ROC PercentileRate Of Change Percentile calculates the current ROC (user defined length) as a percentile rank.
We use 2 separate arrays, one for all positive ROC values and one for all negative values within a defined lookback period. Then the current ROC value is compared to those arrays to find it's percentile ranking.
For example, a ranking of 75 means the ROC is in the 75th percentile of all POSITIVE ROC values over the lookback period.
A ranking of -80 is in the 80th percentile of all NEGATIVE ROC values over the lookback period.
Most ROC scripts use raw ROC values (or smoothed or otherwise altered), or have stochastic formula applied to them, I've not seen one that displays ROC as percentile ranking of previous positive/negative values.
What is the advantage?
Raw ROC data only gives half the picture. What we want to do is compare the ROC to previous ROC values, to give a sense of scale. Raw ROC values don't give you that context and you can only compare visually, usually limited to the number of bars you can see on your screen.
Using a percentile ranking gives us the context of current Rate of Change relative to the previous Rate of Change over a large lookback period, and not just visually but mathematically.
Why not using a long stochastic ROC? The problem with stochastics in general is that an outlier data point can ruin the data for the rest of the lookback period.
For example, imagine a huge outlier 8% ROC. The 2nd largest ROC is 4% and the 3rd largest is 2%, with all other values below this.
In this example, a stochastic ROC would display the 8% outlier as 100, the 4% as 50, the 2% as 25 and all other data would be squeezed down between 0-25.
Additionally, a value of 60 may have vastly different meaning depending on whether the lookback period contains a large outlier or not.
With a percentile ranking, that 8% outlier would still have a value of 100. But the 4% and 2% would be 99 and 98 respectively (this assumes 100 data points in the series, in reality values will usually be decimals).
This effectively flattens the curve and gives a more consistent and dependable experience, allowing you to more accurately assess the relative importance of the current ROC.
The line of circles is set at the 50 and -50 values for quick comparison.
Values > 50 represent ROC greater than 50% of previous positive ROC values.
Values < -50 represent ROC greater than 50% of previous negative ROC values.
Pesquisar nos scripts por "北证50+指数成分股"
Bank Zones #PipGangHello Traders,
If you trade Forex and Indices this indicator will help you identify Buying and Selling levels that Banks are interested in. These levels are displayed on all time frames. Colors of the lines can be customized.
I also added code to show two EMA's, just uncomment the code to show them. :-)
How to use this indicator.
Show Bank Zones - this will enable/disable horizonal lines on the chart.
Price - enter bank zone price.
Increment By - plots three horizonal lines in pips above and below bank zone price.
Note: Decimal placement is KEY, this may vary by symbol.
Sample Settings:
US30USD
Price 35600.0
IncrementBy 50 (equals 50 pips)
XAUUSD
Price 1850.000
IncrementBy 5 (equals 50 pips)
GBPJPY
Price 152.500
IncrementBy .5 (equals 50 pips)
GBPUSD
Price 1.34100
IncrementBy .005 (equals 50 pips)
Forex scalper 2xEMA + SRSI + MACDThis is a forex scalping strategy designed for the most liquid pairs, like major forex pairs.
Its made of
1 EMA 50
1 EMA 100
Stochastic RSI
MACD
Rules
For long :close of the candle is above moving average 50, moving average 50> moving average 100, macd histogram is positive and cross over of stochastic rsi with the oversold level.
For short :close of the candle is below moving average 50, moving average 50 < moving average 100, macd histogram is negative and cross under of stochastic rsi with the overbought level.
Exit
For exit we have take profit and stop loss using fixed pip points.
For this example on EURUSD we use 20 pips for both tp and sl
IF you have any questions let me know !
EBB & Flow: a multi-EMA-based BB cloudIntro
This is an idea evolved out of the market maker method and EMA convergence, divergence, and mean reversion.
The market maker method informs us that the 5, 13, 50 and 200 EMAs are important to regulating price. Those EMA lengths are multiples of the 50 and 200 on lower major timeframes -- the 1 minute, 5, 15, 1H, 4H, 1D. I include the 21 because it is also a multiple and in crypto very often respected.
When market makers are testing price, they set their range and spike in the direction they test for liquidity. This can get chaotic. For instance, in a shorter time frame consolidation inside a bigger timeframe uptrend, it can be too easy to forget where you are in the many trends playing out.
When the EMAs are dragged over each other during normal price movement, you get these crisscrossing tracks of price, and the individual breaks can be hard to trace.
The range is what matters, ultimately, and the range is dynamic. In that case, the Bollinger Band is a great tool for detecting outliers in this case.
The Answer
So the answer this indicator seeks to give, is to look for outliers. This gives you a scalping strategy built on Traders Reality thinking and best put together with the PVSRA indicator, which I may include in this indicator just for the sake of concision, but they can work alongside each other or separately.
The key thing is the different EMA clouds, which are bollinger bands. Tight bands mean imminent breaks, favouring the trend. Vector candles out of a zone, pins to the low/high, etc. are all very relevant alongside this indicator.
You can also use it on its own and scalp the breaks of a cloud.
How it works
Each cloud is a standard deviation from their respective EMA, all in the same colour. The deviation multiple is 1.618 by default. Yes, fibonacci sequences are usually nonsense, but it works better with the BB than 2, 2.5 or 3.
Using just the clouds, you can see where each EMA is headed and how it behaves within the deviation of the others.
But that on its own isn't enough.
The indicator will also print snowflakes above and below the candle for notable outliers. It will be in the colour of the cloud it breaks, but only if that break is also breaking the smaller EMA clouds too.
The most snowflakes will be yellow because that's the 13 EMA. That one is dependent on nothing else and every break will print a snowflake. The 21 will be dependent on the 13. The 50 dependent on the 13 and 21 breaks. The 200 the most important.
For example, if the 200 EMA-BB or EBB is broken at the upper band, deviating by more than 162% of price over a 200 period EMA, and that break is not above the 50 EMA cloud, there will be no snowflake. However, if it exceeds the 13, 21, 50, and 200 clouds, then a purple snowflake will appear above the bar.
Any snowflake is an extreme in price. The purple is an especially good point of entry. That doesn't mean it is a perfect entry. You can build position from it, though, and be relatively certain of a price correction in the near future, because not only was this major EMA cloud violated, but all of the smaller ones too.
Reminder
You still need your PVSRA and candlesticks. This indicator on its own may have a nice hit rate for scalping and building position, as an alternative to the TDI or alongside it, but it is not enough on its own, just like the TDI.
Enjoy!
Quantitative Qualitative Estimation QQE
The QQE indicator is a momentum based indicator to determine trend and sideways.
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index (RSI) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR). These ATR lines are smoothed making this indicator less susceptible to short term volatility.
The most common method of using QQE is to look for crosses of the fast and slow moving trailing stop lines during periods when the QQE line reflects overbought or oversold conditions
Qualitative Quantitative Estimation made up of a smoothed Relative Strength Index (RSI) indicator plus fast and slow volatility-based trailing levels.
Qualitative Quantitative Estimation can be used in two directions:
1.Determine the trend, i.e. if the line is above the 50 level, the trend is ascending, if below - descending;
2.Search for signals at the moment of crossing of the QQE FAST (maroon) and QQE SLOW (blue) lines.
The QQE itself is generally considered to indicate an up-trend ifQQE FAST is above QQE SLOW, and a down-trend if below QQE SLOW.
Often a middle-range between 40 and 60 is set and if the indicator is in that range, then the market is considered to be tracking sideways, or in no trend.
You will need to set only one parameter – “SF” "RSI SMoothing Factor", an analogue of the period in RSI.
By the way, judging from the open source information, the algorithm used the standard strength index with a period of 14 for calculations.
Various signals can be created from the indicator such as:
-Buy when QQE FAST crosses above QQE SLOW below 50 level or just buy when QQE lines crosses above 50 level.
-Sell when QQE FAST crosses below QQE SLOW above 50 level or just sell when QQE lines crosses below 50 level.
WARNING: QQE IS A RSI BASED INDICATOR SO THAT IT CAN TRIGGER FALSE SIGNALS DURING DIVERGENCES!
Kıvanç Özbilgiç
Nifty VolumeWhy this Script : Nifty 50 does not provide volume and some time it is really useful to understand the volume .
This is the pine script which calculate the nifty 50 volume .
Logic :
Take each stock contribute to nifty 50 and find it's volume .
Multiply the same with contribution percentage of the same on Nifty 50
Add up all of them and find the total volume .
There is a similar script by @daytraderph which is built for Bank Nifty (custom volume) . I took the same and built for Nfity.
Nifty has 50 stocks and you cant call security method more than 40 times from one Pine script, so this is the limitation of this script. It consider top 40 stocks and find the volume (which contribute pretty much around 95% of the volume) and convert the same to 100 %
Simple Moving Average Double HelixThis one is a mix of colour-coded moving averages and Ichimoku. It features two pairs of SMAs--default values of 9/20 and 50/200. Each SMA will be green when it rises and red when it falls. The spaces between each pair will fill with green or red depending on which line is on top. 9 over 20 or 50 over 200 makes a green cloud; if 9 or 50 falls below, the cloud will switch to green.
There's also the Ichimoku lagging span and a 35-period SMA (grey) that can be used as a trailing stop loss guideline.
Ideal long setup:
9, 20, 50, and 200 SMA are all green
both clouds are green
lagging span is above historic price action
Ideal short setup:
9, 20, 50, and 200 SMA are all red
both clouds are red
lagging span is below historic price action
RSI5_50 with DivergenceThis is variation of RSI Divergence strategy.
I have added a filter (long term RSI) to the Rules. strategy BUYs when RSI 50 period is above 50 line and there is divergence on the short term RSI
settings
=========
short term RSI period 5
long term RSI period 50
stopLoss is 8% --- if setting is enabled
BUY Rule
========
RSI 50 is above 50 line
short term RSI is showing divergence
Add to existing
==============
if already in position, BUY when shorTermRSI is crossing above 20
TakeProfit
=========
when longTermRSI reaches 60,65, 70 and 75 level , take partial profits .
(not when crossing down --- This may affect on profits , because when price goes down , it goes very fast )
Exit
=====
when longTermRSI is crossing down 30
OR stopLoss value hits
Note: When I tested this with GOOGL stock , I have got excellent results ... any experts there , please check everything is good with scripting ...
Happy Trading
PowerX Strategy Bar Coloring [OFFICIAL VERSION]This script colors the bars according to the PowerX Strategy by Markus Heitkoetter:
The PowerX Strategy uses 3 indicators:
- RSI (7)
- Stochastics (14, 3, 3)
- MACD (12, 26 , 9)
The bars are colored GREEN if...
1.) The RSI (7) is above 50 AND
2.) The Stochastic (14, 3, 3) is above 50 AND
3.) The MACD (12, 26, 9) is above its Moving Average, i.e. MACD Histogram is positive.
The bars are colored RED if...
1.) The RSI (7) is below 50 AND
2.) The Stochastic (14, 3, 3) is below 50 AND
3.) The MACD (12, 26, 9) is below its Moving Average, i.e. MACD Histogram is negative.
If only 2 of these 3 conditions are met, then the bars are black (default color)
We highly recommend plotting the indicators mentioned above on your chart, too, so that you can see when bars are getting close to being "RED" or "GREEN", e.g. RSI is getting close to the 50 line.
BO - Bar's direction Signal - BacktestingBO - Bar's direction Signal - Backtesting Options:
A. Factors Calculate probability of x bars same direction
1. Periods Counting: Data to count From day/month/year To day/month/year
2. Trading Time: only cases occurred in trading time were counted.
B. Timezone
1. Trading time depend on Time zone and specified chart.
2. Enable Highlight Trading Time to check your period time is correct
C. Date Backtesting
* Only cases occurred in Date Backtesting were reported.
D. Setup Options & Rule
1. Reversal after 2 bars same direction
* Probability of 3 bars same direction < 50
* 2 bars same direction is start of series
2. Reversal after 3 bars same direction
* Probability of 4 bars same direction < 50
* 3 bars same direction is start of series
3. Reversal after 4 bars same direction
* Probability of 4 bars same direction < 50
* 3 bars same direction is start of series
4. Reversal after 5 bars same direction
* Probability of 5 bars same direction < 50
* 4 bars same direction is start of series
5. Reversal after 6 bars same direction
* Probability of 6 bars same direction < 50
* 5 bars same direction is start of series
Technical Analysis - Panel Info//A. Oscillators & B. Moving Averages base on TradingView's Technical Analysis by ThiagoSchmitz
//C.Pivot base on Ultimate Pivot Points Alerts by elbartt
//D. Summary & Panel info by anhnguyen14
Panel Info base on these indicators:
A. Oscillators
1. Rsi (14)
2. Stochastic (14,3,3)
3. CCI (20)
4. ADX (14)
5. AO
6. Momentum (10)
7. MACD (12,26)
8. Stoch RSI (3,3,14,14)
9. %R (14)
10. Bull bear
11. UO (7,14,28)
B. Moving Averages
1. SMA & EMA: 5-10-20-30-50-100-200
2. Ichimoku Cloud - Baseline (26)
3. Hull MA (9)
C. Pivot
1. Traditional
2. Fibonacci
3. Woodie
4. Camarilla
D. Summary
Sum_red=A_red+B_red+C_red
Sum_blue=A_blue+B_blue+C_blue
sell_point=(Sum_red/32)*100
buy_point=(Sum_blue/32)*100
sell =
Sum_red>Sum_blue
and sell_point>50
Strong_sell =
A_red>A_blue
and B_red>B_blue
and C_red>C_blue
and sell_point>50
and not crossunder(sell_point,75)
buy =
Sum_red>Sum_blue
and buy_point>50
Strong_buy =
A_red50
and not crossunder(buy_point,75)
neutral = not sell and not Strong_sell and not buy and not Strong_buy
Multi SMA EMA WMA HMA BB (5x8 MAs Bollinger Bands) MAX MTF - RRBMulti SMA EMA WMA HMA 4x7 Moving Averages with Bollinger Bands MAX MTF by RagingRocketBull 2019
Version 1.0
All available MAX MTF versions are listed below (They are very similar and I don't want to publish them as separate indicators):
ver 1.0: 4x7 = 28 MTF MAs + 28 Levels + 3 BB = 59 < 64
ver 2.0: 5x6 = 30 MTF MAs + 30 Levels + 3 BB = 63 < 64
ver 3.0: 3x10 = 30 MTF MAs + 30 Levels + 3 BB = 63 < 64
ver 4.0: 5(4+1)x8 = 8 CurTF MAs + 32 MTF MAs + 20 Levels + 3 BB = 63 < 64
ver 5.0: 6(5+1)x6 = 6 CurTF MAs + 30 MTF MAs + 24 Levels + 3 BB = 63 < 64
ver 6.0: 4(3+1)x10 = 10 CurTF MAs + 30 MTF MAs + 20 Levels + 3 BB = 63 < 64
Fib numbers: 8, 13, 21, 34, 55, 89, 144, 233, 377
This indicator shows multiple MAs of any type SMA EMA WMA HMA etc with BB and MTF support, can show MAs as dynamically moving levels.
There are 4 MA groups + 1 BB group, a total of 4 TFs * 7 MAs = 28 MAs. You can assign any type/timeframe combo to a group, for example:
- EMAs 9,12,26,50,100,200,400 x H1, H4, D1, W1 (4 TFs x 7 MAs x 1 type)
- EMAs 8,13,21,30,34,50,55,89,100,144,200,233,377,400 x M15, H1 (2 TFs x 14 MAs x 1 type)
- D1 EMAs and SMAs 8,13,21,30,34,50,55,89,100,144,200,233,377,400 (1 TF x 14 MAs x 2 types)
- H1 WMAs 13,21,34,55,89,144,233; H4 HMAs 9,12,26,50,100,200,400; D1 EMAs 12,26,89,144,169,233,377; W1 SMAs 9,12,26,50,100,200,400 (4 TFs x 7 MAs x 4 types)
- +1 extra MA type/timeframe for BB
There are several versions: Simple, MTF, Pro MTF, Advanced MTF, MAX MTF and Ultimate MTF. This is the MAX MTF version. The Differences are listed below. All versions have BB
- Simple: you have 2 groups of MAs that can be assigned any type (5+5)
- MTF: +2 custom Timeframes for each group (2x5 MTF) +1 TF for BB, TF XY smoothing
- Pro MTF: 4 custom Timeframes for each group (4x3 MTF), 1 TF for BB, MA levels and show max bars back options
- Advanced MTF: +4 extra MAs/group (4x7 MTF), custom Ticker/Symbols, Timeframe <>= filter, Remove Duplicates Option
- MAX MTF: +2 subtypes/group, packed to the limit with max possible MAs/TFs: 4x7, 5x6, 3x10, 4(3+1)x10, 5(4+1)x8, 6(5+1)x6
- Ultimate MTF: +individual settings for each MA, custom Ticker/Symbols
MAX MTF version tests the limits of Pinescript trying to squeeze as many MAs/TFs as possible into a single indicator.
It's basically a maxed out Advanced version with subtypes allowing for mixed types within a group (i.e. both emas and smas in a single group/TF)
Pinescript has the following limits:
- max 40 security calls (6 calls are reserved for dupe checks and smoothing, 2 are used for BB, so only 32 calls are available)
- max 64 plot outputs (BB uses 3 outputs, so only 61 plot outputs are available)
- max 50000 (50kb) size of the compiled code
Based on those limits, you can only have the following MAs/TFs combos in a single script:
1. 4x7, 5x6, 3x10 - total number of MTF MAs must always be <= 32, and you can still have BB and Num Levels = total MAs, without any compromises
2. 5(4+1)x8, 6(5+1)x6, 4(3+1)x10 - you can use the Current Symbol/Timeframe as an extra (+1) fixed TF with the same number of MTF MAs
- you don't need to call security to display MAs on the Current Symbol/Timeframe, so the total number of MTF MAs remains the same and is still <= 32
- to fit that many MAs into the max 64 plot outputs limit you need to reduce the number of levels (not every MA Group will have corresponding levels)
Features:
- 4x7 = 28 MAs of any type
- 4x MTF groups with XY step line smoothing
- +1 extra TF/type for BB MAs
- 2 MA subtypes within each group/TF
- 4x7 = 28 MA levels with adjustable group offsets, indents and shift
- supports any existing type of MA: SMA, EMA, WMA, Hull Moving Average (HMA)
- custom tickers/symbols for each group
- show max bars back option
- show/hide both groups of MAs/levels/BB and individual MAs
- timeframe filter: show only MAs/Levels with TFs <>= Current TF
- hide MAs/Levels with duplicate TFs
- support for custom TFs that are not available in free accounts: 2D, 3D etc
- support for timeframes in H: H, 2H, 4H etc
Notes:
- Uses timeframe textbox instead of input resolution dropdown to allow for 240 120 and other custom TFs
- Uses symbol textbox instead of input symbol to avoid establishing multiple dummy security connections to the current ticker - otherwise empty symbols will prevent script from running
- Possible reasons for missing MAs on a chart:
- there may not be enough bars in history to start plotting it. For example, W1 EMA200 needs at least 200 bars on a weekly chart.
- for charts with low/fractional prices i.e. 0.00002 << 0.001 (default Y smoothing step) decrease Y smoothing as needed (set Y = 0.0000001) or disable it completely (set X,Y to 0,0)
- for charts with high price values i.e. 20000 >> 0.001 increase Y smoothing as needed (set Y = 10-20). Higher values exceeding MAs point density will cause it to disappear as there will be no points to plot. Different TFs may require diff adjustments
- TradingView Replay Mode UI and Pinescript security calls are limited to TFs >= D (D,2D,W,MN...) for free accounts
- attempting to plot any TF < D1 in Replay Mode will only result in straight lines, but all TFs will work properly in history and real-time modes. This is not a bug.
- Max Bars Back (num_bars) is limited to 5000 for free accounts (10000 for paid), will show error when exceeded. To plot on all available history set to 0 (default)
- Slow load/redraw times. This indicator becomes slower, its UI less responsive when:
- Pinescript Node.js graphics library is too slow and inefficient at plotting bars/objects in a browser window. Code optimization doesn't help much - the graphics engine is the main reason for general slowness.
- the chart has a long history (10000+ bars) in a browser's cache (you have scrolled back a couple of screens in a max zoom mode).
- Reload the page/Load a fresh chart and then apply the indicator or
- Switch to another Timeframe (old TF history will still remain in cache and that TF will be slow)
- in max possible zoom mode around 4500 bars can fit on 1 screen - this also slows down responsiveness. Reset Zoom level
- initial load and redraw times after a param change in UI also depend on TF. For example: D1/W1 - 2 sec, H1/H4 - 5-6 sec, M30 - 10 sec, M15/M5 - 4 sec, M1 - 5 sec. M30 usually has the longest history (up to 16000 bars) and W1 - the shortest (1000 bars).
- when indicator uses more MAs (plots) and timeframes it will redraw slower. Seems that up to 5 Timeframes is acceptable, but 6+ Timeframes can become very slow.
- show_last=last_bars plot limit doesn't affect load/redraw times, so it was removed from MA plot
- Max Bars Back (num_bars) default/custom set UI value doesn't seem to affect load/redraw times
- In max zoom mode all dynamic levels disappear (they behave like text)
- Dupe check includes symbol: symbol, tf, both subtypes - all must match for a duplicate group
- For the dupe check to work correctly a custom symbol must always include an exchange prefix. BB is not checked for dupes
Good Luck! Feel free to learn from/reuse the code to build your own indicators.
Multi SMA EMA WMA HMA BB (4x5 MAs Bollinger Bands) Adv MTF - RRBMulti SMA EMA WMA HMA 4x5 Moving Averages with Bollinger Bands Advanced MTF by RagingRocketBull 2019
Version 1.0
This indicator shows multiple MAs of any type SMA EMA WMA HMA etc with BB and MTF support, can show MAs as dynamically moving levels.
There are 4 MA groups + 1 BB group, a total of 4 TFs * 5 MAs = 20 MAs. You can assign any type/timeframe combo to a group, for example:
- EMAs 12,26,50,100,200 x H1, H4, D1, W1 (4 TFs x 5 MAs x 1 type)
- EMAs 8,10,13,21,30,50,55,100,200,400 x M15, H1 (2 TFs x 10 MAs x 1 type)
- D1 EMAs and SMAs 8,10,12,26,30,50,55,100,200,400 (1 TF x 10 MAs x 2 types)
- H1 WMAs 7,77,89,167,231; H4 HMAs 12,26,50,100,200; D1 EMAs 89,144,169,233,377; W1 SMAs 12,26,50,100,200 (4 TFs x 5 MAs x 4 types)
- +1 extra MA type/timeframe for BB
There are several versions: Simple, MTF, Pro MTF, Advanced MTF and Ultimate MTF. This is the Advanced MTF version. The Differences are listed below. All versions have BB
- Simple: you have 2 groups of MAs that can be assigned any type (5+5)
- MTF: +2 custom Timeframes for each group (2x5 MTF) +1 TF for BB, TF XY smoothing
- Pro MTF: 4 custom Timeframes for each group (4x3 MTF), 1 TF for BB, MA levels and show max bars back options
- Advanced MTF: +2 extra MAs/group (4x5 MTF), custom Ticker/Symbols, Timeframe <>= filter, Remove Duplicates Option
- Ultimate MTF: +individual settings for each MA, custom Ticker/Symbols
Features:
- 4x5 = 20 MAs of any type
- 4x MTF groups with XY step line smoothing
- +1 extra TF/type for BB MAs
- 4x5 = 20 MA levels with adjustable group offsets, indents and shift
- supports any existing type of MA: SMA, EMA, WMA, Hull Moving Average (HMA)
- custom tickers/symbols for each group - you can compare MAs of the same symbol across exchanges
- show max bars back option
- show/hide both groups of MAs/levels/BB and individual MAs
- timeframe filter: show only MAs/Levels with TFs <>= Current TF
- hide MAs/Levels with duplicate TFs
- support for custom TFs that are not available in free accounts: 2D, 3D etc
- support for timeframes in H: H, 2H, 4H etc
Notes:
- Uses timeframe textbox instead of input resolution dropdown to allow for 240 120 and other custom TFs
- Uses symbol textbox instead of input symbol to avoid establishing multiple dummy security connections to the current ticker - otherwise empty symbols will prevent script from running
- Possible reasons for missing MAs on a chart:
- there may not be enough bars in history to start plotting it. For example, W1 EMA200 needs at least 200 bars on a weekly chart.
- price << default Y smoothing step 5. For charts with low/fractional prices (i.e. 0.00002 << 5) adjust X Y smoothing as needed (set Y = 0.0000001) or disable it completely (set X,Y to 0,0)
- TradingView Replay Mode UI and Pinescript security calls are limited to TFs >= D (D,2D,W,MN...) for free accounts
- attempting to plot any TF < D1 in Replay Mode will only result in straight lines, but all TFs will work properly in history and real-time modes. This is not a bug.
- Max Bars Back (num_bars) is limited to 5000 for free accounts (10000 for paid), will show error when exceeded. To plot on all available history set to 0 (default)
- Slow load/redraw times. This indicator becomes slower, its UI less responsive when:
- Pinescript Node.js graphics library is too slow and inefficient at plotting bars/objects in a browser window. Code optimization doesn't help much - the graphics engine is the main reason for general slowness.
- the chart has a long history (10000+ bars) in a browser's cache (you have scrolled back a couple of screens in a max zoom mode).
- Reload the page/Load a fresh chart and then apply the indicator or
- Switch to another Timeframe (old TF history will still remain in cache and that TF will be slow)
- in max possible zoom mode around 4500 bars can fit on 1 screen - this also slows down responsiveness. Reset Zoom level
- initial load and redraw times after a param change in UI also depend on TF. For example:
D1/W1 - 2 sec, H1/H4 - 5-6 sec, M30 - 10 sec, M15/M5 - 4 sec, M1 - 5 sec.
M30 usually has the longest history (up to 16000 bars) and W1 - the shortest (1000 bars).
- when indicator uses more MAs (plots) and timeframes it will redraw slower. Seems that up to 5 Timeframes is acceptable, but 6+ Timeframes can become very slow.
- show_last=last_bars plot limit doesn't affect load/redraw times, so it was removed from MA plot
- Max Bars Back (num_bars) default/custom set UI value doesn't seem to affect load/redraw times
- In max zoom mode all dynamic levels disappear (they behave like text)
1. based on 3EmaBB, uses plot*, barssince and security functions
2. you can't set certain constants from input due to Pinescript limitations - change the code as needed, recompile and use as a private version
3. Levels = trackprice implementation
4. Show Max Bars Back = show_last implementation
5. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
6. Smoothing is applied by default for visual aesthetics on MTF. To use exact ma mtf values (lines with stair stepping) - disable it
Good Luck! You can explore, modify/reuse the code to build your own indicators.
BB Quick Fire5 Bollinger Bands in levels 50,2.0 | 50,2.5 |50,3.0 |50,3.5 |50,4.0
This is used to identify pullbakcs and future pitchfork's.
CM Stochastic POP Method 2-Jake Bernstein_V1Yesterday Jake Bernstein authorized me to post his updated results with the Stochastic Pop Trading System he developed many years ago.
You can take a look at the Original System with Updated Settings at
This indicator is a different set of rules Jake mentioned in the PDF he allowed me to post.
To view the PDF use this link:
dl.dropboxusercontent.com
Today we’re releasing the version described in the PDF that uses the StochK values of 55, 50, and 45. The rules are discussed in the PDF but here is a simple breakdown:
Enter Long when StochK is below 50 and Crosses Above 55
Exit Long on Cross Below 55
Enter Short when StochK is Above 50 and crosses Below 45
Exit Short on Cross Above 45
Two Important Items to understand about this method:
To code the rules Precisely we need a function that will be available when Strategy Capabilities are released on TradingView.
There is one of Jakes Profit Maximizing Strategies that needs to be integrated with this code…which again we need the Strategy based Function that will be coming soon.
To Compare this system to the Stochastic Pop Method 1 System shown yesterday at I used the same Symbol and dates for you to compare…but remember to give this Method 2 System a Fair Look/Evaluation…we need the Soon To Be Released…TradingView Strategy Capabilities.
BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005
Strategy 1 – Stochastic Pop Method 2 System:
Go Long When Stochasticis below 50 and Crosses Above 55. Go Short When Stochastic is above 50 and Crosses Below 45. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value.
Results:
Total Trades = 151
Profit = 40,758 Pips
Win% = 37.1%
Profit Factor = 1.26
Avg Trade = 270 Pips Profit
***Most Consecutive Wins = 4 ... Most Consecutive Losses = 7
Strategy 2:
Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule.
Results:
Total Trades = 151
Profit = 60.305 Pips
Win% = 37.1%
Profit Factor = 1.38
Avg Trade = 399 Pips Profit
***Most Consecutive Wins = 4 ... Most Consecutive Losses = 7
Indicator Includes:
-Ability to Color Candles (CheckBox In Inputs Tab)
Green = Long Trade
Blue = No Trade
Red = Short Trade
Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach TradingView.com’s community how to create Trading Systems and how to Optimize the correct way.
Link To PDF:
dl.dropboxusercontent.com
Link to Original Version of Indicator with Updated Settings.
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
🔥 QUANT MOMENTUM SKORQUANT MOMENTUM SCORE – Description (EN)
Summary: This indicator fuses Price ROC, RSI, MACD, Trend Strength (ADX+EMA) and Volume into a single 0-100 “Momentum Score.” Guide bands (50/60/70/80) and ready-to-use alert conditions are included.
How it works
Price Momentum (ROC): Rate of change normalized to 0-100.
RSI Momentum: RSI treated as a momentum proxy and mapped to 0-100.
MACD Momentum: MACD histogram normalized to capture acceleration.
Trend Strength: ADX is direction-aware (DI+ vs DI–) and blended with EMA state (above/below) to form a combined trend score.
Volume Momentum: Volume relative to its moving average (ratio-based).
Weighting: All five components are weighted, auto-normalized, and summed into the final 0-100 score.
Visuals & Alerts: Score line with 50/60/70/80 guides; threshold-cross alerts for High/Strong/Ultra-Strong regimes.
Inputs, weights and thresholds are configurable; total weights are normalized automatically.
How to use
Timeframes: Works on any timeframe—lower TFs react faster; higher TFs reduce noise.
Reading the score:
<50: Weak momentum
50-60: Transition
60-70: Moderate-Strong (potential acceleration)
≥70: Strong, ≥80: Ultra Strong
Practical tip: Use it as a filter, not a stand-alone signal. Combine score breakouts with market structure/trend context (e.g., pullback-then-re-acceleration) to improve selectivity.
Disclaimer: This is not financial advice; past performance does not guarantee future results.
TrendFlowTrendFlow is a visual trend analysis tool that helps identify changes in market direction and momentum.
It uses three exponential moving averages (EMA 21, EMA 50, and EMA 200) to define short-, medium-, and long-term trend structure.
A dynamic color fill highlights the relationship between the 21 and 50 EMAs:
When EMA 21 is above EMA 50, a green fill indicates upward momentum.
When EMA 21 is below EMA 50, a red fill shows downward momentum.
The EMA 200 line adapts its color based on its position relative to the shorter EMAs:
Red when above both EMAs (strong upward structure)
Green when below both EMAs (strong downward structure)
Gray when between them (neutral or consolidation phase)
This setup provides a clear visual framework for observing trend flow and directional bias over multiple timeframes.
Developed by The Volume Hub Fintech and Strategy Development
S&P Trading System with PivotsThe S&P Trading System with Pivots is a TradingView indicator designed for the 30-minute SPX chart to guide SPY options trading. It uses a trend-following strategy with:
10 SMA and 50 SMA: Plots a 10-period (blue) and 50-period (red) Simple Moving Average. A bullish crossover (10 SMA > 50 SMA) signals a potential buy (green triangle below bar), while a bearish crossunder (10 SMA < 50 SMA) signals a sell or exit (red triangle above bar).
Trend Bias: Colors the background green (bullish) or red (bearish) based on SMA positions.
Pivot Points: Marks recent highs (orange circles) and lows (purple circles) as potential resistance and support levels, using a 5-bar lookback period.
ICT Macro Time WindowsICT Macro Time Windows - Master institutional market timing with automated 'Macro' trading session tracking.
What are 'Macros'?
In ICT terminology, 'Macros' refer to the key institutional trading windows throughout the day where major banks and liquidity providers are most active. These specific time frames see heightened volatility, liquidity, and strategic positioning.
Perfect Timing Automation:
• 8 Critical Macro Sessions:
London 1: 02:33-03:00 EST
London 2: 04:03-04:30 EST
NY AM1: 08:50-09:10 EST
NY AM2: 09:50-10:10 EST
NY AM3: 10:50-11:10 EST
Lunch: 11:50-12:10 EST
PM: 13:10-13:40 EST
Close: 15:15-15:45 EST
• Fully customizable time zones and session times
• Real-time session detection with visual zones & labels
• Automatic High/Low range tracking within each window
• Boxes, lines, and labels for clear visual reference
• Never miss optimal entry/exit timing again
Trade when institutions trade - stop guessing and start timing your setups with precision during these key liquidity windows! All session times are easily adjustable in settings to match your preferred trading hours.
Perfect for Forex, Futures, and Index traders following ICT concepts and institutional flow analysis.
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
SFC Bollinger Band and Bandit概述 (Overview)
SFC 布林通道與海盜策略 (SFC Bollinger Band and Bandit Strategy) 是一個基於 Pine Script™ v6 的技術分析指標，結合布林通道 (Bollinger Bands)、移動平均線 (Moving Averages) 以及布林海盜 (Bollinger Bandit) 交易策略，旨在為交易者提供多時間框架的趨勢分析與進出場訊號。該腳本支援風險管理功能，並提供視覺化圖表與交易訊號提示，適用於多種金融市場。
This script, written in Pine Script™ v6, combines Bollinger Bands, Moving Averages, and the Bollinger Bandit strategy to provide traders with multi-timeframe trend analysis and entry/exit signals. It includes risk management features and visualizes data through charts and trading signals, suitable for various financial markets.
功能特點 (Key Features)
布林通道 (Bollinger Bands)
提供可調整的標準差參數 (σ1, σ2)，支援多層布林通道顯示。
進場訊號基於價格穿越布林通道上下軌，並結合連續K線確認機制。
Provides adjustable standard deviation parameters (σ1, σ2) for multi-layer Bollinger Bands display.
Entry signals are based on price crossing the upper/lower bands, combined with a consecutive bar confirmation mechanism.
移動平均線 (Moving Averages)
支援簡單移動平均線 (SMA) 或指數移動平均線 (EMA)，可自訂快、中、慢線週期。
Supports Simple Moving Average (SMA) or Exponential Moving Average (EMA) with customizable fast, medium, and slow line periods.
布林海盜策略 (Bollinger Bandit Strategy)
基於變動率 (ROC) 與布林通道動態止損，提供做多與做空訊號。
包含動態止損均線與平倉天數設定，增強交易靈活性。
Utilizes Rate of Change (ROC) and Bollinger Bands with dynamic stop-loss for long and short signals.
Includes dynamic stop-loss moving average and liquidation days for enhanced trading flexibility.
多時間框架分析 (Multi-Timeframe Analysis)
支援六個時間框架 (5分、15分、1小時、4小時、日線、週線) 的趨勢分析。
通過表格顯示各時間框架的連續上漲/下跌趨勢，輔助交易決策。
Supports trend analysis across six timeframes (5m, 15m, 1h, 4h, daily, weekly).
Displays consecutive up/down trends in a table to aid decision-making.
風險管理 (Risk Management)
提供基於 ATR 或布林通道的停利/停損設定。
自動計算交易手數，根據報價貨幣匯率調整風險敞口。
Offers take-profit/stop-loss settings based on ATR or Bollinger Bands.
Automatically calculates trading lots, adjusting risk exposure based on quote currency exchange rates.
視覺化與提示 (Visualization and Alerts)
繪製布林通道、移動平均線、海盜策略動態止損線及交易訊號。
提供多時間框架趨勢表格、交易手數標籤及浮水印。
支援交易訊號快訊，方便即時監控。
Plots Bollinger Bands, Moving Averages, Bandit strategy stop-loss lines, and trading signals.
Includes multi-timeframe trend tables, trading lot labels, and watermark.
Supports alert conditions for real-time trade monitoring.
使用說明 (Usage Instructions)
設置參數 (Parameter Setup)
布林通道 (Bollinger Bands): 可調整週期 (預設21)、標準差 (σ1=1, σ2=2) 及停利/停損依據 (ATR 或 BAND)。
移動平均線 (Moving Averages): 可選擇顯示快線 (10)、中線 (20)、慢線 (60)，並切換 SMA/EMA。
布林海盜 (Bollinger Bandit): 調整通道週期 (50)、平倉均線週期 (50) 及 ROC 週期 (30)。
時間框架 (Timeframes): 自訂六個時間框架，預設為 5分、15分、1小時、4小時、日線、週線。
Adjust Bollinger Band period (default 21), standard deviations (σ1=1, σ2=2), and take-profit/stop-loss basis (ATR or BAND).
Configure Moving Averages (fast=10, medium=20, slow=60) and toggle SMA/EMA.
Set Bollinger Bandit parameters: channel period (50), liquidation MA period (50), ROC period (30).
Customize six timeframes (default: 5m, 15m, 1h, 4h, daily, weekly).
交易訊號 (Trading Signals)
買入訊號 (Buy): 價格穿越下軌且滿足連續K線條件。
賣出訊號 (Sell): 價格穿越上軌且滿足連續K線條件。
海盜策略訊號: 基於 ROC 與布林通道穿越，結合動態止損。
Buy signal: Price crosses below lower band with consecutive bar confirmation.
Sell signal: Price crosses above upper band with consecutive bar confirmation.
Bandit strategy signals: Based on ROC and band crossings with dynamic stop-loss.
視覺化 (Visualization)
布林通道以不同顏色顯示上下軌與中軌。
移動平均線以快、中、慢線區分顏色。
趨勢表格顯示各時間框架的趨勢狀態 (🔴上漲, 🟢下跌, ⚪中性)。
海盜策略顯示動態止損線與交易狀態。
Bollinger Bands display upper, lower, and middle bands in distinct colors.
Moving Averages use different colors for fast, medium, and slow lines.
Trend table shows timeframe trends (🔴 up, 🟢 down, ⚪ neutral).
Bandit strategy displays dynamic stop-loss and trading status.
Volatility Channel Oscillator█ OVERVIEW
"Volatility Channel Oscillator" is a technical indicator that analyzes price volatility relative to dynamic price channels, displaying an oscillator, its moving average, and signals based on crossovers and divergences. The indicator offers customizable overbought and oversold levels, gradient visualization, and divergence detection, supported by alerts for key signals.
█ CONCEPTS
The VCO indicator creates dynamic price channels based on a moving average of the price (calculated as the arithmetic mean of the high and low prices: (high + low) / 2) and market volatility (measured as the average candle range and body size). These channels are not displayed on the chart but are used to calculate the oscillator value, which reflects the position of the closing price relative to the channel width, scaled to a range from -100 to +100, with the zero line as the central point. A moving average of the oscillator (SMA) smooths its values, enabling signals based on crossovers with the zero line or overbought/oversold levels. The indicator also detects divergences between price and the oscillator, which may indicate potential trend reversals. VCO is useful for identifying market momentum, reversal points, and trend confirmation, especially when combined with other technical analysis tools.
█ FEATURES
- Volatility Channels: Calculates invisible chart boundaries based on a simple moving average (SMA) of the price (high + low) / 2 and volatility (average candle range and body). The length parameter (default 30) sets the SMA length, and scale (default 200%) adjusts the channel width.
- Oscillator: Determines the oscillator value in the range of -100 to +100, indicating the closing price's position relative to the volatility channel. Displayed with dynamic coloring (green for positive values, red for negative).
- Oscillator Moving Average: A simple moving average (SMA) of the oscillator values, smoothing its movements. The signalLength parameter (default 20) defines the SMA length. Displayed in yellow with an optional gradient.
- Overbought/Oversold Levels: Configurable thresholds for the oscillator (overbought, default 50; oversold, default -50) and its moving average (maOverbought, default 30; maOversold, default -30), shown as horizontal lines with optional gradients. Band colors change dynamically (red for overbought, green for oversold, gray for neutral) based on the moving average's position relative to maOverbought/maOversold, reinforcing other signals.
- Divergences: Detects bullish (price forms a lower low, oscillator a higher low) and bearish (price forms a higher high, oscillator a lower high) divergences using pivots (pivotLength, default 2). Divergences are displayed with a delay equal to the pivot length; larger lengths increase reliability but delay signals. Use as additional confirmation.
Signals:
- Overbought/Oversold Crossovers: Green triangles (buy) when the oscillator crosses above the oversold level, red triangles (sell) when it crosses below the overbought level.
- Zero Line Crossovers: Buy/sell signals when the oscillator crosses the zero line upward (buy) or downward (sell).
- Moving Average Crossovers: Buy/sell signals when the oscillator's moving average crosses the zero line or the maOverbought/maOversold levels. Dynamic band color changes (red/green) at these crossovers reinforce other signals.
- Visualization: Gradient lines for the oscillator, its moving average, overbought/oversold levels, and zero line, with adjustable transparency. Gradient fill between the oscillator and zero line.
Divergence Labels: "Bull" (bullish) and "Bear" (bearish) labels with customizable color and transparency.
- Alerts: Built-in alerts for divergences, overbought/oversold crossovers, and zero line crossovers by the oscillator and its moving average.
█ HOW TO USE
Add to Chart: Apply the indicator via Pine Editor or the Indicators menu on TradingView.
Configure Settings:
- Channel and Oscillator Settings: Adjust the channel SMA length (length, default 30) and channel scaling (scale, default 200%). Increase scale for high-volatility markets.
- Threshold Levels: Set oscillator overbought (overbought, default 50) and oversold (oversold, default -50) levels, and moving average thresholds (maOverbought, default 30; maOversold, default -30).
- Divergence Settings: Enable/disable divergence detection (calculateDivergence) and set pivot length (pivotLength, default 2). Larger values increase reliability but delay signals.
- Signal Settings: Choose signal types (signalType): overbought/oversold, zero line, moving average, or all.
- Styling: Customize colors for the oscillator, moving average, horizontal levels, and divergence labels. Adjust gradient and fill transparency.
Interpreting Signals:
- Buy Signals: Green triangles below the bar when the oscillator or its moving average crosses above the oversold level or zero line.
- Sell Signals: Red triangles above the bar when the oscillator or its moving average crosses below the overbought level or zero line.
- Moving Average Signals: Green/red triangles when the moving average crosses maOverbought/maOversold levels, indicating potential reversals or trend continuation. Dynamic band color changes (red for overbought, green for oversold) at these crossovers reinforce other signals.
- Divergences: "Bull" (bullish) and "Bear" (bearish) labels indicate potential trend reversals with a delay based on pivot length. Use as confirmation.
- Overbought/Oversold Levels: Monitor price reactions in these zones as potential reversal points. Dynamic band color changes based on the moving average reinforce signals.
Signal Confirmation: Use VCO with other tools, such as pivot levels (for key turning points) or Fibonacci levels (for support/resistance zones).
█ APPLICATIONS
- Trend Trading: Zero line crossovers by the oscillator or its moving average identify momentum in uptrends or downtrends.
- Range Trading: Overbought/oversold levels help identify entry/exit points in sideways markets.
- Divergences: Use bullish/bearish divergences as additional confirmation of reversals, especially near key price levels.
- Trend Identification: To analyze trends over a longer perspective, increase the moving average length (signalLength) for more stable signals.
█ NOTES
- Test the indicator across different timeframes and markets to optimize parameters, such as length and scale, for your trading style.
- In strong trends, overbought/oversold levels may persist, requiring additional signal verification.
- Divergences are more reliable on higher timeframes (H4, D1), where market noise is reduced, but their delay requires caution.
- In low-liquidity markets, signals may be less effective, so use on high-liquidity assets is recommended.
