Modified RSI Multi-Time Frame (HM)Effective RSI with Multi-Timeframe with Hilema - Milega(HM) concept (HM=WMA -EMA). RSI Script is included with WMA and EMA band for RSI1 and it works very simple
i) When the RSI band turns to Green its a Buy signal. Normally whenever Bearish strength weakens and move towards the Bullish area, the WMA and EMA cross each other and that tends to provide a possible trend change. A trade at crossover normally provides a very good trading oppertunity. One can combine with some other Price action if needed for double confirmation.
ii)When RSI band turns to RED its a Sell signal. As explained in the point 1 , its a vice-versa where a crossover of WMA and EMA is perfect entry to get a good swing trade. Once can combine this tool with Price action for double confirmation.
iii) Using the Multi timeframe user could able to find the trend at higher timeframe to take double confirm on the trend strength and take a perfect oppertunity to take the trade.
By default, script uses the RSI with length 14, WMA 21 and EMA 3 which perfectly working for Index in NSE. Please change as per your requirement.
Apart from the above band, RSI is not have the different levels like 20/ 40 /50/60/80
Multi-timeframes currently set as
RSI1 - Same as Chart
RSI2 - 15 Min
RSI3 - 60 Min
RSI4 - Daily
Script has enabled the option to change the values for these timeframes as per the user requirement.
These ranges can be interpreted and acts as a probable swing points based on the trend and momentum.
40-60 - Neutral Range or Sideways
20 - 60 Bearish range
40 - 70 - Bullish range
Below 20 -- Over Sold Zone
Above 80 - over Bought zone
Also, the crossovers of the WMA and EMA on the RSI gives a very good momentum towards that trend.
在腳本中搜尋"信达股份40周年"
ADX with SignalsThis indicator basicly usind ADX ( Average Directional Index )
ADX can show us how trend is strong
ADX below 20: the market is currently not trending
ADX crosses above 20: signifies that a new trend is emerging. Traders may start placing sell or buy orders in the direction of the price movement.
ADX between 20 and 40: When the ADX is growing between 20 and 40 it is considered as a confirmation of an emerging trend. Traders should use this opportunity to buy or short sell in the trend's direction.
ADX above 40: the trend is very strong.
ADX crosses 50: the trend is extremely strong.
ADX crosses 70: a very rare occasion, which is called a “Power Trend.”
If we use ADX with DI+ and DI+ indactor can tell us to buy.
How can we calculate this all?
Directional Movement (DI) is defined as the largest part of the current period’s price range that lies outside the previous period’s price range. For each period calculate:
+DI = positive or plus DI = High - Previous High
-DI = negative or minus DI = Previous Low - Low
The smaller of the two values is reset to zero, i.e., if +DI > -DI , then -DI = 0. On an inside bar (a lower high and higher low), both +DI and -DI are negative values, so both get reset to zero as there was no directional movement for that period.
The True Range ( TR ) is calculated for each period, where:
TR = Max of ( High - Low ), ( High -PreviousClose ), ( PreviousClose - Low )
The +DI , -DI and TR are each accumulated and smoothed using a custom smoothing method proposed by Wilder. For an n period smoothing, 1/n of each period’s value is added to the total each period, similar to an exponential smoothing:
+DIt = (+DIt-1 - (+DIt-1 / n)) + (+DIt)
-DIt = (-DIt-1 - (-DIt-1 / n)) + (-DIt)
TRt = (TRt-1 - (TRt-1 / n)) + ( TRt )
Compute the positive/negative Directional Indexes, +DI and -DI , as a percentage of the True Range:
+DI = ( +DI / TR ) * 100
-DI = ( -DI / TR ) * 100
Compute the Directional Difference as the absolute value of the differences: DIdiff = | (( +DI ) - ( -DI )) |
Sum the directional indicator values: DIsum = (( +DI ) + ( -DI )) .
Calculate the Directional Movement index: DX = ( DIdiff / DIsum ) * 100 . The DX is always between 0 and 100.
Finally, apply Wilder’s smoothing technique to produce the final ADX value:
ADXt = ( ( ADXt-1 * ( n - 1) ) + DXt ) / n
When indicator tell us to buy?
If when DI+ crosses DI- and ADX is bigger than DI- indicator tell us to buy.
RSI Step Oscillator [racer8]Purpose of RSO is to identify when RSI has reached key levels. These levels are 80, 70, 60, 40, 30, and 20.
When indicator displays a bar with color...
Purple : RSI > 80
Blue : RSI > 70
Green : RSI > 60
Gray : RSI is inbetween 40 and 60.
Yellow : RSI < 40
Orange : RSI < 30
Red : RSI < 20
Hit the like button and enjoy 😁
ADX+DMI_by_BIMashed together Chris Moody's ADX thing with his DMI thing.
So you can see trend strength + direction
green-ish = uptrend-ish//red-ish = downtrend-ish
Colors can be adjusted though.
below 10 = gray, not much going on
10 - 20 = light green/light red, could be the beginning o something
20 - 40 = bright green / bright red, something is going on
above 40 = dark green, dark red, exhaustion (default is 40, can be adjusted to whatever)
RSI with Visual Buy/Sell Setup | Corrective/Impulsive IndicatorRSI with Visual Buy/Sell Setup | 40-60 Support/Resistance | Corrective/Impulsive Indicator v2.15
|| RSI - The Complete Guide PDF ||
Modified Zones with Colors for easy recognition of Price Action.
Resistance @ downtrend = 60
Support @ uptrend = 40
Over 70 = Strong Bullish Impulse
Under 30 = Strong Bearish Impulse
Uptrend : 40-80
Downtrend: 60-20
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Higher Highs in price, Lower Highs in RSI = Bearish Divergence
Lower Lows in price, Higher Lows in RSI = Bullish Divergence
--------------------
Trendlines from Higher/Lower Peaks, breakout + retest for buy/sell setups.
###################
There are multiple ways for using RSI, not only divergences, but it confirms the trend, possible bounce for continuation and signals for possible trend reversal.
There's more advanced use of RSI inside the book RSI: The Complete Guide
Go with the force, and follow the trend.
"The Force is more your friend than the trend"
Chop and explodeThe purpose of this script is to decipher chop zones from runs/movement/explosion
The chop is RSI movement between 40 and 60
tight chop is RSI movement between 45 and 55. There should be an explosion after RSI breaks through 60 (long) or 40 (short). Tight chop bars are colored black, a series of black bars is tight consolidation and should explode imminently. The longer the chop the longer the explosion will go for. tighter the better.
Loose chop (whip saw/yellow bars) will range between 40 and 60.
the move begins with blue bars for long and purple bars for short.
Couple it with your trading system to help stay out of chop and enter when there is movement. Use with "Simple Trender."
Best of luck in all you do. Get money.
Edge of MomentumThe script was designed for the purpose of catching the rocket portion of a move (the edge of momentum).
Long
--When RSI closes over 60, take long order 1 tick above that bar. The closed bar above RSI 60 will be colored "green" or whatever color the user chooses. (RSI > 60)
--On a long position, exit will be a closed bar below the ema (low, 10) . The closed bar below the ema will be colored "yellow." (Price < ema)
--Note: On a long position there is no need to exit when a closed bar is colored "purple." RSI is just below 60 but above 40. Pullback or chop
Short
--When RSI closes below 40, take a short order 1 tick below that bar. The closed bar below RSI 40 will be colored "red." RSI<40)
--On a short position, exit will be a closed bar above the ema (low, 10). The closed bar above the ema will be colored "purple." (Price > ema)
--Note: On a short position there is no need to exit when a closed bar is colored "yellow."
Note: You may see a series of purple and yellow bars, that is simply chop. I define chop as RSI moving between 60 and 40.
Trade should only be taken above green colored candle(long) and below red colored candle (short). No position should be taken off yellow or purple candle (chop)
Again this is designed to catch the momentum part of a move, and to help reduce some entries during chop. It is a simple systems that beginning traders can use and profit from.
Note: I don't no shit about coding scripts I just learn from reading others.
Enjoy. If you decide to use please drop me a line...suggestions/comments, etc.
Best of luck in all you do.
Money Flow Index + AlertsThis study is based on the work of TV user Beasley Savage ( ) and all credit goes to them.
Changes I've made:
1. Added a visual symbol of an overbought/oversold threshold cross in the form of a red/green circle, respectively. Sometimes it can be hard to see when a cross actually occurs, and if your scaling isn't set up properly you can get misleading visuals. This way removes all doubt. Bear in mind they aren't meant as trading signals, so DO NOT use them as such. Research the MFI if you're unsure, but I use them as an early warning and that particular market/stock is added to my watchlist.
2. Added 60/40 lines as the MFI respects these incredibly well in trends. E.g. in a solid uptrend the MFI won't go below 40, and vice versa. Use the idea of support and resistance levels on the indicator and it'll be a great help. I've coloured the zones. Strong uptrends should stay above 60, strong downtrends should stay below 40. The zone in between 40-60 I've called the transition zone. MFI often stays here in consolidation periods, and in the last leg of a cycle/trend the MFI will often drop into this zone after being above 60 or below 40. This is a great sign that you should get out and start looking to reverse your position. Hopefully it helps to spot divergences as well.
3. Added alerts based on an overbought/oversold cross. Also added an alert for when either condition is triggered, so hopefully that's useful for those struggling with low alert limits. Feel free to change the overbought/oversold levels, the alerts + crossover visual are set to adapt.
Like any indicator, don't use this one alone. It works best paired with indicators/techniques that contradict it. You'll often see a OB/OS cross, and price will continue on it's way for many weeks more. But MFI is a great tool for identifying upcoming trend changes.
Any queries please comment or PM me.
Cheers,
RJR
Average Directional Index with DI SpreadThis indicator converts conventional triple lined ADX, DI+ and DI- into two lines. First line is the
original ADX line and second line is obtained by subtracting DI- from DI+ which named DI Spread(DIS)
If ADX is greater than 20 there is a trend and if greater than 40 there is a strong trend but ADX does not tell
the trend direction
To determine trend direction, DIS can be used with ADX; Sımply; If DIS is greater than 0, it is an uptrend and If DIS
is less than 0, it is a downtrend.
To sum up;
If ADX is greater than 20 and especially greater than 40 with positive DIS value, this implies an uptrend.
If ADX is greater than 20 and especially greater than 40 with negative DIS value, this implies a downtrend.
*Because of coloration and reference levels used, this indicator is really simple and efficient to analyze trend direction.
90009If( MDI(14)>40 AND ADX(14)>40 AND PDI(14)<15 AND RSI(14)<30,1,0)
;If( MDI(14)<15 AND ADX(14)<15 AND PDI(14)>40 AND RSI(14)>70,-1,0)
CM_ADX+DMI ModMashed together Chris Moody's ADX thing with his DMI thing.
So you can see trend strength + direction
green-ish = uptrend-ish//red-ish = downtrend-ish
Colors can be adjusted though.
below 10 = gray, not much going on
10 - 20 = light green/light red, could be the beginning o something
20 - 40 = bright green / bright red, something is going on
above 40 = dark green, dark red, exhaustion (default is 40, can be adjusted to whatever)
Indicators: Volume Zone Indicator & Price Zone IndicatorVolume Zone Indicator (VZO) and Price Zone Indicator (PZO) are by Waleed Aly Khalil.
Volume Zone Indicator (VZO)
------------------------------------------------------------
VZO is a leading volume oscillator that evaluates volume in relation to the direction of the net price change on each bar.
A value of 40 or above shows bullish accumulation. Low values (< 40) are bearish. Near zero or between +/- 20, the market is either in consolidation or near a break out. When VZO is near +/- 60, an end to the bull/bear run should be expected soon. If that run has been opposite to the long term price trend direction, then a reversal often will occur.
Traditional way of looking at this also works:
* +/- 40 levels are overbought / oversold
* +/- 60 levels are extreme overbought / oversold
More info:
drive.google.com
Price Zone Indicator (PZO)
------------------------------------------------------------
PZO is interpreted the same way as VZO (same formula with "close" substituted for "volume").
Chart Markings
------------------------------------------------------------
In the chart above,
* The red circles indicate a run-end (or reversal) zones (VZO +/- 60).
* Blue rectangle shows the consolidation zone (VZO betwen +/- 20)
I have been trying out VZO only for a week now, but I think this has lot of potential. Give it a try, let me know what you think.
Fisher (zero-color + simple OB assist)//@version=5
indicator("Fisher (zero-color + simple OB assist)", overlay=false)
// Inputs
length = input.int(10, "Fisher Period", minval=1)
pivotLen = input.int(3, "Structure pivot length (SMC-lite)", minval=1)
showZero = input.bool(true, "Show Zero Line")
colPos = input.color(color.lime, "Color Above 0 (fallback)")
colNeg = input.color(color.red, "Color Below 0 (fallback)")
useOB = input.bool(true, "Color by OB proximity (Demand below = green, Supply above = red)")
showOBMarks = input.bool(true, "Show OB markers")
// Fisher (MT4-style port)
price = (high + low) / 2.0
hh = ta.highest(high, length)
ll = ta.lowest(low, length)
rng = hh - ll
norm = rng != 0 ? (price - ll) / rng : 0.5
var float v = 0.0
var float fish = 0.0
v := 0.33 * 2.0 * (norm - 0.5) + 0.67 * nz(v , 0)
v := math.min(math.max(v, -0.999), 0.999)
fish := 0.5 * math.log((1 + v) / (1 - v)) + 0.5 * nz(fish , 0)
// SMC-lite OB
ph = ta.pivothigh(high, pivotLen, pivotLen)
pl = ta.pivotlow(low, pivotLen, pivotLen)
var float lastSwingHigh = na
var float lastSwingLow = na
if not na(ph)
lastSwingHigh := ph
if not na(pl)
lastSwingLow := pl
bosUp = not na(lastSwingHigh) and close > lastSwingHigh
bosDn = not na(lastSwingLow) and close < lastSwingLow
bearishBar = close < open
bullishBar = close > open
demHigh_new = ta.valuewhen(bearishBar, high, 0)
demLow_new = ta.valuewhen(bearishBar, low, 0)
supHigh_new = ta.valuewhen(bullishBar, high, 0)
supLow_new = ta.valuewhen(bullishBar, low, 0)
// แยกประกาศตัวแปรทีละตัว และใช้ชนิดให้ชัดเจน
var float demHigh = na
var float demLow = na
var float supHigh = na
var float supLow = na
var bool demActive = false
var bool supActive = false
if bosUp and not na(demHigh_new) and not na(demLow_new)
demHigh := demHigh_new
demLow := demLow_new
demActive := true
if bosDn and not na(supHigh_new) and not na(supLow_new)
supHigh := supHigh_new
supLow := supLow_new
supActive := true
// Mitigation (แตะโซน)
if demActive and not na(demHigh) and not na(demLow)
if low <= demHigh
demActive := false
if supActive and not na(supHigh) and not na(supLow)
if high >= supLow
supActive := false
demandBelow = useOB and demActive and not na(demHigh) and demHigh <= close
supplyAbove = useOB and supActive and not na(supLow) and supLow >= close
colDimUp = color.new(colPos, 40)
colDimDown = color.new(colNeg, 40)
barColor = demandBelow ? colPos : supplyAbove ? colNeg : fish > 0 ? colDimUp : colDimDown
// Plots
plot(0, title="Zero", color=showZero ? color.new(color.gray, 70) : color.new(color.gray, 100))
plot(fish, title="Fisher", style=plot.style_columns, color=barColor, linewidth=2)
plotchar(showOBMarks and demandBelow ? fish : na, title="Demand below", char="D", location=location.absolute, color=color.teal, size=size.tiny)
plotchar(showOBMarks and supplyAbove ? fish : na, title="Supply above", char="S", location=location.absolute, color=color.fuchsia, size=size.tiny)
alertcondition(ta.crossover(fish, 0.0), "Fisher Cross Up", "Fisher crosses above 0")
alertcondition(ta.crossunder(fish, 0.0), "Fisher Cross Down", "Fisher crosses below 0")
ForecastForecast (FC), indicator documentation
Type: Study, not a strategy
Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars
Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets
⸻
What the indicator does
FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes:
• Absolute: Forecast of the selected symbol
• Relative: Forecast of the ratio symbol / benchmark
• Combined: Average of Absolute and Relative
A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs.
⸻
PineScreener, relative-strength screening
This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale.
Available PineScreener columns
PineScreener reads the plotted series. You will see at least these columns:
• FC, the capped forecast
• from EMA20, (price − EMA20) / ATR in ATR multiples
• from EMA50, (price − EMA50) / ATR in ATR multiples
• ATR, ATR as a percent of price
• Corr, weekly correlation with the chosen benchmark
Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source.
⸻
How it works, step by step
1. Volatility model
Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma.
2. EWMAC momentum, three legs
Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128).
Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor.
3. Breakout momentum, three channels
Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged.
4. Composite forecast
Average the EWMAC composite and the breakout composite, then cap to ±20.
Relative mode runs the same logic on symbol / benchmark.
Combined mode averages Absolute and Relative composites.
5. Weekly correlation
Pearson correlation between weekly closes of the asset and the benchmark over a user-set length.
6. Direction overlay
Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20.
⸻
Plots
• FC, capped forecast on the daily chart
• 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view
• 8-32-128 Abs, 8-32-128 Rel, three-leg composite views
• from EMA20, from EMA50, (price − EMA) / ATR
• ATR, ATR as a percent of price
• Corr, weekly correlation with the benchmark
• Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill
• Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides
Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them.
⸻
Inputs
Symbol selection
• Absolute, Relative, Combined
• Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD
• Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL
Engine selection
• Include:
• 8-32-128, three EWMAC legs plus three breakouts
• 8-32, simplified view based on the 8-32 leg plus a 40-day breakout
EMA, applied to the forecast
• EMA1, EMA2, with line-width controls, plus color and opacity
Volatility
• Span, EW volatility span for daily returns
• 10y %, blend of long-run volatility
• Thresh, Too volatile, placeholders in this version
Background
• Horizontal bg, level shading, enabled by default
• Long BG, Hedge BG, colors and opacities
Show
• Table, Header, Direction, Gain, Extension
• Corr, Length for correlation row
Table settings
• Position, background, opacity, text size, text color
Lines
• 0-lines, 10-lines, 5-lines, level guides
⸻
Reading the outputs
• Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt
• ±10 and ±20 indicate strength on a uniform scale
• EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum
• Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances
⸻
Data handling, repainting, and performance
• Daily and weekly series are fetched with request.security().
• Calculations use closed bars, values can update until the bar closes.
• No lookahead, historical values do not repaint.
• Weekly correlation updates during the week, it finalizes on weekly close.
• On intraday charts most visuals are hidden by design.
⸻
Good practice and limitations
• This is a research indicator, not a trading system.
• The fixed Cap = 20 keeps a common scale, extreme moves will be clipped.
• Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed.
⸻
Credits
Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script.
⸻
Changelog
• First version
⸻
Disclaimer
For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI
What this is
A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts:
• A sensitivity window that scans several recent bars to capture the strongest up and down impulses.
• A selectable moving average that smooths those impulses before computing RSI.
The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection.
How it works
Impulse extraction
• For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price.
• It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise.
MA-based averaging
• The up and down impulse series are averaged with your chosen MA over rsi_len bars.
• Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA.
Zero-centered RSI transform
• RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) .
• Above 0 implies positive momentum bias. Below 0 implies negative momentum bias.
Optional extra smoothing
• A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”.
Visual encoding
• The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes.
• Static bands mark 80 to 100 and −80 to −100 for extreme conditions.
Key inputs and what they change
• Price Source : input series for momentum.
• Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower.
• Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts.
• Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower.
• Smoothing Type and Length : optional second pass to calm noise on the final output.
• UI toggles : show or hide the oscillator, candle painting, and extreme bands.
Reading the oscillator
• Midline cross up (0) : momentum bias turning positive.
• Midline cross down (0) : momentum bias turning negative.
• Positive territory :
– 0 to 40: constructive but not stretched.
– 40 to 80: strong momentum, continuation more likely.
– Above 80: extreme risk of mean reversion grows.
• Negative territory : mirror the same levels for the downside.
Divergence detection
The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR .
• Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion.
• Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up.
• Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion.
• Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down.
Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish.
Candle coloring
• Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only.
Strengths
• Adaptive sensitivity via a rolling impulse window that responds to genuine bursts.
• Configurable MA core so you can match responsiveness to the instrument.
• Zero-centered scale for simple regime reads with 0 as a clear bias line.
• Built-in regular and hidden divergence mapping.
• Flexible across symbols and timeframes once tuned.
Limitations and cautions
• Trends can remain extended. Treat extremes as context rather than automatic reversal signals.
• Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag.
• Double smoothing can delay zero-line transitions. Balance smoothness and timeliness.
Practical usage ideas
• Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0.
• Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends.
• Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence.
• Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts.
Alerts
• MA-A RSI Long : oscillator crosses above 0.
• MA-A RSI Short : oscillator crosses below 0.
Use these as bias or timing aids, not standalone trade commands.
Settings quick reference
• Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity.
• Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing.
• UI : Show Oscillator, Paint Candles, Show Static High and Low Levels.
• Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences.
Final thoughts
This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.
T-Virus Sentiment [hapharmonic]🧬 T-Virus Sentiment: Visualize the Market's DNA
Remember the iconic T-Virus vial from the first Resident Evil? That powerful, swirling helix of potential has always fascinated me. It sparked an idea: what if we could visualize the market's underlying health in a similar way? What if we could capture the "genetic code" of market sentiment and contain it within a dynamic, 3D indicator? This project is the result of that idea, brought to life with Pine Script.
The indicator's main goal is to measure the strength and direction of market sentiment by analyzing the "genetic code" of price action through a variety of trusted indicators. The result is displayed as a liquid level within a DNA helix, a bubble density representing buying pressure, and a T-Virus mascot that reflects the overall mood.
🧐 Core Concept: How It Works
The primary output of the indicator is the "Active %" gauge you see on the right side of the vial. This percentage represents the overall sentiment score, calculated as an average from 7 different technical analysis tools. Each tool is analyzed on every bar and assigned a score from 1 (strong bearish pressure) to 5 (strong bullish potential).
In this indicator, we re-imagine market dynamics through the lens of a viral outbreak. A strong bear market is like a virus taking hold, pulling all technical signals down into a state of weakness. Conversely, a powerful bull market is like an antiviral serum ; positive signals rise and spread toward the top of the vial, indicating that the system is being injected with strength.
This is not just another line on a chart. It's a comprehensive sentiment dashboard designed to give an immediate, at-a-glance understanding of the confluence between 7 classic technical indicators. The incredible 3D model of the vial itself was inspired by a design concept found here .
⚛️ The 4 Core Elements of T-Virus Sentiment
These four elements work in harmony to give a complete, multi-faceted picture of market sentiment. Each component tells a different part of the story.
The Virus Mascot: An instant emotional cue. This character provides the quickest possible read on the overall market mood, combining sentiment with volume pressure.
The Antiviral Serum Level: The main quantitative output. This is the liquid level in the DNA helix and the percentage gauge on the right, representing the average sentiment score from all 7 indicators.
Buy Pressure & Bubble Density: This visualizes volume flow. The density of bubbles represents the intensity of accumulation (buying) versus distribution (selling). It's the "power" behind the move.
The Signal Distribution: This shows the confluence (or dispersion) of sentiment. Are all signals bullish and clustered at the top, or are they scattered, indicating a conflicted market? The position of the indicator labels is crucial, as each is assigned to one of five distinct zones:
Base Bottom: The market is at its weakest. Signals here suggest strong bearish control and distribution.
Lower Zone: The market is still bearish, but signals may be showing early signs of accumulation or bottoming.
Neutral Core (Center): A state of balance or sideways consolidation. The market is waiting for a new direction.
Upper Zone: Bullish momentum is becoming clear. Signals are strengthening and showing bullish control.
Top Cap: The market is "heating up" with strong bullish sentiment, potentially nearing overbought conditions.
🐂🐻 The Virus Mascot: The At-a-Glance Indicator
This character acts as a shortcut to confirm market health. It combines the sentiment score with volume, preventing false confidence in a low-volume rally.
Its state is determined by a dual-check: the overall "Antiviral Serum Level" and the "Buy Pressure" must both be above 50%.
Green & Smiling: The 'all clear' signal. This means that not only is the overall technical sentiment bullish, but it's also being supported by real buying pressure. This is a sign of a healthy bull market.
Red & Angry: A warning sign. This appears if either the sentiment is weak, or a bullish sentiment is not being confirmed by buying volume. The latter could indicate a potential "bull trap" or an exhaustive move.
This mascot can be disabled from the settings page under "Virus Mascot Styling" if a cleaner look is preferred.
🫧 Bubble Density: Gauging Buy vs. Sell Pressure
The bubbles visualize the battle between buyers and sellers. There are two modes to control how this is calculated:
Mode 1: Visible Range (The 'Big Picture' View)
This default mode is best for getting a broad, contextual understanding of the current session. It dynamically analyzes the volume of every single candlestick currently visible on the screen to calculate the buy/sell pressure ratio. It answers the question: "Over the entire period I'm looking at, who is in control?" As you zoom in or out, the calculation adapts.
Mode 2: Custom Lookback (The 'Precision' View)
This mode is for traders who need to analyze short-term pressure. You can define a fixed number of recent bars to analyze, which is perfect for scalping or understanding the volume dynamics leading into a key level. It answers the question: "What is happening right now ?" In the example above, a lookback of 2 focuses only on the most recent action, clearly showing intense, immediate selling pressure (few bubbles) and a corresponding drop in the sentiment score to 29%.
ℹ️ Interactive Tooltips: Dive Deeper
We believe in transparency, not 'black box' indicators. This feature transforms the indicator from a visual aid into an active learning tool.
Simply hover the mouse over any indicator label (like EMA, OBV, etc.) to get a detailed tooltip. It will explain the specific data points and thresholds that signal met to be placed in its current zone. This helps build trust in the signals and allows users to fine-tune the indicator settings to better match their own trading style.
🎯 The Scoring Logic Breakdown
The "Antiviral Serum Level" gauge is the average score from 7 technical analysis tools. Each is graded on a 5-point scale (1=Strong Bearish to 5=Strong Bullish). Here’s a detailed, transparent look at how each "gene" is evaluated:
Relative Strength Index (RSI)
Measures momentum and overbought/oversold conditions.
Group 1 (Strong Bearish): RSI > 80 (Extreme Overbought)
Group 2 (Bearish): 70 < RSI ≤ 80 (Overbought)
Group 3 (Neutral): 30 ≤ RSI ≤ 70
Group 4 (Bullish): 20 ≤ RSI < 30 (Oversold)
Group 5 (Strong Bullish): RSI < 20 (Extreme Oversold)
Exponential Moving Averages (EMA)
Evaluates the trend's strength and structure based on the alignment of multiple EMAs (9, 21, 50, 100, 200, 250).
Group 1 (Strong Bearish): A perfect bearish sequence (9 < 21 < 50 < ...)
Group 2 (Bearish Transition): Early signs of a potential reversal (e.g., 9 > 21 but still below 50)
Group 3 (Neutral / Mixed): MAs are intertwined or showing a partial bullish sequence.
Group 4 (Bullish): A strong bullish sequence is forming (e.g., 9 > 21 > 50 > 100)
Group 5 (Strong Bullish): A perfect bullish sequence (9 > 21 > 50 > 100 > 200 > 250)
Moving Average Convergence Divergence (MACD)
Analyzes the relationship between two moving averages to gauge momentum.
Group 1 (Strong Bearish): MACD & Histogram are negative and momentum is falling.
Group 2 (Weakening Bearish): MACD is negative but the histogram is rising or positive.
Group 3 (Neutral / Crossover): A crossover event is occurring near the zero line.
Group 4 (Bullish): MACD & Histogram are positive.
Group 5 (Strong Bullish): MACD & Histogram are positive, rising strongly, and accelerating.
Average Directional Index (ADX)
Measures trend strength, not direction. The score is based on both ADX value and the dominance of DI+ vs DI-.
Group 1 (Bearish / No Trend): ADX < 20 and DI- is dominant.
Group 2 (Developing Bearish Trend): 20 ≤ ADX < 25 and DI- is dominant.
Group 3 (Neutral / Indecision): Trend is weak or DI+ and DI- are nearly equal.
Group 4 (Developing Bullish Trend): 25 ≤ ADX ≤ 40 and DI+ is dominant.
Group 5 (Strong Bullish Trend): ADX > 40 and DI+ is dominant.
Ichimoku Cloud (IKH)
A comprehensive indicator that defines support/resistance, momentum, and trend direction.
Group 1 (Strong Bearish): Price is below the Kumo, Tenkan < Kijun, and Chikou is below price.
Group 2 (Bearish): Price is inside or below the Kumo, with mixed secondary signals.
Group 3 (Neutral / Ranging): Price is inside the Kumo, often with a Tenkan/Kijun cross.
Group 4 (Bullish): Price is above the Kumo with strong primary signals.
Group 5 (Strong Bullish): All signals are aligned bullishly: price above Kumo, bullish Tenkan/Kijun cross, bullish future Kumo, and Chikou above price.
Bollinger Bands (BB)
Measures volatility and relative price levels.
Group 1 (Strong Bearish): Price is below the lower band.
Group 2 (Bearish Territory): Price is between the lower band and the basis line.
Group 3 (Neutral): Price is hovering around the basis line.
Group 4 (Bullish Territory): Price is between the basis line and the upper band.
Group 5 (Strong Bullish): Price is above the upper band.
On-Balance Volume (OBV)
Uses volume flow to predict price changes. The score is based on OBV's trend and its position relative to its moving average.
Group 1 (Strong Bearish): OBV is below its MA and falling.
Group 2 (Weakening Bearish): OBV is below its MA but showing signs of rising.
Group 3 (Neutral): OBV is very close to its MA.
Group 4 (Bullish): OBV is above its MA and rising.
Group 5 (Strong Bullish): OBV is above its MA, rising strongly, and showing signs of a volume spike.
🧭 How to Use the T-Virus Sentiment Indicator
IMPORTANT: This indicator is a sentiment dashboard , not a direct buy/sell signal generator. Its strength lies in showing confluence and providing a quick, holistic view of the market's technical health.
Confirmation Tool: Use the "Active %" gauge to confirm a trade setup from your primary strategy. For example, if you see a bullish chart pattern, a high and rising sentiment score can add confidence to your trade.
Momentum & Trend Gauge: A consistently high score (e.g., > 75%) suggests strong, established bullish momentum. A consistently low score (< 25%) suggests strong bearish control. A score hovering around 50% often indicates a ranging or indecisive market.
Divergence & Warning System: Pay attention to divergences. If the price is making new highs but the sentiment score is failing to follow or is actively decreasing, it could be an early warning sign that the underlying momentum is weakening.
⚙️ Settings & Customization
The indicator is highly customizable to fit any trading style.
Position & Anchor: Control where the vial appears on the chart.
Styling (Vial, Helix, etc.): Nearly every visual element can be color-customized.
Signals: This is where the real power is. All underlying indicator parameters (RSI length, MACD settings, etc.) can be fine-tuned to match a personal strategy. The text labels can also be disabled if the chart feels cluttered.
Enjoy visualizing the market's DNA with the T-Virus Sentiment indicator
Multi-TF Trend Table (Configurable)1) What this tool does (in one minute)
A compact, multi‑timeframe dashboard that stacks eight timeframes and tells you:
Trend (fast MA vs slow MA)
Where price sits relative to those MAs
How far price is from the fast MA in ATR terms
MA slope (rising, falling, flat)
Stochastic %K (with overbought/oversold heat)
MACD momentum (up or down)
A single score (0%–100%) per timeframe
Alignment tick when trend, structure, slope and momentum all agree
Use it to:
Frame bias top‑down (M→W→D→…→15m)
Time entries on your execution timeframe when the higher‑TF stack is aligned
Avoid counter‑trend traps when the table is mixed
2) Table anatomy (each column explained)
The table renders 9 columns × 8 rows (one row per timeframe label you define).
TF — The label you chose for that row (e.g., Month, Week, 4H). Cosmetic; helps you read the stack.
Trend — Arrow from fast MA vs slow MA: ↑ if fastMA > slowMA (up‑trend), ↓ otherwise (down‑trend). Cell is green for up, red for down.
Price Pos — One‑character structure cue:
🔼 if price is above both fast and slow MAs (bullish structure)
🔽 if price is below both (bearish structure)
– otherwise (between MAs / mixed)
MA Dist — Distance of price from the fast MA measured in ATR multiples:
XS < S < M < L < XL according to your thresholds (see §3.3). Useful for judging stretch/mean‑reversion risk and stop sizing.
MA Slope — The fast MA one‑bar slope:
↑ if fastMA - fastMA > 0
↓ if < 0
→ if = 0
Stoch %K — Rounded %K value (default 14‑1‑3). Background highlights when it aligns with the trend:
Green heat when trend up and %K ≤ oversold
Red heat when trend down and %K ≥ overbought Tooltip shows K and D values precisely.
Trend % — Composite score (0–100%), the dashboard’s confidence for that timeframe:
+20 if trendUp (fast>slow)
+20 if fast MA slope > 0
+20 if MACD up (signal definition in §2.8)
+20 if price above fast MA
+20 if price above slow MA
Background colours:
≥80 lime (strong alignment)
≥60 green (good)
≥40 orange (mixed)
<40 grey (weak/contrary)
MACD — 🟢 if EMA(12)−EMA(26) > its EMA(9), else 🔴. It’s a simple “momentum up/down” proxy.
Align — ✔ when everything is in gear for that trend direction:
For up: trendUp and price above both MAs and slope>0 and MACD up
For down: trendDown and price below both MAs and slope<0 and MACD down Tooltip spells this out.
3) Settings & how to tune them
3.1 Timeframes (TF1–TF8)
Inputs: TF1..TF8 hold the resolution strings used by request.security().
Defaults: M, W, D, 720, 480, 240, 60, 15 with display labels Month, Week, Day, 12H, 8H, 4H, 1H, 15m.
Tips
Keep a top‑down funnel (e.g., Month→Week→Day→H4→H1→M15) so you can cascade bias into entries.
If you scalp, consider D, 240, 120, 60, 30, 15, 5, 1.
Crypto weekends: consider 2D in place of W to reflect continuous trading.
3.2 Moving Average (MA) group
Type: EMA, SMA, WMA, RMA, HMA. Changes both fast & slow MA computations everywhere.
Fast Length: default 20. Shorten for snappier trend/slope & tighter “price above fast” signals.
Slow Length: default 200. Controls the structural trend and part of the score.
When to change
Swing FX/equities: EMA 20/200 is a solid baseline.
Mean‑reversion style: consider SMA 20/100 so trend flips slower.
Crypto/indices momentum: HMA 21 / EMA 200 will read slope more responsively.
3.3 ATR / Distance group
ATR Length: default 14; longer makes distance less jumpy.
XS/S/M/L thresholds: define the labels in column MA Dist. They are compared to |close − fastMA| / ATR.
Defaults: XS 0.25×, S 0.75×, M 1.5×, L 2.5×; anything ≥L is XL.
Usage
Entries late in a move often occur at L/XL; consider waiting for a pullback unless you are trading breakouts.
For stops, an initial SL around 0.75–1.5 ATR from fast MA often sits behind nearby noise; use your plan.
3.4 Stochastic group
%K Length / Smoothing / %D Smoothing: defaults 14 / 1 / 3.
Overbought / Oversold: defaults 70 / 30 (adjust to 80/20 for trendier assets).
Heat logic (column Stoch %K): highlights when a pullback aligns with the dominant trend (oversold in an uptrend, overbought in a downtrend).
3.5 View
Full Screen Table Mode: centers and enlarges the table (position.middle_center). Great for clean screenshots or multi‑monitor setups.
4) Signal logic (how each datapoint is computed)
Per‑TF data (via a single request.security()):
fastMA, slowMA → based on your MA Type and lengths
%K, %D → Stoch(High,Low,Close,kLen) smoothed by kSmooth, then %D smoothed by dSmooth
close, ATR(atrLen) → for structure and distance
MACD up → (EMA12−EMA26) > EMA9(EMA12−EMA26)
fastMA_prev → yesterday/previous‑bar fast MA for slope
TrendUp → fastMA > slowMA
Price Position → compares close to both MAs
MA Distance Label → thresholds on abs(close − fastMA)/ATR
Slope → fastMA − fastMA
Score (0–100) → sum of the five 20‑point checks listed in §2.7
Align tick → conjunction of trend, price vs both MAs, slope and MACD (see §2.9)
Important behaviour
HTF values are sampled at the execution chart’s bar close using Pine v6 defaults (no lookahead). So the daily row updates only when a daily bar actually closes.
5) How to trade with it (playbooks)
The table is a framework. Entries/exits still follow your plan (e.g., S/D zones, price action, risk rules). Use the table to know when to be aggressive vs patient.
Playbook A — Trend continuation (pullback entry)
Look for Align ✔ on your anchor TFs (e.g., Week+Day both ≥80 and green, Trend ↑, MACD 🟢).
On your execution TF (e.g., H1/H4), wait for Stoch heat with the trend (oversold in uptrend or overbought in downtrend), and MA Dist not at XL.
Enter on your trigger (break of pullback high/low, engulfing, retest of fast MA, or S/D first touch per your plan).
Risk: consider ATR‑based SL beyond structure; size so 0.25–0.5% account risk fits your rules.
Trail or scale at M/L distances or when score deteriorates (<60).
Playbook B — Breakout with confirmation
Mixed stack turns into broad green: Trend % jumps to ≥80 on Day and H4; MACD flips 🟢.
Price Pos shows 🔼 across H4/H1 (above both MAs). Slope arrows ↑.
Enter on the first clean base‑break with volume/impulse; avoid if MA Dist already XL.
Playbook C — Mean‑reversion fade (advanced)
Use only when higher TFs are not aligned and the row you trade shows XL distance against the higher‑TF context. Take quick targets back to fast MA. Lower win‑rate, faster management.
Playbook D — Top‑down filter for Supply/Demand strategy
Trade first retests only in the direction where anchor TFs (Week/Day) have Align ✔ and Trend % ≥60. Skip counter‑trend zones when the stack is red/green against you.
6) Reading examples
Strong bullish stack
Week: ↑, 🔼, S/M, slope ↑, %K=32 (green heat), Trend 100%, MACD 🟢, Align ✔
Day: ↑, 🔼, XS/S, slope ↑, %K=45, Trend 80%, MACD 🟢, Align ✔
Action: Look for H4/H1 pullback into demand or fast MA; buy continuation.
Late‑stage thrust
H1: ↑, 🔼, XL, slope ↑, %K=88
Day/H4: only 60–80%
Action: Likely overextended on H1; wait for mean reversion or multi‑TF alignment before chasing.
Bearish transition
Day flips from 60%→40%, Trend ↓, MACD turns 🔴, Price Pos “–” (between MAs)
Action: Stand aside for longs; watch for lower‑high + Align ✔ on H4/H1 to join shorts.
7) Practical tips & pitfalls
HTF closure: Don’t assume a daily row changed mid‑day; it won’t settle until the daily bar closes. For intraday anticipation, watch H4/H1 rows.
MA Type consistency: Changing MA Type changes slope/structure everywhere. If you compare screenshots, keep the same type.
ATR thresholds: Calibrate per asset class. FX may suit defaults; indices/crypto might need wider S/M/L.
Score ≠ signal: 100% does not mean “must buy now.” It means the environment is favourable. Still execute your trigger.
Mixed stacks: When rows disagree, reduce size or skip. The tool is telling you the market lacks consensus.
8) Customisation ideas
Timeframe presets: Save layouts (e.g., Swing, Intraday, Scalper) as indicator templates in TradingView.
Alternative momentum: Replace the MACD condition with RSI(>50/<50) if desired (would require code edit).
Alerts: You can add alert conditions for (a) Align ✔ changes, (b) Trend % crossing 60/80, (c) Stoch heat events. (Not shipped in this script, but easy to add.)
9) FAQ
Q: Why do I sometimes see a dash in Price Pos? A: Price is between fast and slow MAs. Structure is mixed; seek clarity before acting.
Q: Does it repaint? A: No, higher‑TF values update on the close of their own bars (standard request.security behaviour without lookahead). Intra‑bar they can fluctuate; decisions should be made at your bar close per your plan.
Q: Which columns matter most? A: For trend‑following: Trend, Price Pos, Slope, MACD, then Stoch heat for entries. The Score summarises, and Align enforces discipline.
Q: How do I integrate with ATR‑based risk? A: Use the MA Dist label to avoid chasing at extremes and to size stops in ATR terms (e.g., SL behind structure at ~1–1.5 ATR).
Screener based on Profitunity strategy for multiple timeframes
Screener based on Profitunity strategy by Bill Williams for multiple timeframes (max 5, including chart timeframe) and customizable symbol list. The screener analyzes the Alligator and Awesome Oscillator indicators, Divergent bars and high volume bars.
The maximum allowed number of requests (symbols and timeframes) is limited to 40 requests, for example, for 10 symbols by 4 requests of different timeframes. Therefore, the indicator automatically limits the number of displayed symbols depending on the number of timeframes for each symbol, if there are more symbols than are displayed in the screener table, then the ordinal numbers are displayed to the left of the symbols, in this case you can display the next group of symbols by increasing the value by 1 in the "Show tickers from" field, if the "Group" field is enabled, or specify the symbol number by 1 more than the last symbol in the screener table. 👀 When timeframe filtering is applied, the screener table displays only the columns of those timeframes for which the filtering value is selected, which allows displaying more symbols.
For each timeframe, in the "TIMEFRAMES > Prev" field, you can enable the display of data for the previous bar relative to the last (current) one, if the market is open for the requested symbol. In the "TIMEFRAMES > Y" field, you can enable filtering depending on the location of the last five bars relative to the Alligator indicator lines, which are designated by special symbols in the screener table:
⬆️ — if the Alligator is open upwards (Lips > Teeth > Jaw) and none of the bars is closed below the Lips line;
↗️ — if one of the bars, except for the penultimate one, is closed below Lips, or two bars, except for the last one, are closed below Lips, or the Alligator is open upwards only below four bars, but none of the bars is closed below Lips;
⬇️ — if the Alligator is open downwards (Lips < Teeth < Jaw), but none of the bars is closed above Lips;
↘️ — if one of the bars, except the penultimate one, is closed above the Lips, or two bars, except the last one, are closed above the Lips, or the Alligator is open down only above four bars, but none of the bars are closed above the Lips;
➡️ — in other cases, including when the Alligator lines intersect and one of the bars is closed behind the Lips line or two bars intersect one of the Alligator lines.
In the "TIMEFRAMES > Show bar change value for TF" field, you can add a column to the right of the selected timeframe column with the percentage change between the closing price of the last bar (current) and the closing price of the previous bar ((close – previous close) / previous close * 100). Depending on the percentage value, the background color of the screener table cell will change: dark red if <= -3%; red if <= -2%, light red if <= -0.5%; dark green if >= 3%; green if >= 2%; light green if >= 0.5%.
For each timeframe, the screener table displays the symbol of the latest (current) bar, depending on the closing price relative to the bar's midpoint ((high + low) / 2) and its location relative to the Alligator indicator lines: ⎾ — the bar's closing price is above its midpoint; ⎿ — the bar's closing price is below its midpoint; ├ — the bar's closing price is equal to its midpoint; 🟢 — Bullish Divergent bar, i.e. the bar's closing price is above its midpoint, the bar's high is below all Alligator lines, the bar's low is below the previous bar's low; 🔴 — Bearish Divergent bar, i.e. the bar's closing price is below its midpoint, the bar's low is above all Alligator lines, the bar's high is above the previous bar's high. When filtering is enabled in the "TIMEFRAMES > Filtering by Divergent bar" field, the data in the screener table cells will be displayed only for those timeframes that have a Divergent bar. A high bar volume signal is also displayed — 📶/📶² if the bar volume is greater than 40%/70% of the average volume value calculated using a simple moving average (SMA) in the 140 bar interval from the last bar.
In the indicator settings in the "SYMBOL LIST" field, each ticker (for example: OANDA:SPX500USD) must be on a separate line. If the market is closed, then the data for requested symbols will be limited to the time of the last (current) bar on the chart, for example, if the current symbol was traded yesterday, and the requested symbol is traded today, when requesting data for an hourly timeframe, the last bar will be for yesterday, if the timeframe of the current chart is not higher than 1 day. Therefore, by default, a warning will be displayed on the chart instead of the screener table that if the market is open, you must wait for the screener to load (after the first price change on the current chart), or if the highest timeframe in the screener is 1 day, you will be prompted to change the timeframe on the current chart to 1 week, if the screener requests data for the timeframe of 1 week, you will be prompted to change the timeframe on the current chart to 1 month, or switch to another symbol on the current chart for which the market is open (for example: BINANCE:BTCUSDT), or disable the warning in the field "SYMBOL LIST > Do not display screener if market is close".
The number of the last columns with the color of the AO indicator that will be displayed in the screener table for each timeframe is specified in the indicator settings in the "AWESOME OSCILLATOR > Number of columns" field.
For each timeframe, the direction of the trend between the price of the highest and lowest bars in the specified range of bars from the last bar is displayed — ↑ if the trend is up (the highest bar is to the right of the lowest), or ↓ if the trend is down (the lowest bar is to the right of the highest). If there is a divergence on the AO indicator in the specified interval, the symbol ∇ is also displayed. The average volume value is also calculated in the specified interval using a simple moving average (SMA). The number of bars is set in the indicator settings in the "INTERVAL FOR HIGHEST AND LOWEST BARS > Bars count" field.
In the indicator settings in the "STYLE" field you can change the position of the screener table relative to the chart window, the background color, the color and size of the text.
***
Скринер на основе стратегии Profitunity Билла Вильямса для нескольких таймфреймов (максимум 5, включая таймфрейм графика) и настраиваемого списка символов. Скринер анализирует индикаторы Alligator и Awesome Oscillator, Дивергентные бары и бары с высоким объемом.
Максимально допустимое количество запросов (символы и таймфреймы) ограничено 40 запросами, например, для 10 символов по 4 запроса разных таймфреймов. Поэтому в индикаторе автоматически ограничивается количество отображаемых символов в зависимости от количества таймфреймов для каждого символа, если символов больше чем отображено в таблице скринера, то слева от символов отображаются порядковые номера, в таком случае можно отобразить следующую группу символов, увеличив значение на 1 в настройках индикатора поле "Show tickers from", если включено поле "Group", или указать номер символа на 1 больше, чем последний символ в таблице скринера. 👀 Когда применяется фильтрация по таймфрейму, в таблице скринера отображаются только столбцы тех таймфреймов, для которых выбрано значение фильтрации, что позволяет отображать большее количество символов.
Для каждого таймфрейма в настройках индикатора в поле "TIMEFRAMES > Prev" можно включить отображение данных для предыдущего бара относительно последнего (текущего), если для запрашиваемого символа рынок открыт. В поле "TIMEFRAMES > Y" можно включить фильтрацию, в зависимости от расположения последних пяти баров относительно линий индикатора Alligator, которые обозначаются специальными символами в таблице скринера:
⬆️ — если Alligator открыт вверх (Lips > Teeth > Jaw) и ни один из баров не закрыт ниже линии Lips;
↗️ — если один из баров, кроме предпоследнего, закрыт ниже Lips, или два бара, кроме последнего, закрыты ниже Lips, или Alligator открыт вверх только ниже четырех баров, но ни один из баров не закрыт ниже Lips;
⬇️ — если Alligator открыт вниз (Lips < Teeth < Jaw), но ни один из баров не закрыт выше Lips;
↘️ — если один из баров, кроме предпоследнего, закрыт выше Lips, или два бара, кроме последнего, закрыты выше Lips, или Alligator открыт вниз только выше четырех баров, но ни один из баров не закрыт выше Lips;
➡️ — в остальных случаях, в то числе когда линии Alligator пересекаются и один из баров закрыт за линией Lips или два бара пересекают одну из линий Alligator.
В поле "TIMEFRAMES > Show bar change value for TF" можно добавить справа от выбранного столбца таймфрейма столбец с процентным изменением между ценой закрытия последнего бара (текущего) и ценой закрытия предыдущего бара ((close – previous close) / previous close * 100). В зависимости от величины процента будет меняться цвет фона ячейки таблицы скринера: темно-красный, если <= -3%; красный, если <= -2%, светло-красный, если <= -0.5%; темно-зеленый, если >= 3%; зеленый, если >= 2%; светло-зеленый, если >= 0.5%.
Для каждого таймфрейма в таблице скринера отображается символ последнего (текущего) бара, в зависимости от цены закрытия относительно середины бара ((high + low) / 2) и расположения относительно линий индикатора Alligator: ⎾ — цена закрытия бара выше его середины; ⎿ — цена закрытия бара ниже его середины; ├ — цена закрытия бара равна его середине; 🟢 — Бычий Дивергентный бар, т.е. цена закрытия бара выше его середины, максимум бара ниже всех линий Alligator, минимум бара ниже минимума предыдущего бара; 🔴 — Медвежий Дивергентный бар, т.е. цена закрытия бара ниже его середины, минимум бара выше всех линий Alligator, максимум бара выше максимума предыдущего бара. При включении фильтрации в поле "TIMEFRAMES > Filtering by Divergent bar" данные в ячейках таблицы скринера будут отображаться только для тех таймфреймов, где есть Дивергентный бар. Также отображается сигнал высокого объема бара — 📶/📶², если объем бара больше чем на 40%/70% среднего значения объема, рассчитанного с помощью простой скользящей средней (SMA) в интервале 140 баров от последнего бара.
В настройках индикатора в поле "SYMBOL LIST" каждый тикер (например: OANDA:SPX500USD) должен быть на отдельной строке. Если рынок закрыт, то данные для запрашиваемых символов будут ограничены временем последнего (текущего) бара на графике, например, если текущий символ торговался последний день вчера, а запрашиваемый символ торгуется сегодня, при запросе данных для часового таймфрейма, последний бар будет за вчерашний день, если таймфрейм текущего графика не выше 1 дня. Поэтому по умолчанию на графике будет отображаться предупреждение вместо таблицы скринера о том, что если рынок открыт, то необходимо дождаться загрузки скринера (после первого изменения цены на текущем графике), или если в скринере самый высокий таймфрейм 1 день, то будет предложено изменить на текущем графике таймфрейм на 1 неделю, если в скринере запрашиваются данные для таймфрейма 1 неделя, то будет предложено изменить на текущем графике таймфрейм на 1 месяц, или же переключиться на другой символ на текущем графике, для которого рынок открыт (например: BINANCE:BTCUSDT), или отключить предупреждение в поле "SYMBOL LIST > Do not display screener if market is close".
Количество последних столбцов с цветом индикатора AO, которые будут отображены в таблице скринера для каждого таймфрейма, указывается в настройках индикатора в поле "AWESOME OSCILLATOR > Number of columns".
Для каждого таймфрейма отображается направление тренда между ценой самого высокого и самого низкого баров в указанном интервале баров от последнего бара — ↑, если тренд направлен вверх (самый высокий бар справа от самого низкого), или ↓, если тренд направлен вниз (самый низкий бар справа от самого высокого). Если есть дивергенция на индикаторе AO в указанном интервале, то также отображается символ — ∇. В указанном интервале также рассчитывается среднее значение объема с помощью простой скользящей средней (SMA). Количество баров устанавливается в настройках индикатора в поле "INTERVAL FOR HIGHEST AND LOWEST BARS > Bars count".
В настройках индикатора в поле "STYLE" можно изменить положение таблицы скринера относительно окна графика, цвет фона, цвет и размер текста.
NAS100 Component Sentiment Scanner# NAS100 Component Sentiment Scanner
## 🎯 Overview
The NAS100 Component Sentiment Scanner analyzes the top-weighted stocks in the NASDAQ-100 index to provide real-time bullish/bearish sentiment signals that can help predict NAS100 price movements. This indicator combines multiple technical analysis methods to give traders a comprehensive view of underlying market sentiment.
## 📊 How It Works
The indicator calculates sentiment scores for major NASDAQ-100 components (AAPL, MSFT, NVDA, GOOGL, AMZN, META, TSLA, AVGO, COST, NFLX) using:
- **RSI Analysis**: Identifies overbought/oversold conditions
- **Moving Average Trends**: Compares fast vs slow MA positioning
- **Volume Confirmation**: Validates moves with volume thresholds
- **Price Momentum**: Analyzes recent price direction
- **Market Cap Weighting**: Uses actual NASDAQ-100 weightings for accuracy
## 🚀 Key Features
### Real-Time Sentiment Analysis
- Weighted composite score based on individual stock analysis
- Color-coded sentiment line (Green = Bullish, Red = Bearish)
- Dynamic background coloring for strong signals
### Interactive Data Table
- Shows individual stock scores and signals
- Bullish/Bearish stock count summary
- Customizable position and size
### Smart Signal System
- **Bullish Signals**: Green triangle up when sentiment crosses threshold
- **Bearish Signals**: Red triangle down when sentiment falls below threshold
- **Alert Conditions**: Automatic notifications for signal changes
## ⚙️ Customization Options
### Technical Analysis Settings
- **RSI Period**: Adjust lookback period (default: 14)
- **RSI Levels**: Set overbought/oversold thresholds
- **Moving Averages**: Configure fast/slow MA periods
- **Volume Threshold**: Set volume confirmation multiplier
### Signal Thresholds
- **Bullish/Bearish Levels**: Customize trigger points
- **Strong Signal Levels**: Set extreme sentiment thresholds
- Fine-tune sensitivity to market conditions
### Display Options
- **Toggle Table**: Show/hide sentiment data table
- **Table Position**: 6 position options (Top/Bottom/Middle + Left/Right)
- **Table Size**: Choose from Tiny, Small, Normal, or Large
- **Background Colors**: Enable/disable signal backgrounds
- **Signal Arrows**: Show/hide buy/sell indicators
### Stock Selection
- **Individual Control**: Enable/disable any of the 10 major stocks
- **Dynamic Weighting**: Automatically adjusts calculations based on selected stocks
- **Flexible Analysis**: Focus on specific sectors or market leaders
## 📈 How to Use
### 1. Basic Setup
1. Add the indicator to your NAS100 chart
2. Default settings work well for most traders
3. Observe the sentiment line and signals
### 2. Signal Interpretation
- **Score > 30**: Bullish bias for NAS100
- **Score > 50**: Strong bullish signal
- **Score -30 to 30**: Neutral/consolidation
- **Score < -30**: Bearish bias for NAS100
- **Score < -50**: Strong bearish signal
### 3. Trading Strategies
**Trend Following:**
- Buy NAS100 when bullish signals appear
- Sell/short when bearish signals trigger
- Use background colors for quick visual confirmation
**Divergence Trading:**
- Watch for sentiment/price divergences
- Strong sentiment with weak NAS100 price = potential breakout
- Weak sentiment with strong NAS100 price = potential reversal
**Consensus Trading:**
- Monitor bullish/bearish stock counts in table
- 8+ stocks aligned = strong directional bias
- Mixed signals = wait for clearer consensus
### 4. Advanced Usage
- Combine with your existing NAS100 trading strategy
- Use multiple timeframes for confirmation
- Adjust thresholds based on market volatility
- Focus on specific stocks by disabling others
## 🔔 Alert Setup
The indicator includes built-in alert conditions:
1. Go to TradingView Alerts
2. Select "NAS100 Component Sentiment Scanner"
3. Choose from available alert types:
- NAS100 Bullish Signal
- NAS100 Bearish Signal
- Strong Bullish Consensus
- Strong Bearish Consensus
## 💡 Pro Tips
### Optimization
- **High Volatility**: Increase signal thresholds (±40, ±60)
- **Low Volatility**: Decrease thresholds (±20, ±40)
- **Day Trading**: Use smaller table, focus on real-time signals
- **Swing Trading**: Enable background colors, larger thresholds
### Best Practices
- Don't use as a standalone system - combine with price action
- Check individual stock table for context
- Monitor during market open for most reliable signals
- Consider earnings seasons for individual stock impacts
### Market Conditions
- **Trending Markets**: Higher accuracy, use with trend following
- **Ranging Markets**: Watch for false signals, increase thresholds
- **News Events**: Individual stock news can skew sentiment temporarily
## 🎨 Visual Guide
- **Green Line Above Zero**: Bullish sentiment building
- **Red Line Below Zero**: Bearish sentiment building
- **Background Color Changes**: Strong signal confirmation
- **Triangle Arrows**: Entry/exit signal points
- **Table Colors**: Quick sentiment overview
## ⚠️ Important Notes
- This indicator analyzes component stocks, not NAS100 directly
- Market cap weightings approximate real NASDAQ-100 weightings
- Sentiment can change rapidly during volatile periods
- Always use proper risk management
- Combine with other technical analysis tools
## 🔧 Troubleshooting
- **No signals**: Check if thresholds are too extreme
- **Too many signals**: Increase threshold sensitivity
- **Table not showing**: Ensure "Show Sentiment Table" is enabled
- **Missing stocks**: Verify individual stock toggles in settings
---
**Suitable for**: Day traders, swing traders, NAS100 specialists, index traders
**Best Timeframes**: 5min, 15min, 1H, 4H
**Market Sessions**: US market hours for highest accuracy
Sector Rotation & Money Flow Dashboard📊 Overview
The Sector Rotation & Money Flow Dashboard is a comprehensive market analysis tool that tracks 39 major sector ETFs in real-time, providing institutional-grade insights into sector rotation, momentum shifts, and money flow patterns. This indicator helps traders identify which sectors are attracting capital, which are losing favor, and where the next opportunities might emerge.
Perfect for swing traders, position traders, and investors who want to stay ahead of sector rotation and ride the strongest trends while avoiding weak sectors.
🎯 What This Indicator Does
Tracks 39 Major Sectors: From technology to utilities, cryptocurrencies to commodities
Calculates Multiple Timeframes: 1-week, 1-month, 3-month, and 6-month performance
Advanced Momentum Metrics: Proprietary momentum score and acceleration calculations
Relative Strength Analysis: Compare sector performance against any benchmark index
Money Flow Signals: Visual indicators showing where institutional money is moving
Smart Filtering: Pre-built strategy filters for different trading styles
Trend Detection: Emoji-based visual system for quick trend identification
💡 Key Features
1. Performance Metrics
Multiple timeframe analysis (1W, 1M, 3M, 6M)
Month-over-month change tracking
Relative strength vs benchmark index
2. Advanced Analytics
Momentum Score: Weighted composite of recent performance
Acceleration: Rate of change in momentum (second derivative)
Money Flow Signals: IN/OUT/TURN/WATCH indicators
3. Strategy Preset Filters
🎯 Swing Trade: High momentum opportunities
📈 Trend Follow: Established uptrends
🔄 Mean Reversion: Oversold bounce candidates
💎 Value Hunt: Deep value opportunities
🚀 Breakout: Emerging strength
⚠️ Risk Off: Sectors to avoid
4. Customization
All 39 sector ETFs can be customized
Adjustable benchmark index
Flexible display options
Multiple sorting methods
📋 Settings Documentation
Display Settings
Show Table (Default: On)
Toggles the entire dashboard display
Table Position (Default: Middle Center)
Choose from 9 positions on your chart
Options: Top/Middle/Bottom × Left/Center/Right
Rows to Show (Default: 15)
Number of sectors displayed (5-40)
Useful for focusing on top/bottom performers
Sort By (Default: Momentum)
1M/3M/6M: Sort by specific timeframe performance
Momentum: Weighted recent performance score
Acceleration: Rate of momentum change
1M Change: Month-over-month improvement
RS: Relative strength vs benchmark
Flow: IN First: Prioritize sectors with inflows
Flow: TURN First: Focus on reversal candidates
Recovery Plays: Oversold sectors recovering
Oversold Bounce: Deepest declines with positive signs
Top Gainers/Losers 3M: Best/worst quarterly performers
Best Acc + Mom: Combined strength score
Worst Acc (Topping): Sectors losing momentum
Filter Settings
Strategy Preset Filter (Default: All)
All: No filtering
🎯 Swing Trade: Mom >5, Acc >2, Money flowing in
📈 Trend Follow: Positive 1M & 3M, RS >0
🔄 Mean Reversion: Oversold but improving
💎 Value Hunt: Down >10% with recovery signs
🚀 Breakout: Rapid momentum surge
⚠️ Risk Off: Declining or topping sectors
Custom Flow Filter: Use manual flow filter
Custom Flow Signal Filter (Default: All)
Only active when Strategy Preset = "Custom Flow Filter"
IN Only: Strong inflows
TURN Only: Reversal signals
WATCH Only: Recovery candidates
OUT Only: Outflow sectors
Active Flows Only: Any non-neutral signal
Hide Low Volume ETFs (Default: Off)
Filters out illiquid sectors (future enhancement)
Visual Settings
Show Trend Emojis (Default: On)
🚀 Breakout (Strong 1M + High Acceleration)
🔥 Hot Recovery (From -10% to positive)
💪 Steady Uptrend (All timeframes positive)
➡️ Sideways/Ranging
⚠️ Warning/Topping (Up >15%, now slowing)
📉 Falling (Negative + declining)
🔄 Bottoming (Improving from lows)
Compact Mode (Default: Off)
Removes decimals for cleaner display
Useful when showing many rows
Min Data Points Required (Default: 3)
Minimum data points needed to display a sector
Prevents showing sectors with insufficient data
Relative Strength Settings
RS Benchmark Index (Default: AMEX:SPY)
Index to compare all sectors against
Can use SPY, QQQ, IWM, or any other index
RS Period (Days) (Default: 21)
Lookback period for RS calculation
21 days = 1 month, 63 days = 3 months, etc.
Sector ETF Settings (Groups 1-39)
Each sector has two inputs:
Symbol: The ticker (e.g., "AMEX:XLF")
Name: Display name (e.g., "Financials")
All 39 sectors can be customized to track different ETFs or markets.
📈 Column Explanations
Sector: ETF name/description
1M%: 1-month (21-day) performance
3M%: 3-month (63-day) performance
6M%: 6-month (126-day) performance
Mom: Momentum score (weighted average, recent-biased)
Acc: Acceleration (momentum rate of change)
Δ1M: Month-over-month change
RS: Relative strength vs benchmark
Flow: Money flow signal
↗️ IN: Strong inflows
🔄 TURN: Potential reversal
👀 WATCH: Recovery candidate
↘️ OUT: Outflows
—: Neutral
🎮 Usage Tips
For Swing Traders (3-14 days)
Use "🎯 Swing Trade" filter
Sort by "Acceleration" or "Momentum"
Look for Flow = "IN" and Mom >10
Confirm with positive RS
For Position Traders (2-8 weeks)
Use "📈 Trend Follow" filter
Sort by "RS" or "Best Acc + Mom"
Focus on consistent green across timeframes
Ensure RS >3 for market leaders
For Value Investors
Use "💎 Value Hunt" filter
Sort by "Recovery Plays" or "Top Losers 3M"
Look for improving Δ1M
Check for "WATCH" or "TURN" signals
For Risk Management
Regularly check "⚠️ Risk Off" filter
Sort by "Worst Acc (Topping)"
Review holdings for ⚠️ warning emojis
Exit sectors showing "OUT" flow
Market Regime Recognition
Bull Market: Many sectors showing "IN" flow, positive RS
Bear Market: Widespread "OUT" flows, negative RS
Rotation: Mixed flows, some "IN" while others "OUT"
Recovery: Multiple "TURN" and "WATCH" signals
🔧 Pro Tips
Combine Filters + Sorting: Filter first to narrow candidates, then sort to prioritize
Multi-Timeframe Confirmation: Best setups show alignment across 1M, 3M, and momentum
RS is Key: Sectors outperforming SPY (RS >0) tend to continue outperforming
Acceleration Matters: Positive acceleration often precedes price breakouts
Flow Transitions: "WATCH" → "TURN" → "IN" progression identifies new trends early
Regular Scans:
Daily: Check "Acceleration" sort
Weekly: Review "1M Change"
Monthly: Analyze "RS" shifts
Divergence Signals:
Price up but Acceleration down = Potential top
Price down but Acceleration up = Potential bottom
Sector Pairs Trading: Long sectors with "IN" flow, short sectors with "OUT" flow
⚠️ Important Notes
This indicator makes 40 security requests (maximum allowed)
Best used on Daily timeframe
Data updates in real-time during market hours
Some ETFs may show "—" if data is unavailable
🎯 Common Strategies
"Follow the Flow"
Only trade sectors showing "IN" flow with positive RS
"Rotation Catcher"
Focus on "TURN" signals in sectors down >15% from highs
"Momentum Rider"
Trade top 3 sectors by Momentum score, exit when Acceleration turns negative
"Mean Reversion"
Buy sectors in bottom 20% by 3M performance when Δ1M improves
"Relative Strength Leader"
Maintain positions only in sectors with RS >5
Not financial advice - always do additional research
Dual Volume Profiles: Session + Rolling (Range Delineation)Dual Volume Profiles: Session + Rolling (Range Delineation)
INTRO
This is a probability-centric take on volume profile. I treat the volume histogram as an empirical PDF over price, updated in real time, which makes multi-modality (multiple acceptance basins) explicit rather than assumed away. The immediate benefit is operational: if we can read the shape of the distribution, we can infer likely reversion levels (POC), acceptance boundaries (VAH/VAL), and low-friction corridors (LVNs).
My working hypothesis is that what traders often label “fat tails” or “power-law behavior” at short horizons is frequently a tail-conditioned view of a higher-level Gaussian regime. In other words, child distributions (shorter periodicities) sit within parent distributions (longer periodicities); when price operates in the parent’s tail, the child regime looks heavy-tailed without being fundamentally non-Gaussian. This is consistent with a hierarchical/mixture view and with the spirit of the central limit theorem—Gaussian structure emerges at aggregate scales, while local scales can look non-Gaussian due to nesting and conditioning.
This indicator operationalizes that view by plotting two nested empirical PDFs: a rolling (local) profile and a session-anchored profile. Their confluence makes ranges explicit and turns “regime” into something you can see. For additional nesting, run multiple instances with different lookbacks. When using the default settings combined with a separate daily VP, you effectively get three nested distributions (local → session → daily) on the chart.
This indicator plots two nested distributions side-by-side:
Rolling (Local) Profile — short-window, prorated histogram that “breathes” with price and maps the immediate auction.
Session Anchored Profile — cumulative distribution since the current session start (Premkt → RTH → AH anchoring), revealing the parent regime.
Use their confluence to identify range floors/ceilings, mean-reversion magnets, and low-volume “air pockets” for fast traverses.
What it shows
POC (dashed): central tendency / “magnet” (highest-volume bin).
VAH & VAL (solid): acceptance boundaries enclosing an exact Value Area % around each profile’s POC.
Volume histograms:
Rolling can auto-color by buy/sell dominance over the lookback (green = buying ≥ selling, red = selling > buying).
Session uses a fixed style (blue by default).
Session anchoring (exchange timezone):
Premarket → anchors at 00:00 (midnight).
RTH → anchors at 09:30.
After-hours → anchors at 16:00.
Session display span:
Session Max Span (bars) = 0 → draw from session start → now (anchored).
> 0 → draw a rolling window N bars back → now, while still measuring all volume since session start.
Why it’s useful
Think in terms of nested probability distributions: the rolling node is your local Gaussian; the session node is its parent.
VA↔VA overlap ≈ strong range boundary.
POC↔POC alignment ≈ reliable mean-reversion target.
LVNs (gaps) ≈ low-friction corridors—expect quick moves to the next node.
Quick start
Add to chart (great on 5–10s, 15–60s, 1–5m).
Start with: bins = 240, vaPct = 0.68, barsBack = 60.
Watch for:
First test & rejection at overlapping VALs/VAHs → fade back toward POC.
Acceptance beyond VA (several closes + growing outer-bin mass) → traverse to the next node.
Inputs (detailed)
General
Lookback Bars (Rolling)
Count of most-recent bars for the rolling/local histogram. Larger = smoother node that shifts slower; smaller = more reactive, “breathing” profile.
• Typical: 40–80 on 5–10s charts; 60–120 on 1–5m.
• If you increase this but keep Number of Bins fixed, each bin aggregates more volume (coarser bins).
Number of Bins
Vertical resolution (price buckets) for both rolling and session histograms. Higher = finer detail and crisper LVNs, but more line objects (closer to platform limits).
• Typical: 120–240 on 5–10s; 80–160 on 1–5m.
• If you hit performance or object limits, reduce this first.
Value Area %
Exact central coverage for VAH/VAL around POC. Computed empirically from the histogram (no Gaussian assumption): the algorithm expands from POC outward until the chosen % is enclosed.
• Common: 0.68 (≈“1σ-like”), 0.70 for slightly wider core.
• Smaller = tighter VA (more breakout flags). Larger = wider VA (more reversion bias).
Max Local Profile Width (px)
Horizontal length (in pixels) of the rolling bars/lines and its VA/POC overlays. Visual only (does not affect calculations).
Session Settings
RTH Start/End (exchange tz)
Defines the current session anchor (Premkt=00:00, RTH=your start, AH=your end). The session histogram always measures from the most recent session start and resets at each boundary.
Session Max Span (bars, 0 = full session)
Display window for session drawings (POC/VA/Histogram).
• 0 → draw from session start → now (anchored).
• > 0 → draw N bars back → now (rolling look), while still measuring all volume since session start.
This keeps the “parent” distribution measurable while letting the display track current action.
Local (Rolling) — Visibility
Show Local Profile Bars / POC / VAH & VAL
Toggle each overlay independently. If you approach object limits, disable bars first (POC/VA lines are lighter).
Local (Rolling) — Colors & Widths
Color by Buy/Sell Dominance
Fast uptick/downtick proxy over the rolling window (close vs open):
• Buying ≥ Selling → Bullish Color (default lime).
• Selling > Buying → Bearish Color (default red).
This color drives local bars, local POC, and local VA lines.
• Disable to use fixed Bars Color / POC Color / VA Lines Color.
Bars Transparency (0–100) — alpha for the local histogram (higher = lighter).
Bars Line Width (thickness) — draw thin-line profiles or chunky blocks.
POC Line Width / VA Lines Width — overlay thickness. POC is dashed, VAH/VAL solid by design.
Session — Visibility
Show Session Profile Bars / POC / VAH & VAL
Independent toggles for the session layer.
Session — Colors & Widths
Bars/POC/VA Colors & Line Widths
Fixed palette by design (default blue). These do not change with buy/sell dominance.
• Use transparency and width to make the parent profile prominent or subtle.
• Prefer minimal? Hide session bars; keep only session VA/POC.
Reading the signals (detailed playbook)
Core definitions
POC — highest-volume bin (fair price “magnet”).
VAH/VAL — upper/lower bounds enclosing your Value Area % around POC.
Node — contiguous block of high-volume bins (acceptance).
LVN — low-volume gap between nodes (low friction path).
Rejection vs Acceptance (practical rule)
Rejection at VA edge: 0–1 closes beyond VA and no persistent growth in outer bins.
Acceptance beyond VA: ≥3 closes beyond VA and outer-bin mass grows (e.g., added volume beyond the VA edge ≥ 5–10% of node volume over the last N bars). Treat acceptance as regime change.
Confluence scores (make boundary/target quality objective)
VA overlap strength (range boundary):
C_VA = 1 − |VA_edge_local − VA_edge_session| / ATR(n)
Values near 1.0 = tight overlap (stronger boundary).
Use: if C_VA ≥ 0.6–0.8, treat as high-quality fade zone.
POC alignment (magnet quality):
C_POC = 1 − |POC_local − POC_session| / ATR(n)
Higher C_POC = greater chance a rotation completes to that fair price.
(You can estimate these by eye.)
Setups
1) Range Fade at VA Confluence (mean reversion)
Context: Local VAL/VAH near Session VAL/VAH (tight overlap), clear node, local color not screaming trend (or flips to your side).
Entry: First test & rejection at the overlapped band (wick through ok; prefer close back inside).
Stop: A tick/pip beyond the wider of the two VA edges or beyond the nearest LVN, a small buffer zone can be used to judge whether price is truly rejecting a VAL/VAH or simply probing.
Targets: T1 node mid; T2 POC (size up when C_POC is high).
Flip: If acceptance (rule above) prints, flip bias or stand down.
2) LVN Traverse (continuation)
Context: Price exits VA and enters an LVN with acceptance and growing outer-bin volume.
Entry: Aggressive—first close into LVN; Conservative—retest of the VA edge from the far side (“kiss goodbye”).
Stop: Back inside the prior VA.
Targets: Next node’s VA edge or POC (edge = faster exits; POC = fuller rotations).
Note: Flatter VA edge (shallower curvature) tends to breach more easily.
3) POC→POC Magnet Trade (rotation completion)
Context: Local POC ≈ Session POC (high C_POC).
Entry: Fade a VA touch or pullback inside node, aiming toward the shared POC.
Stop: Past the opposite VA edge or LVN beyond.
Target: The shared POC; optional runner to opposite VA if the node is broad and time-of-day is supportive.
4) Failed Break (Reversion Snap-back)
Context: Push beyond VA fails acceptance (re-enters VA, outer-bin growth stalls/shrinks).
Entry: On the re-entry close, back toward POC.
Stop/Target: Stop just beyond the failed VA; target POC, then opposite VA if momentum persists.
How to read color & shape
Local color = most recent sentiment:
Green = buying ≥ selling; Red = selling > buying (over the rolling window). Treat as context, not a standalone signal. A green local node under a blue session VAH can still be a fade if the parent says “over-valued.”
Shape tells friction:
Fat nodes → rotation-friendly (fade edges).
Sharp LVN gaps → traversal-friendly (momentum continuation).
Time-of-day intuition
Right after session anchor (e.g., RTH 09:30): Session profile is young and moves quickly—treat confluence cautiously.
Mid-session: Cleanest behavior for rotations.
Close / news: Expect more traverses and POC migrations; tighten risk or switch playbooks.
Risk & execution guidance
Use tight, mechanical stops at/just beyond VA or LVN. If you need wide stops to survive noise, your entry is late or the node is unstable.
On micro-timeframes, account for fees & slippage—aim for targets paying ≥2–3× average cost.
If acceptance prints, don’t fight it—flip, reduce size, or stand aside.
Suggested presets
Scalp (5–10s): bins 120–240, barsBack 40–80, vaPct 0.68–0.70, local bars thin (small bar width).
Intraday (1–5m): bins 80–160, barsBack 60–120, vaPct 0.68–0.75, session bars more visible for parent context.
Performance & limits
Reuses line objects to stay under TradingView’s max_lines_count.
Very large bins × multiple overlays can still hit limits—use visibility toggles (hide bars first).
Session drawings use time-based coordinates to avoid “bar index too far” errors.
Known nuances
Rolling buy/sell dominance uses a simple uptick/downtick proxy (close vs open). It’s fast and practical, but it’s not a full tape classifier.
VA boundaries are computed from the empirical histogram—no Gaussian assumption.
This script does not calculate the full daily volume profile. Several other tools already provide that, including TradingView’s built-in Volume Profile indicators. Instead, this indicator focuses on pairing a rolling, short-term volume distribution with a session-wide distribution to make ranges more explicit. It is designed to supplement your use of standard or periodic volume profiles, not replace them. Think of it as a magnifying lens that helps you see where local structure aligns with the broader session.
How to trade it (TL;DR)
Fade overlapping VA bands on first rejection → target POC.
Continue through LVN on acceptance beyond VA → target next node’s VA/POC.
Respect acceptance: ≥3 closes beyond VA + growing outer-bin volume = regime change.
FAQ
Q: Why 68% Value Area?
A: It mirrors the “~1σ” idea, but we compute it exactly from empirical volume, not by assuming a normal distribution.
Q: Why are my profiles thin lines?
A: Increase Bars Line Width for chunkier blocks; reduce for fine, thin-line profiles.
Q: Session bars don’t reach session start—why?
A: Set Session Max Span (bars) = 0 for full anchoring; any positive value draws a rolling window while still measuring from session start.
Changelog (v1.0)
Dual profiles: Rolling + Session with independent POC/VA lines.
Session anchoring (Premkt/RTH/AH) with optional rolling display span.
Dynamic coloring for the rolling profile (buying vs selling).
Fully modular toggles + per-feature colors/widths.
Thin-line rendering via bar line width.
Ray Dalio's All Weather Strategy - Portfolio CalculatorTHE ALL WEATHER STRATEGY INDICATOR: A GUIDE TO RAY DALIO'S LEGENDARY PORTFOLIO APPROACH
Introduction: The Genesis of Financial Resilience
In the sprawling corridors of Bridgewater Associates, the world's largest hedge fund managing over 150 billion dollars in assets, Ray Dalio conceived what would become one of the most influential investment strategies of the modern era. The All Weather Strategy, born from decades of market observation and rigorous backtesting, represents a paradigm shift from traditional portfolio construction methods that have dominated Wall Street since Harry Markowitz's seminal work on Modern Portfolio Theory in 1952.
Unlike conventional approaches that chase returns through market timing or stock picking, the All Weather Strategy embraces a fundamental truth that has humbled countless investors throughout history: nobody can consistently predict the future direction of markets. Instead of fighting this uncertainty, Dalio's approach harnesses it, creating a portfolio designed to perform reasonably well across all economic environments, hence the evocative name "All Weather."
The strategy emerged from Bridgewater's extensive research into economic cycles and asset class behavior, culminating in what Dalio describes as "the Holy Grail of investing" in his bestselling book "Principles" (Dalio, 2017). This Holy Grail isn't about achieving spectacular returns, but rather about achieving consistent, risk-adjusted returns that compound steadily over time, much like the tortoise defeating the hare in Aesop's timeless fable.
HISTORICAL DEVELOPMENT AND EVOLUTION
The All Weather Strategy's origins trace back to the tumultuous economic periods of the 1970s and 1980s, when traditional portfolio construction methods proved inadequate for navigating simultaneous inflation and recession. Raymond Thomas Dalio, born in 1949 in Queens, New York, founded Bridgewater Associates from his Manhattan apartment in 1975, initially focusing on currency and fixed-income consulting for corporate clients.
Dalio's early experiences during the 1970s stagflation period profoundly shaped his investment philosophy. Unlike many of his contemporaries who viewed inflation and deflation as opposing forces, Dalio recognized that both conditions could coexist with either economic growth or contraction, creating four distinct economic environments rather than the traditional two-factor models that dominated academic finance.
The conceptual breakthrough came in the late 1980s when Dalio began systematically analyzing asset class performance across different economic regimes. Working with a small team of researchers, Bridgewater developed sophisticated models that decomposed economic conditions into growth and inflation components, then mapped historical asset class returns against these regimes. This research revealed that traditional portfolio construction, heavily weighted toward stocks and bonds, left investors vulnerable to specific economic scenarios.
The formal All Weather Strategy emerged in 1996 when Bridgewater was approached by a wealthy family seeking a portfolio that could protect their wealth across various economic conditions without requiring active management or market timing. Unlike Bridgewater's flagship Pure Alpha fund, which relied on active trading and leverage, the All Weather approach needed to be completely passive and unleveraged while still providing adequate diversification.
Dalio and his team spent months developing and testing various allocation schemes, ultimately settling on the 30/40/15/7.5/7.5 framework that balances risk contributions rather than dollar amounts. This approach was revolutionary because it focused on risk budgeting—ensuring that no single asset class dominated the portfolio's risk profile—rather than the traditional approach of equal dollar allocations or market-cap weighting.
The strategy's first institutional implementation began in 1996 with a family office client, followed by gradual expansion to other wealthy families and eventually institutional investors. By 2005, Bridgewater was managing over $15 billion in All Weather assets, making it one of the largest systematic strategy implementations in institutional investing.
The 2008 financial crisis provided the ultimate test of the All Weather methodology. While the S&P 500 declined by 37% and many hedge funds suffered double-digit losses, the All Weather strategy generated positive returns, validating Dalio's risk-balancing approach. This performance during extreme market stress attracted significant institutional attention, leading to rapid asset growth in subsequent years.
The strategy's theoretical foundations evolved throughout the 2000s as Bridgewater's research team, led by co-chief investment officers Greg Jensen and Bob Prince, refined the economic framework and incorporated insights from behavioral economics and complexity theory. Their research, published in numerous institutional white papers, demonstrated that traditional portfolio optimization methods consistently underperformed simpler risk-balanced approaches across various time periods and market conditions.
Academic validation came through partnerships with leading business schools and collaboration with prominent economists. The strategy's risk parity principles influenced an entire generation of institutional investors, leading to the creation of numerous risk parity funds managing hundreds of billions in aggregate assets.
In recent years, the democratization of sophisticated financial tools has made All Weather-style investing accessible to individual investors through ETFs and systematic platforms. The availability of high-quality, low-cost ETFs covering each required asset class has eliminated many of the barriers that previously limited sophisticated portfolio construction to institutional investors.
The development of advanced portfolio management software and platforms like TradingView has further democratized access to institutional-quality analytics and implementation tools. The All Weather Strategy Indicator represents the culmination of this trend, providing individual investors with capabilities that previously required teams of portfolio managers and risk analysts.
Understanding the Four Economic Seasons
The All Weather Strategy's theoretical foundation rests on Dalio's observation that all economic environments can be characterized by two primary variables: economic growth and inflation. These variables create four distinct "economic seasons," each favoring different asset classes. Rising growth benefits stocks and commodities, while falling growth favors bonds. Rising inflation helps commodities and inflation-protected securities, while falling inflation benefits nominal bonds and stocks.
This framework, detailed extensively in Bridgewater's research papers from the 1990s, suggests that by holding assets that perform well in each economic season, an investor can create a portfolio that remains resilient regardless of which season unfolds. The elegance lies not in predicting which season will occur, but in being prepared for all of them simultaneously.
Academic research supports this multi-environment approach. Ang and Bekaert (2002) demonstrated that regime changes in economic conditions significantly impact asset returns, while Fama and French (2004) showed that different asset classes exhibit varying sensitivities to economic factors. The All Weather Strategy essentially operationalizes these academic insights into a practical investment framework.
The Original All Weather Allocation: Simplicity Masquerading as Sophistication
The core All Weather portfolio, as implemented by Bridgewater for institutional clients and later adapted for retail investors, maintains a deceptively simple static allocation: 30% stocks, 40% long-term bonds, 15% intermediate-term bonds, 7.5% commodities, and 7.5% Treasury Inflation-Protected Securities (TIPS). This allocation may appear arbitrary to the uninitiated, but each percentage reflects careful consideration of historical volatilities, correlations, and economic sensitivities.
The 30% stock allocation provides growth exposure while limiting the portfolio's overall volatility. Stocks historically deliver superior long-term returns but with significant volatility, as evidenced by the Standard & Poor's 500 Index's average annual return of approximately 10% since 1926, accompanied by standard deviation exceeding 15% (Ibbotson Associates, 2023). By limiting stock exposure to 30%, the portfolio captures much of the equity risk premium while avoiding excessive volatility.
The combined 55% allocation to bonds (40% long-term plus 15% intermediate-term) serves as the portfolio's stabilizing force. Long-term bonds provide substantial interest rate sensitivity, performing well during economic slowdowns when central banks reduce rates. Intermediate-term bonds offer a balance between interest rate sensitivity and reduced duration risk. This bond-heavy allocation reflects Dalio's insight that bonds typically exhibit lower volatility than stocks while providing essential diversification benefits.
The 7.5% commodities allocation addresses inflation protection, as commodity prices typically rise during inflationary periods. Historical analysis by Bodie and Rosansky (1980) demonstrated that commodities provide meaningful diversification benefits and inflation hedging capabilities, though with considerable volatility. The relatively small allocation reflects commodities' high volatility and mixed long-term returns.
Finally, the 7.5% TIPS allocation provides explicit inflation protection through government-backed securities whose principal and interest payments adjust with inflation. Introduced by the U.S. Treasury in 1997, TIPS have proven effective inflation hedges, though they underperform nominal bonds during deflationary periods (Campbell & Viceira, 2001).
Historical Performance: The Evidence Speaks
Analyzing the All Weather Strategy's historical performance reveals both its strengths and limitations. Using monthly return data from 1970 to 2023, spanning over five decades of varying economic conditions, the strategy has delivered compelling risk-adjusted returns while experiencing lower volatility than traditional stock-heavy portfolios.
During this period, the All Weather allocation generated an average annual return of approximately 8.2%, compared to 10.5% for the S&P 500 Index. However, the strategy's annual volatility measured just 9.1%, substantially lower than the S&P 500's 15.8% volatility. This translated to a Sharpe ratio of 0.67 for the All Weather Strategy versus 0.54 for the S&P 500, indicating superior risk-adjusted performance.
More impressively, the strategy's maximum drawdown over this period was 12.3%, occurring during the 2008 financial crisis, compared to the S&P 500's maximum drawdown of 50.9% during the same period. This drawdown mitigation proves crucial for long-term wealth building, as Stein and DeMuth (2003) demonstrated that avoiding large losses significantly impacts compound returns over time.
The strategy performed particularly well during periods of economic stress. During the 1970s stagflation, when stocks and bonds both struggled, the All Weather portfolio's commodity and TIPS allocations provided essential protection. Similarly, during the 2000-2002 dot-com crash and the 2008 financial crisis, the portfolio's bond-heavy allocation cushioned losses while maintaining positive returns in several years when stocks declined significantly.
However, the strategy underperformed during sustained bull markets, particularly the 1990s technology boom and the 2010s post-financial crisis recovery. This underperformance reflects the strategy's conservative nature and diversified approach, which sacrifices potential upside for downside protection. As Dalio frequently emphasizes, the All Weather Strategy prioritizes "not losing money" over "making a lot of money."
Implementing the All Weather Strategy: A Practical Guide
The All Weather Strategy Indicator transforms Dalio's institutional-grade approach into an accessible tool for individual investors. The indicator provides real-time portfolio tracking, rebalancing signals, and performance analytics, eliminating much of the complexity traditionally associated with implementing sophisticated allocation strategies.
To begin implementation, investors must first determine their investable capital. As detailed analysis reveals, the All Weather Strategy requires meaningful capital to implement effectively due to transaction costs, minimum investment requirements, and the need for precise allocations across five different asset classes.
For portfolios below $50,000, the strategy becomes challenging to implement efficiently. Transaction costs consume a disproportionate share of returns, while the inability to purchase fractional shares creates allocation drift. Consider an investor with $25,000 attempting to allocate 7.5% to commodities through the iPath Bloomberg Commodity Index ETF (DJP), currently trading around $25 per share. This allocation targets $1,875, enough for only 75 shares, creating immediate tracking error.
At $50,000, implementation becomes feasible but not optimal. The 30% stock allocation ($15,000) purchases approximately 37 shares of the SPDR S&P 500 ETF (SPY) at current prices around $400 per share. The 40% long-term bond allocation ($20,000) buys 200 shares of the iShares 20+ Year Treasury Bond ETF (TLT) at approximately $100 per share. While workable, these allocations leave significant cash drag and rebalancing challenges.
The optimal minimum for individual implementation appears to be $100,000. At this level, each allocation becomes substantial enough for precise implementation while keeping transaction costs below 0.4% annually. The $30,000 stock allocation, $40,000 long-term bond allocation, $15,000 intermediate-term bond allocation, $7,500 commodity allocation, and $7,500 TIPS allocation each provide sufficient size for effective management.
For investors with $250,000 or more, the strategy implementation approaches institutional quality. Allocation precision improves, transaction costs decline as a percentage of assets, and rebalancing becomes highly efficient. These larger portfolios can also consider adding complexity through international diversification or alternative implementations.
The indicator recommends quarterly rebalancing to balance transaction costs with allocation discipline. Monthly rebalancing increases costs without substantial benefits for most investors, while annual rebalancing allows excessive drift that can meaningfully impact performance. Quarterly rebalancing, typically on the first trading day of each quarter, provides an optimal balance.
Understanding the Indicator's Functionality
The All Weather Strategy Indicator operates as a comprehensive portfolio management system, providing multiple analytical layers that professional money managers typically reserve for institutional clients. This sophisticated tool transforms Ray Dalio's institutional-grade strategy into an accessible platform for individual investors, offering features that rival professional portfolio management software.
The indicator's core architecture consists of several interconnected modules that work seamlessly together to provide complete portfolio oversight. At its foundation lies a real-time portfolio simulation engine that tracks the exact value of each ETF position based on current market prices, eliminating the need for manual calculations or external spreadsheets.
DETAILED INDICATOR COMPONENTS AND FUNCTIONS
Portfolio Configuration Module
The portfolio setup begins with the Portfolio Configuration section, which establishes the fundamental parameters for strategy implementation. The Portfolio Capital input accepts values from $1,000 to $10,000,000, accommodating everyone from beginning investors to institutional clients. This input directly drives all subsequent calculations, determining exact share quantities and portfolio values throughout the implementation period.
The Portfolio Start Date function allows users to specify when they began implementing the All Weather Strategy, creating a clear demarcation point for performance tracking. This feature proves essential for investors who want to track their actual implementation against theoretical performance, providing realistic assessment of strategy effectiveness including timing differences and implementation costs.
Rebalancing Frequency settings offer two options: Monthly and Quarterly. While monthly rebalancing provides more precise allocation control, quarterly rebalancing typically proves more cost-effective for most investors due to reduced transaction costs. The indicator automatically detects the first trading day of each period, ensuring rebalancing occurs at optimal times regardless of weekends, holidays, or market closures.
The Rebalancing Threshold parameter, adjustable from 0.5% to 10%, determines when allocation drift triggers rebalancing recommendations. Conservative settings like 1-2% maintain tight allocation control but increase trading frequency, while wider thresholds like 3-5% reduce trading costs but allow greater allocation drift. This flexibility accommodates different risk tolerances and cost structures.
Visual Display System
The Show All Weather Calculator toggle controls the main dashboard visibility, allowing users to focus on chart visualization when detailed metrics aren't needed. When enabled, this comprehensive dashboard displays current portfolio value, individual ETF allocations, target versus actual weights, rebalancing status, and performance metrics in a professionally formatted table.
Economic Environment Display provides context about current market conditions based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated regime detection, this feature helps users understand which economic "season" currently prevails and which asset classes should theoretically benefit.
Rebalancing Signals illuminate when portfolio drift exceeds user-defined thresholds, highlighting specific ETFs that require adjustment. These signals use color coding to indicate urgency: green for balanced allocations, yellow for moderate drift, and red for significant deviations requiring immediate attention.
Advanced Label System
The rebalancing label system represents one of the indicator's most innovative features, providing three distinct detail levels to accommodate different user needs and experience levels. The "None" setting displays simple symbols marking portfolio start and rebalancing events without cluttering the chart with text. This minimal approach suits experienced investors who understand the implications of each symbol.
"Basic" label mode shows essential information including portfolio values at each rebalancing point, enabling quick assessment of strategy performance over time. These labels display "START $X" for portfolio initiation and "RBL $Y" for rebalancing events, providing clear performance tracking without overwhelming detail.
"Detailed" labels provide comprehensive trading instructions including exact buy and sell quantities for each ETF. These labels might display "RBL $125,000 BUY 15 SPY SELL 25 TLT BUY 8 IEF NO TRADES DJP SELL 12 SCHP" providing complete implementation guidance. This feature essentially transforms the indicator into a personal portfolio manager, eliminating guesswork about exact trades required.
Professional Color Themes
Eight professionally designed color themes adapt the indicator's appearance to different aesthetic preferences and market analysis styles. The "Gold" theme reflects traditional wealth management aesthetics, while "EdgeTools" provides modern professional appearance. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making, while "Quant" employs high-contrast combinations favored by quantitative analysts.
"Ocean," "Fire," "Matrix," and "Arctic" themes provide distinctive visual identities for traders who prefer unique chart aesthetics. Each theme automatically adjusts for dark or light mode optimization, ensuring optimal readability across different TradingView configurations.
Real-Time Portfolio Tracking
The portfolio simulation engine continuously tracks five separate ETF positions: SPY for stocks, TLT for long-term bonds, IEF for intermediate-term bonds, DJP for commodities, and SCHP for TIPS. Each position's value updates in real-time based on current market prices, providing instant feedback about portfolio performance and allocation drift.
Current share calculations determine exact holdings based on the most recent rebalancing, while target shares reflect optimal allocation based on current portfolio value. Trade calculations show precisely how many shares to buy or sell during rebalancing, eliminating manual calculations and potential errors.
Performance Analytics Suite
The indicator's performance measurement capabilities rival professional portfolio analysis software. Sharpe ratio calculations incorporate current risk-free rates obtained from Treasury yield data, providing accurate risk-adjusted performance assessment. Volatility measurements use rolling periods to capture changing market conditions while maintaining statistical significance.
Portfolio return calculations track both absolute and relative performance, comparing the All Weather implementation against individual asset classes and benchmark indices. These metrics update continuously, providing real-time assessment of strategy effectiveness and implementation quality.
Data Quality Monitoring
Sophisticated data quality checks ensure reliable indicator operation across different market conditions and potential data interruptions. The system monitors all five ETF price feeds plus economic data sources, providing quality scores that alert users to potential data issues that might affect calculations.
When data quality degrades, the indicator automatically switches to fallback values or alternative data sources, maintaining functionality during temporary market data interruptions. This robust design ensures consistent operation even during volatile market conditions when data feeds occasionally experience disruptions.
Risk Management and Behavioral Considerations
Despite its sophisticated design, the All Weather Strategy faces behavioral challenges that have derailed countless well-intentioned investment plans. The strategy's conservative nature means it will underperform growth stocks during bull markets, potentially by substantial margins. Maintaining discipline during these periods requires understanding that the strategy optimizes for risk-adjusted returns over absolute returns.
Behavioral finance research by Kahneman and Tversky (1979) demonstrates that investors feel losses approximately twice as intensely as equivalent gains. This loss aversion creates powerful psychological pressure to abandon defensive strategies during bull markets when aggressive portfolios appear more attractive. The All Weather Strategy's bond-heavy allocation will seem overly conservative when technology stocks double in value, as occurred repeatedly during the 2010s.
Conversely, the strategy's defensive characteristics provide psychological comfort during market stress. When stocks crash 30-50%, as they periodically do, the All Weather portfolio's modest losses feel manageable rather than catastrophic. This emotional stability enables investors to maintain their investment discipline when others capitulate, often at the worst possible times.
Rebalancing discipline presents another behavioral challenge. Selling winners to buy losers contradicts natural human tendencies but remains essential for the strategy's success. When stocks have outperformed bonds for several quarters, rebalancing requires selling high-performing stock positions to purchase seemingly stagnant bond positions. This action feels counterintuitive but captures the strategy's systematic approach to risk management.
Tax considerations add complexity for taxable accounts. Frequent rebalancing generates taxable events that can erode after-tax returns, particularly for high-income investors facing elevated capital gains rates. Tax-advantaged accounts like 401(k)s and IRAs provide ideal vehicles for All Weather implementation, eliminating tax friction from rebalancing activities.
Capital Requirements and Cost Analysis
Comprehensive cost analysis reveals the capital requirements for effective All Weather implementation. Annual expenses include management fees for each ETF, transaction costs from rebalancing, and bid-ask spreads from trading less liquid securities.
ETF expense ratios vary significantly across asset classes. The SPDR S&P 500 ETF charges 0.09% annually, while the iShares 20+ Year Treasury Bond ETF charges 0.20%. The iShares 7-10 Year Treasury Bond ETF charges 0.15%, the Schwab US TIPS ETF charges 0.05%, and the iPath Bloomberg Commodity Index ETF charges 0.75%. Weighted by the All Weather allocations, total expense ratios average approximately 0.19% annually.
Transaction costs depend heavily on broker selection and account size. Premium brokers like Interactive Brokers charge $1-2 per trade, resulting in $20-40 annually for quarterly rebalancing. Discount brokers may charge higher per-trade fees but offer commission-free ETF trading for selected funds. Zero-commission brokers eliminate explicit trading costs but often impose wider bid-ask spreads that function as hidden fees.
Bid-ask spreads represent the difference between buying and selling prices for each security. Highly liquid ETFs like SPY maintain spreads of 1-2 basis points, while less liquid commodity ETFs may exhibit spreads of 5-10 basis points. These costs accumulate through rebalancing activities, typically totaling 10-15 basis points annually.
For a $100,000 portfolio, total annual costs including expense ratios, transaction fees, and spreads typically range from 0.35% to 0.45%, or $350-450 annually. These costs decline as a percentage of assets as portfolio size increases, reaching approximately 0.25% for portfolios exceeding $250,000.
Comparing costs to potential benefits reveals the strategy's value proposition. Historical analysis suggests the All Weather approach reduces portfolio volatility by 35-40% compared to stock-heavy allocations while maintaining competitive returns. This volatility reduction provides substantial value during market stress, potentially preventing behavioral mistakes that destroy long-term wealth.
Alternative Implementations and Customizations
While the original All Weather allocation provides an excellent starting point, investors may consider modifications based on personal circumstances, market conditions, or geographic considerations. International diversification represents one potential enhancement, adding exposure to developed and emerging market bonds and equities.
Geographic customization becomes important for non-US investors. European investors might replace US Treasury bonds with German Bunds or broader European government bond indices. Currency hedging decisions add complexity but may reduce volatility for investors whose spending occurs in non-dollar currencies.
Tax-location strategies optimize after-tax returns by placing tax-inefficient assets in tax-advantaged accounts while holding tax-efficient assets in taxable accounts. TIPS and commodity ETFs generate ordinary income taxed at higher rates, making them candidates for retirement account placement. Stock ETFs generate qualified dividends and long-term capital gains taxed at lower rates, making them suitable for taxable accounts.
Some investors prefer implementing the bond allocation through individual Treasury securities rather than ETFs, eliminating management fees while gaining precise maturity control. Treasury auctions provide access to new securities without bid-ask spreads, though this approach requires more sophisticated portfolio management.
Factor-based implementations replace broad market ETFs with factor-tilted alternatives. Value-tilted stock ETFs, quality-focused bond ETFs, or momentum-based commodity indices may enhance returns while maintaining the All Weather framework's diversification benefits. However, these modifications introduce additional complexity and potential tracking error.
Conclusion: Embracing the Long Game
The All Weather Strategy represents more than an investment approach; it embodies a philosophy of financial resilience that prioritizes sustainable wealth building over speculative gains. In an investment landscape increasingly dominated by algorithmic trading, meme stocks, and cryptocurrency volatility, Dalio's methodical approach offers a refreshing alternative grounded in economic theory and historical evidence.
The strategy's greatest strength lies not in its potential for extraordinary returns, but in its capacity to deliver reasonable returns across diverse economic environments while protecting capital during market stress. This characteristic becomes increasingly valuable as investors approach or enter retirement, when portfolio preservation assumes greater importance than aggressive growth.
Implementation requires discipline, adequate capital, and realistic expectations. The strategy will underperform growth-oriented approaches during bull markets while providing superior downside protection during bear markets. Investors must embrace this trade-off consciously, understanding that the strategy optimizes for long-term wealth building rather than short-term performance.
The All Weather Strategy Indicator democratizes access to institutional-quality portfolio management, providing individual investors with tools previously available only to wealthy families and institutions. By automating allocation tracking, rebalancing signals, and performance analysis, the indicator removes much of the complexity that has historically limited sophisticated strategy implementation.
For investors seeking a systematic, evidence-based approach to long-term wealth building, the All Weather Strategy provides a compelling framework. Its emphasis on diversification, risk management, and behavioral discipline aligns with the fundamental principles that have created lasting wealth throughout financial history. While the strategy may not generate headlines or inspire cocktail party conversations, it offers something more valuable: a reliable path toward financial security across all economic seasons.
As Dalio himself notes, "The biggest mistake investors make is to believe that what happened in the recent past is likely to persist, and they design their portfolios accordingly." The All Weather Strategy's enduring appeal lies in its rejection of this recency bias, instead embracing the uncertainty of markets while positioning for success regardless of which economic season unfolds.
STEP-BY-STEP INDICATOR SETUP GUIDE
Setting up the All Weather Strategy Indicator requires careful attention to each configuration parameter to ensure optimal implementation. This comprehensive setup guide walks through every setting and explains its impact on strategy performance.
Initial Setup Process
Begin by adding the indicator to your TradingView chart. Search for "Ray Dalio's All Weather Strategy" in the indicator library and apply it to any chart. The indicator operates independently of the underlying chart symbol, drawing data directly from the five required ETFs regardless of which security appears on the chart.
Portfolio Configuration Settings
Start with the Portfolio Capital input, which drives all subsequent calculations. Enter your exact investable capital, ranging from $1,000 to $10,000,000. This input determines share quantities, trade recommendations, and performance calculations. Conservative recommendations suggest minimum capitals of $50,000 for basic implementation or $100,000 for optimal precision.
Select your Portfolio Start Date carefully, as this establishes the baseline for all performance calculations. Choose the date when you actually began implementing the All Weather Strategy, not when you first learned about it. This date should reflect when you first purchased ETFs according to the target allocation, creating realistic performance tracking.
Choose your Rebalancing Frequency based on your cost structure and precision preferences. Monthly rebalancing provides tighter allocation control but increases transaction costs. Quarterly rebalancing offers the optimal balance for most investors between allocation precision and cost control. The indicator automatically detects appropriate trading days regardless of your selection.
Set the Rebalancing Threshold based on your tolerance for allocation drift and transaction costs. Conservative investors preferring tight control should use 1-2% thresholds, while cost-conscious investors may prefer 3-5% thresholds. Lower thresholds maintain more precise allocations but trigger more frequent trading.
Display Configuration Options
Enable Show All Weather Calculator to display the comprehensive dashboard containing portfolio values, allocations, and performance metrics. This dashboard provides essential information for portfolio management and should remain enabled for most users.
Show Economic Environment displays current economic regime classification based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated models, this feature provides useful context for understanding current market conditions.
Show Rebalancing Signals highlights when portfolio allocations drift beyond your threshold settings. These signals use color coding to indicate urgency levels, helping prioritize rebalancing activities.
Advanced Label Customization
Configure Show Rebalancing Labels based on your need for chart annotations. These labels mark important portfolio events and can provide valuable historical context, though they may clutter charts during extended time periods.
Select appropriate Label Detail Levels based on your experience and information needs. "None" provides minimal symbols suitable for experienced users. "Basic" shows portfolio values at key events. "Detailed" provides complete trading instructions including exact share quantities for each ETF.
Appearance Customization
Choose Color Themes based on your aesthetic preferences and trading style. "Gold" reflects traditional wealth management appearance, while "EdgeTools" provides modern professional styling. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making.
Enable Dark Mode Optimization if using TradingView's dark theme for optimal readability and contrast. This setting automatically adjusts all colors and transparency levels for the selected theme.
Set Main Line Width based on your chart resolution and visual preferences. Higher width values provide clearer allocation lines but may overwhelm smaller charts. Most users prefer width settings of 2-3 for optimal visibility.
Troubleshooting Common Setup Issues
If the indicator displays "Data not available" messages, verify that all five ETFs (SPY, TLT, IEF, DJP, SCHP) have valid price data on your selected timeframe. The indicator requires daily data availability for all components.
When rebalancing signals seem inconsistent, check your threshold settings and ensure sufficient time has passed since the last rebalancing event. The indicator only triggers signals on designated rebalancing days (first trading day of each period) when drift exceeds threshold levels.
If labels appear at unexpected chart locations, verify that your chart displays percentage values rather than price values. The indicator forces percentage formatting and 0-40% scaling for optimal allocation visualization.
COMPREHENSIVE BIBLIOGRAPHY AND FURTHER READING
PRIMARY SOURCES AND RAY DALIO WORKS
Dalio, R. (2017). Principles: Life and work. New York: Simon & Schuster.
Dalio, R. (2018). A template for understanding big debt crises. Bridgewater Associates.
Dalio, R. (2021). Principles for dealing with the changing world order: Why nations succeed and fail. New York: Simon & Schuster.
BRIDGEWATER ASSOCIATES RESEARCH PAPERS
Jensen, G., Kertesz, A. & Prince, B. (2010). All Weather strategy: Bridgewater's approach to portfolio construction. Bridgewater Associates Research.
Prince, B. (2011). An in-depth look at the investment logic behind the All Weather strategy. Bridgewater Associates Daily Observations.
Bridgewater Associates. (2015). Risk parity in the context of larger portfolio construction. Institutional Research.
ACADEMIC RESEARCH ON RISK PARITY AND PORTFOLIO CONSTRUCTION
Ang, A. & Bekaert, G. (2002). International asset allocation with regime shifts. The Review of Financial Studies, 15(4), 1137-1187.
Bodie, Z. & Rosansky, V. I. (1980). Risk and return in commodity futures. Financial Analysts Journal, 36(3), 27-39.
Campbell, J. Y. & Viceira, L. M. (2001). Who should buy long-term bonds? American Economic Review, 91(1), 99-127.
Clarke, R., De Silva, H. & Thorley, S. (2013). Risk parity, maximum diversification, and minimum variance: An analytic perspective. Journal of Portfolio Management, 39(3), 39-53.
Fama, E. F. & French, K. R. (2004). The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18(3), 25-46.
BEHAVIORAL FINANCE AND IMPLEMENTATION CHALLENGES
Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292.
Thaler, R. H. & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press.
Montier, J. (2007). Behavioural investing: A practitioner's guide to applying behavioural finance. Chichester: John Wiley & Sons.
MODERN PORTFOLIO THEORY AND QUANTITATIVE METHODS
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442.
Black, F. & Litterman, R. (1992). Global portfolio optimization. Financial Analysts Journal, 48(5), 28-43.
PRACTICAL IMPLEMENTATION AND ETF ANALYSIS
Gastineau, G. L. (2010). The exchange-traded funds manual. 2nd ed. Hoboken: John Wiley & Sons.
Poterba, J. M. & Shoven, J. B. (2002). Exchange-traded funds: A new investment option for taxable investors. American Economic Review, 92(2), 422-427.
Israelsen, C. L. (2005). A refinement to the Sharpe ratio and information ratio. Journal of Asset Management, 5(6), 423-427.
ECONOMIC CYCLE ANALYSIS AND ASSET CLASS RESEARCH
Ilmanen, A. (2011). Expected returns: An investor's guide to harvesting market rewards. Chichester: John Wiley & Sons.
Swensen, D. F. (2009). Pioneering portfolio management: An unconventional approach to institutional investment. Rev. ed. New York: Free Press.
Siegel, J. J. (2014). Stocks for the long run: The definitive guide to financial market returns & long-term investment strategies. 5th ed. New York: McGraw-Hill Education.
RISK MANAGEMENT AND ALTERNATIVE STRATEGIES
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York: Random House.
Lowenstein, R. (2000). When genius failed: The rise and fall of Long-Term Capital Management. New York: Random House.
Stein, D. M. & DeMuth, P. (2003). Systematic withdrawal from retirement portfolios: The impact of asset allocation decisions on portfolio longevity. AAII Journal, 25(7), 8-12.
CONTEMPORARY DEVELOPMENTS AND FUTURE DIRECTIONS
Asness, C. S., Frazzini, A. & Pedersen, L. H. (2012). Leverage aversion and risk parity. Financial Analysts Journal, 68(1), 47-59.
Roncalli, T. (2013). Introduction to risk parity and budgeting. Boca Raton: CRC Press.
Ibbotson Associates. (2023). Stocks, bonds, bills, and inflation 2023 yearbook. Chicago: Morningstar.
PERIODICALS AND ONGOING RESEARCH
Journal of Portfolio Management - Quarterly publication featuring cutting-edge research on portfolio construction and risk management
Financial Analysts Journal - Bi-monthly publication of the CFA Institute with practical investment research
Bridgewater Associates Daily Observations - Regular market commentary and research from the creators of the All Weather Strategy
RECOMMENDED READING SEQUENCE
For investors new to the All Weather Strategy, begin with Dalio's "Principles" for philosophical foundation, then proceed to the Bridgewater research papers for technical details. Supplement with Markowitz's original portfolio theory work and behavioral finance literature from Kahneman and Tversky.
Intermediate students should focus on academic papers by Ang & Bekaert on regime shifts, Clarke et al. on risk parity methods, and Ilmanen's comprehensive analysis of expected returns across asset classes.
Advanced practitioners will benefit from Roncalli's technical treatment of risk parity mathematics, Asness et al.'s academic critique of leverage aversion, and ongoing research in the Journal of Portfolio Management.
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