set AI timeframe to 3-5× execution TF (e.g. 15 m or 30 m) so the signal survives market noise.
Wait for AI signal to align with gradient extremes on at least one higher TF.
Enter on the first gradient reversal inside the 30-70 band on the execution TF.
Place stop beyond the swing that caused the gradient flip; target next opposing 70/30 level on the same TF or trail with structure.
Colour cheat-sheet
Bright green → RSI ≥ 70 (overbought)
Bright red → RSI ≤ 30 (oversold)
Muted colours → RSI near 50 (neutral, momentum pause)
That’s it—one pane, ten time-frames, colour-coded extremes and an AI confluence layer.
Keep the chart clean, use price action for precise entries, and let the gradient tell you when the wind is at your back.
Séparateur H4 & DailyH4 & Daily Separator - TradingView Indicator
This Pine Script v6 indicator draws infinite vertical lines to mark H4 and Daily candle separations on your chart.
Features:
H4 Separations: Marks candles starting at 3am, 7am, 11am, 3pm, 7pm, and 11pm
Daily Separations: Marks candles starting at midnight (00:00)
Fully Customizable:
Toggle H4 and/or Daily lines independently
Choose line color, thickness (1-4), and style (Solid, Dotted, Dashed)
Control the number of visible vertical lines (1-500)
Use Case:
Perfect for traders who want to visualize higher timeframe separations while trading on lower timeframes. Helps identify H4 and Daily candle opens without switching charts.
Installation:
Simply copy the code into TradingView's Pine Editor and add it to your chart. All settings are adjustable in the indicator's settings panel.
Goal Setting Strategies Viprasol# 🎯 Goal Setting Strategies Viprasol
A powerful goal tracking tool designed for disciplined traders who want to monitor their trading objectives, milestones, and progress directly on their charts.
## ✨ KEY FEATURES
### 📊 Flexible Goal Management
- Track anywhere from 1 to 20 trading goals simultaneously
- Adjustable goal count via simple input slider
- Each goal has its own unique emoji identifier
- Real-time progress counter
### ✅ Visual Tracking System
- Interactive checkbox system for goal completion
- Clear visual indicators (✅ completed, ⬜️ pending)
- Customizable goal names and descriptions
- Dynamic progress display
### 🎨 Full Customization
- **4 Position Options**: Top Left, Top Right, Bottom Left, Bottom Right
- **5 Font Sizes**: Tiny, Small, Normal, Large, Huge (optimized for all screen sizes)
- **Custom Colors**: Header, labels, background, achievement text
- **Premium Styling**: Modern cyber-themed design with professional appearance
### 💡 Perfect For:
- Daily/Weekly trading goal tracking
- Risk management milestones
- Profit target monitoring
- Trading plan compliance
- Personal development objectives
- Learning milestones
## 🔧 HOW TO USE
1. **Set Your Primary Goal**: Enter your main objective in "Primary Goal" field
2. **Choose Goal Count**: Select how many goals you want (1-20)
3. **Name Your Goals**: Customize each goal name in the "Goal Definitions" section
4. **Track Progress**: Check off goals as you complete them
5. **Customize Display**: Adjust colors, sizes, and position to match your chart setup
## 📐 INPUT GROUPS
### 🎯 Viprasol Goal Configuration
- Primary Goal Name
- Number of Goals (1-20)
### 📋 Goal Definitions
- All 20 goals with individual names and checkboxes
- Only enabled goals (based on count) will display
### 🌈 Premium Styling
- Goal Header Color
- Label Color
- Panel Background Color
- Achievement Color
- Header Font Size
- Milestone Font Size (Tiny/Small optimized for space)
### 📍 Elite Display
- Dashboard Position selector
## 💎 UNIQUE FEATURES
- **Space Efficient**: Tiny and Small font options for compact displays
- **Scalable**: Grow from 1 goal to 20 as your needs evolve
- **Non-Intrusive**: Overlay indicator that doesn't interfere with price action
- **Professional Design**: Clean, modern interface with cyber aesthetic
## 🎓 USE CASES
**Day Traders**: Track daily profit targets, trade count limits, max loss thresholds
**Swing Traders**: Monitor weekly/monthly goals, position management rules
**New Traders**: Learning milestones, strategy development checkpoints
**Experienced Traders**: Advanced risk management, portfolio objectives
## ⚙️ TECHNICAL DETAILS
- Version: Pine Script v5
- Type: Overlay Indicator
- Max Labels: 500
- Table-based display system
- No repainting
- Lightweight performance
## 🚀 GETTING STARTED
1. Add indicator to your chart
2. Set "Number of Goals" to your desired count (start small, scale up)
3. Customize goal names
4. Check boxes as you achieve goals
5. Watch your progress build!
## 📊 DISPLAY OPTIMIZATION
- Use "Tiny" or "Small" for maximum goals on small screens
- Use "Normal" or "Large" for standard monitors
- Use "Huge" for presentation or large displays
- Adjust position to avoid chart overlap
## 🎯 TRADING DISCIPLINE
This tool helps reinforce:
- Goal-oriented trading mindset
- Progress tracking accountability
- Milestone celebration
- Structured approach to trading development
---
**© viprasol**
*Designed for traders who take their goals seriously.*
S&P 500 Scalper Pro [Trend + MACD] 5 minfor scalping 5 min S&P on 5 min chart put SL on 20 min ma and take 2:1 risk
Average True Range (ATR)Strategy Name: ATR Trend-Following System with Volatility Filter & Dynamic Risk Management
Short Name: ATR Pro Trend System
Current Version: 2025 Edition (fully tested and optimized)Core ConceptA clean, robust, and highly profitable trend-following strategy that only trades when three strict conditions are met simultaneously:Clear trend direction (price above/below EMA 50)
Confirmed trend strength and trailing stop (SuperTrend)
Sufficient market volatility (current ATR(14) > its 50-period average)
This combination ensures the strategy stays out of choppy, low-volatility ranges and only enters during high-probability, trending moves with real momentum.Key Features & ComponentsComponent
Function
Default Settings
EMA 50
Primary trend filter
50-period exponential
SuperTrend
Dynamic trailing stop + secondary trend confirmation
Period 10, Multiplier 3.0
ATR(14) with RMA
True volatility measurement (Wilder’s original method)
Length 14
50-period SMA of ATR
Volatility filter – only trade when current ATR > average ATR
Length 50
Background coloring
Visual position status: light green = long, light red = short, white = flat
–
Entry markers
Green/red triangles at the exact entry bar
–
Dynamic position sizing
Fixed-fractional risk: exactly 1% of equity per trade
1.00% risk
Stop distance
2.5 × ATR(14) – fully adaptive to current volatility
Multiplier 2.5
Entry RulesLong: Close > EMA 50 AND SuperTrend bullish AND ATR(14) > SMA(ATR,50)
Short: Close < EMA 50 AND SuperTrend bearish AND ATR(14) > SMA(ATR,50)
Exit RulesPosition is closed automatically when SuperTrend flips direction (acts as volatility-adjusted trailing stop).
Money ManagementRisk per trade: exactly 1% of current account equity
Position size is recalculated on every new entry based on current ATR
Automatically scales up in strong trends, scales down in low-volatility regimes
Performance Highlights (2015–Nov 2025, real backtests)CAGR: 22–50% depending on market
Max Drawdown: 18–28%
Profit Factor: 1.89–2.44
Win Rate: 57–62%
Average holding time: 10–25 days (daily timeframe)
Best Markets & TimeframesExcellent on: Bitcoin, S&P 500, Nasdaq-100, DAX, Gold, major Forex pairs
Recommended timeframes: 4H, Daily, Weekly (Daily is the sweet spot)
NQUSB Sector Industry Stocks Strength
A Comprehensive Multi-Industry Performance Comparison Tool
The complete Pine Script code and supporting Python automation scripts are available on GitHub:
GitHub Repository: github.com
Original idea from by www.tradingview.com
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ WHAT'S NEW ═══
4-Level Hierarchical Navigation:
Primary: All 11 NQUSB sectors (NQUSB10, NQUSB15, NQUSB20, etc.)
Secondary (Default): Broad sectors like Technology, Energy
Tertiary: Industry groups within sectors
Quaternary: Individual stocks within industries (37 semiconductors)
Enhanced Stock Coverage:
1,176 total stocks across 129 industries
37 semiconductor stocks
Market-cap weighted selection: 60% tech / 35% others
Range: 1-37 stocks per industry
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ CORE FEATURES ═══
1. Drill-Down/Drill-Up Navigation
View NVDA at different granularity levels:
Quaternary: ● NVDA ranks #3 of 37 semiconductors
Tertiary: ✓ Semiconductors at 85% (strongest in tech hardware)
Secondary: ✓ Tech Hardware at 82% (stronger than software)
Primary: ✓ Technology at 78% (#1 sector overall)
Insight: One indicator, one stock, four perspectives - instantly see if strength is stock-specific, industry-specific, or sector-wide.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
2. Visual Current Stock Identification
Violet Markers - Instant Recognition:
● (dot) marker when current stock is in top N performers
✕ (cross) marker when current stock is below top N
Violet color (#9C27B0) on both symbol and value labels
Example: "NVDA ● ranks #3 of 37"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3. Rank Display in Title
Dynamic title shows performance context:
"Semiconductors (RS Rating - 3 Months) | NVDA ranks #3 of 37"
#1 = Best performer, higher number = lower rank
Total adjusts if current stock auto-added
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
4. Auto-Add Current Stock
Always Included:
Current stock automatically added if not in predefined list
Example: Viewing PRSO → "PRSO ranks #37 of 39 ✕"
Works for any stock - from NVDA to obscure small-caps
Violet markers ensure visibility even when ranked low
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ DUAL PERFORMANCE METRICS ═══
RS Rating (Relative Strength):
Normalized strength score 1-99
Compare stocks across different price ranges
Default benchmark: SPX
% Return:
Simple percentage price change
Direct performance comparison
11 Time Periods:
1 Week, 2 Weeks, 1 Month, 2 Months, 3 Months (Default) , 6 Months, 1 Year, YTD, MTD, QTD, Custom (1-500 days)
Result: 22 analytical combinations (2 metrics × 11 periods)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ USE CASES ═══
Sector Rotation Analysis:
Is NVDA's strength semiconductors-specific or tech-wide?
Drill through all 4 levels to find answer
Identify which industry groups are leading/lagging
Finding Hidden Gems:
JPM ranks #3 of 13 in Major Banks
But Financials sector weak overall (68%)
= Relative strength play in weak sector
Cross-Industry Comparison:
129 industries covered
Market-wide scan capability
Find strongest performers across all sectors
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ TECHNICAL SPECIFICATIONS ═══
V32 Stats:
Total Industries: 129
Total Stocks: 1,176
File Size: 82,032 bytes (80.1 KB)
Request Limit: 39 max (Semiconductors), 10-16 typical
Granularity Levels: 4 (Primary → Quaternary)
Smart Stock Allocation:
Technology industries: 60% coverage
Other industries: 35% coverage
Market-cap weighted selection
Formula: MIN(39, MAX(5, CEILING(total × percentage)))
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ KEY ADVANTAGES ═══
vs. Single Industry Tools:
✓ 129 industries vs 1
✓ Market-wide perspective
✓ Hierarchical navigation
✓ Sector rotation detection
vs. Manual Comparison:
✓ No ETF research needed
✓ Instant visual markers
✓ Automatic ranking
✓ One-click drill-down
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
For complete documentation, Python automation scripts, and CSV data files:
github.com
Version: V32
Last Updated: 2025-11-30
Pine Script Version: v5
