7EMA_5MA (G/D + Bias + 12/26 Signal)This script alow you to survey multiple crossing signals as Golden/Death cross (MA50/200), Institutional Bias (EMA9/18), or EMA 12/26 crossing. You can show/hide all EMAs/MAs and show/hide all signals. Default config displays EMA 50/100/200 and MA 20. Full script includes display of EMA 9/18/12/26/50/100/200 and MA 20/21/50/100/200.
Pesquisar nos scripts por "北证50+指数成分股"
ema based pseudo RSI - JDIf you reverse engineer the "50-level" of the 14 period rsi, you end up with almost exactly the 27 period ema
So to calculate the rsi, you can 'reverse engineer' the 'reverse engineered rsi'.
This can be done by taking the distance between the current price and the "50-level ema"
you can then normalise this by dividing with the atr or the st dev to end up with a chart that's almost exactly like the rsi line
As OB/OS levele, a multiplier of the atr or st dev can be used
one application for this is to quickly refer to MTF rsi levels by multiplying th 27 ema value with the timeframe multiplier
as it turns out, I discovered that the ema's with multiples of 27 as a period align with the 50-level line of the rsi of all the corresponding timeframes.
Enjoy!
JD.
#NotTradingAdvice
#DYOR
RSI Oscillator by mattzabRSI-Oscillator is designed to be highly visual, based on strategies that recognize the RSI above 50 to be positive strength, and below 50 to be weakness.
Midpoint is 50, above is blue, below is red.
BTC 1D Alerts V1This script contains a variety of key indicator for bitcoin all-in-one and they can be activated individually in the menu. These are meant to be used on the 1D chart for Bitcoin.
1457 Day Moving Average: the bottom of the bitcoin price and arguably the rock bottom price target.
Ichimoku Cloud: a common useful indicator for bitcoin support and resistance.
350ma fibs (21 8 5 3 2 and 1.6) : Signify the tops of each logarthmic rise in bitcoin price. They are generally curving higher over the long term. For halvening #3, the predicted market crash would be after hitting the 350ma x3 fib. Also the 350 ma / 111 ma cross signifies bull market top within about 3 days as well. Using the combination of the 350ma fibs and the 350/111 crosses, reasonably identify when market top is about to occur.
50,120,200 ma: Common moving averages that bitcoin retests during bull market runs. Also, the 50/200 golden and death crosses.
1D EMA Superguppy Ribbons: green = bull market, gray is indeterminate, red = bear market. Very high specificity indicator of bull runs, especially for bitcoin. You can change to 3D candle for even more specificity for a bull market start. Use the 1W for even more specificity. 1D Superguppy is recommended for decisionmaking.
1W EMA21: a very good moving average programmed to be shown on both the daily and weekly candle time. Bitcoin commonly corrects to this repeatedly during past bull runs. Acts as support during bull run and resistance during a bear market.
Steps to identifying a bull market:
1. 50/200 golden cross
2. 1D EMA superguppy green
3. 3D EMA superguppy green (if you prefer more certainty than step 2).
4. Hitting the 1W EMA21 and bouncing off during the bull run signifies corrections.
Once a bull market is identified,
Additional recommended buying and selling techniques:
Indicators:
- Fiblines - to determine retracements from peaks (such as all time high or recent highs)
- Stochastic RSI - 1d, 3d, and 1W SRSI are great time to buy, especially the 1W SRSI which comes much less frequently.
- volumen consolidado - for multi exchange volumes compiled into a single line. I prefer buying on the lowest volume days which generally coincide with dips.
- MACD - somewhat dubious utility but many algorithms are programmed to buy or sell based on this.
Check out the Alerts for golden crosses and 350ma Fib crosses which are invaluable for long term buying planning.
I left this open source so that all the formulas can be understood and verified. Much of it hacked together from other sources but all indicators that are fundamental to bitcoin. I apologize in advance for not attributing all the articles and references... but then again I am making no money off of this anyway.
Fischy Bands (multiple periods)Just a quick way to have multiple periods. Coded at (14,50,100,200,400,600,800). Feel free to tweak it. Default is all on, obviously not as usable! Try just using 14, and 50.
This was generated with javascript for easy templating.
Source:
```
const periods = ;
const generate = (period) => {
const template = `
= bandFor(${period})
plot(b${period}, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Basis", transp=show${period}TransparencyLine)
pb${period}Upper = plot(b${period}Upper, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Upper", transp=show${period}TransparencyLine)
pb${period}Lower = plot(b${period}Lower, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Lower", transp=show${period}TransparencyLine)
fill(pb${period}Upper, pb${period}Lower, color=colorFor(${period}, b${period}), transp=show${period}TransparencyFill)`
console.log(template);
}
console.log(`//@version=4
study(shorttitle="Fischy BB", title="Fischy Bands", overlay=true)
stdm = input(1.25, title="stdev")
bandFor(length) =>
src = hlc3
mult = stdm
basis = sma(src, length)
dev = mult * stdev(src, length)
upper = basis + dev
lower = basis - dev
`);
periods.forEach(e => console.log(`show${e} = input(title="Show ${e}?", type=input.bool, defval=true)`));
periods.forEach(e => console.log(`show${e}TransparencyLine = show${e} ? 20 : 100`));
periods.forEach(e => console.log(`show${e}TransparencyFill = show${e} ? 80 : 100`));
console.log('\n');
console.log(`colorFor(period, series) =>
c = period == 14 ? color.white :
period == 50 ? color.aqua :
period == 100 ? color.orange :
period == 200 ? color.purple :
period == 400 ? color.lime :
period == 600 ? color.yellow :
period == 800 ? color.orange :
color.black
c
`);
periods.forEach(e => generate(e))
```
Principe de NY - Rodrigo CohenIndicador criado baseado nas informações de fechamento de bollinger, seguindo o Setup Principe de NY sugerido pelo Analista Rodrigo Cohen, ainda em fase de testes para aprimorar a eficácia do setup
*Considerado apenas Fechamento fora e nesta condição + 50 pontos para entrada sendo assim
Fechamentos com Candles em Vermelho soma 50 pontos e entra vendido
Fechamentos com Candles em Verde soma 50 pontos e entra comprado
O setup pelo que percebi é composto de mais detalhes, aos quais quando tiver acesso realizarei as atualizações devidas
Também estão disponíveis versões de indicadores para Forex
Em breve posto a lista completa com os resultados no MQL5
General Filter Estimator-An Experiment on Estimating EverythingIntroduction
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA , who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something more flexible and less complex with the ability to approximate any filter output. Its possible, but the methods to do so are not something that pinescript can do, we have to use another base for our estimation using coefficients, so i inspired myself from the alpha-beta filter and i started writing the code.
Calculation and The Estimation Coefficients
Simplicity is the key word, its also my signature style, if i want something good it should be simple enough, so my code look like that :
p = length/beta
a = close - nz(b ,close)
b = nz(b ,close) + a/p*gamma
3 line, 2 function, its a good start, we could put everything in one line of code but its easier to see it this way. length control the smoothing amount of the filter, for any filter f(Period) Period should be equal to length and f(Period) = p , it would be inconvenient to have to use a different length period than the one used in the filter we want to estimate (imagine our estimation with length = 50 estimating an ema with period = 100) , this is where the first coefficients beta will be useful, it will allow us to leave length as it is. In general beta will be greater than 1, the greater it will be the less lag the filter will have, this coefficient will be useful to estimate low lagging filters, gamma however is the coefficient who will estimate lagging filters, in general it will range around .
We can get loose easily with those coefficients estimation but i will leave a coefficients table in the code for estimating popular filters, and some comparison below.
Estimating a Simple Moving Average
Of course, the boxcar filter, the running mean, the simple moving average, its an easy filter to use and calculate.
For an SMA use the following coefficients :
beta = 2
gamma = 0.5
Our filter is in red and the moving average in white with both length at 50 (This goes for every comparison we will do)
Its a bit imprecise but its a simple moving average, not the most interesting thing to estimate.
Estimating an Exponential Moving Average
The ema is a great filter because its length times more computing efficient than a simple moving average. For the EMA use the following coefficients :
beta = 3
gamma = 0.4
N.B : The EMA is rougher than the SMA, so it filter less, this is why its faster and closer to the price
Estimating The Hull Moving Average
Its a good filter for technical analysis with tons of use, lets try to estimate it ! For the HMA use the following coefficients :
beta = 4
gamma = 0.85
Looks ok, of course if you find better coefficients i will test them and actualize the coefficient table, i will also put a thank message.
Estimating a LSMA
Of course i was gonna estimate it, but this time this estimation does not have anything a lsma have, no moving average, no standard deviation, no correlation coefficient, lets do it.
For the LSMA use the following coefficients :
beta = 3.5
gamma = 0.9
Its far from being the best estimation, but its more efficient than any other i previously made.
Estimating the Quadratic Least Square Moving Average
I doubted about this one but it can be approximated as well. For the QLSMA use the following coefficients :
beta = 5.25
gamma = 1
Another ok estimate, the estimate filter a bit more than needed but its ok.
Jurik Moving Average
Its far from being a filter that i like and its a bit old. For the comparison i will use the JMA provided by @everget described in this article : c.mql5.com
For the JMA use the following coefficients :
for phase = 0
beta = pow*2 (pow is a parameter in the Jma)
gamma = 0.5
Here length = 50, phase = 0, pow = 5 so beta = 10
Looks pretty good considering the fact that the Jma use an adaptive architecture.
Discussion
I let you the task to judge if the estimation is good or not, my motivation was to estimate such filters using the less amount of calculations as possible, in itself i think that the code is quite elegant like all the codes of IIR filters (IIR Filters = Infinite Impulse Response : Filters using recursion) .
It could be possible to have a better estimate of the coefficients using optimization methods like the gradient descent. This is not feasible in pinescript but i could think about it using python or R.
Coefficients should be dependant of length but this would lead to a massive work, the variation of the estimation using fixed coefficients when using different length periods is just ok if we can allow some errors of precision.
I dont think it should be possible to estimate adaptive filter relying a lot on their adaptive parameter/smoothing constant except by making our coefficients adaptive (gamma could be)
So at the end ? What make a filter truly unique ? From my point of sight the architecture of a filter and the problem he is trying to solve is what make him unique rather than its output result. If you become a signal, hide yourself into noise, then look at the filters trying to find you, what a challenging game, this is why we need filters.
Conclusion
I wanted to give a simple filter estimator relying on two coefficients in order to estimate both lagging and low-lagging filters. I will try to give more precise estimate and update the indicator with new coefficients.
Thanks for reading !
BTC Volume Index [v2018-11-21] @ LekkerCryptisch.nlIndicates the volume trend:
~50 = short term volume is the same as long term volume
> 50 = short term volume is higher than long term volume (i.e. trend is rising volume)
< 50 = short term volume is lower than long term volume (i.e. trend is declining volume)
Reverse Engineered RSI - Key Levels + MTFThis indicator overlays 5 Reverse Engineered RSI (RERSI) levels on your main chart window.
The RERSI was first developed by Giorgos Siligardos in the June 2003 issue of Stocks and Commodities Magazine. HPotter provided the initial implementation - from which this script is derived - so all credit to them (see: ).
In simple terms, RERSI plots lines on the price chart that reflect levels of the RSI . E.g. if you set up a RERSI line at a level of 50, then price will touch that line when the standard RSI indicator reads 50. Hopefully that makes sense, but compare the two if it doesn't.
Why is the RERSI useful if it's just plotting RSI values? Well, it simplifies things, and enables you to get a clearer picture of trend direction, RSI support and resistance levels, RSI trading signals, and it keeps your chart window uncluttered.
I've set up 5 RERSI lines to be plotted: Overbought and Oversold Levels, a Middle Level (generally leave this at 50), and then Down/Up Trend Lines. The latter two are loosely based on the work of Constance Brown (and they in turn were influenced by Andrew Brown), who posited that RSI doesn't breach certain levels during trends (e.g. 40-50 is often a support level during an uptrend).
Play around with the levels, and the RSI Length, to see how your particular market reacts, and where key levels may lie. Remember, this isn't meant as a stand-alone system (although I think there's potential to use it as such, especially with price action trading - which I guess wouldn't make it stand-alone then!!), and works best with confirmation from other sources.
Oh, and there's MTF capability, because I think that's useful for all indicators.
Any queries, please let me know.
Cheers,
RJR
Better RSI with bullish / bearish market cycle indicator This script improves the default RSI. First. it identifies regions of the RSI which are oversold and overbought by changing the color of RSI from white to red. Second, it adds additional reference lines at 20,40,50,60, and 80 to better gauge the RSI value. Finally, the coolest feature, the middle 50 line is used to indicate which cycle the price is currently at. A green color at the 50 line indicates a bullish cycle, a red color indicators a bearish cycle, and a white color indicates a neutral cycle.
The cycles are determined using the RSI as follows:
if RSI is overbought, cycle switches to bullish until RSI falls below 40, at which point it becomes neutral
if RSI is oversold, cycle switches bearish until RSI rises above 60, at which point it becomes neutral
a neutral cycle is exited at either overbought or oversold conditions
Very useful, please give it a try and let me know what you think
ACM22 not repaintedДелал данный скрипт для FORTS.Идеально подойдет тем,кто использует трейлинг стопы.В основе стратегии лежит RSI.Как по мне,хорошая вещь для проверки стратегии и ее оптимизиации.На скрине 50 контрактов,так что не сильно радуйтесь,а просто делите на 50 и получите показатели на 1 контракт.
Script make for futures on MICEX.U can change paramets of RSI,traling stop and stop loss .On a ps 50 futures USDollar-russian ruble.Use for testing and optimisation.
Inertia Indicator The inertia indicator measures the market, stock or currency pair momentum and
trend by measuring the security smoothed RVI (Relative Volatility Index).
The RVI is a technical indicator that estimates the general direction of the
volatility of an asset.
The inertia indicator returns a value that is comprised between 0 and 100.
Positive inertia occurs when the indicator value is higher than 50. As long as
the inertia value is above 50, the long-term trend of the security is up. The inertia
is negative when its value is lower than 50, in this case the long-term trend is
down and should stay down if the inertia stays below 50
GC RSI Columns V2016This is a basic RSI indicator but in column format.I had been using this for a while and it gives a nice visual representation of trend change by changing color of the column.
Base line is 50 level. Anything above 50 is buy opportunity and below 50 is sell opportunity . Try it on higher time frames and see the results.
Example on chart above.
Note: i published it on demand. many folks were asking me for this ,since it(column rsi) was not available in public indicators
Golden Cross, SMA 200 Moving Average Strategy (by ChartArt)This famous moving average strategy is very easy to follow to decide when to buy (go long) and when to take profit.
The strategy goes long when the faster SMA 50 (the simple moving average of the last 50 bars) crosses above the slower SMA 200. Orders are closed when the SMA 50 crosses below the SMA 200. This simple strategy does not have any other stop loss or take profit money management logic. The strategy does not short and goes long only!
Here is an article explaining the "golden cross" strategy in more detail:
www.stockopedia.com
On the S&P 500 index (symbol "SPX") this strategy worked on the daily chart 81% since price data is available since 1982. And on the DOW Jones Industrial Average (symbol "DOWI") this strategy worked on the daily chart 55% since price data is available since 1916. The low number of trades is in both cases not statistically significant though.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Forex Master v4.0 (EUR/USD Mean-Reversion Algorithm)DESCRIPTION
Forex Master v4.0 is a mean-reversion algorithm currently optimized for trading the EUR/USD pair on the 5M chart interval. All indicator inputs use the period's closing price and all trades are executed at the open of the period following the period where the trade signal was generated.
There are 3 main components that make up Forex Master v4.0:
I. Trend Filter
The algorithm uses a version of the ADX indicator as a trend filter to trade only in certain time periods where price is more likely to be range-bound (i.e., mean-reverting). This indicator is composed of a Fast ADX and a Slow ADX, both using the same look-back period of 50. However, the Fast ADX is smoothed with a 6-period EMA and the Slow ADX is smoothed with a 12-period EMA. When the Fast ADX is above the Slow ADX, the algorithm does not trade because this indicates that price is likelier to trend, which is bad for a mean-reversion system. Conversely, when the Fast ADX is below the Slow ADX, price is likelier to be ranging so this is the only time when the algorithm is allowed to trade.
II. Bollinger Bands
When allowed to trade by the Trend Filter, the algorithm uses the Bollinger Bands indicator to enter long and short positions. The Bolliger Bands indicator has a look-back period of 20 and a standard deviation of 1.5 for both upper and lower bands. When price crosses over the lower band, a Long Signal is generated and a long position is entered. When price crosses under the upper band, a Short Signal is generated and a short position is entered.
III. Money Management
Rule 1 - Each trade will use a limit order for a fixed quantity of 50,000 contracts (0.50 lot). The only exception is Rule
Rule 2 - Order pyramiding is enabled and up to 10 consecutive orders of the same signal can be executed (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts).
Rule 3 - Every order will include a bracket with both TP and SL set at 50 pips (note: the algorithm only closes the current open position and does not enter the opposite trade once a TP or SL has been hit).
Rule 4 - When a new opposite trade signal is generated, the algorithm sends in a larger order to close the current open position as well as open a new one (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts. A Short Signal is generated shortly after the 14th Long Signal. The algorithm then sends in a sell order for 400,000 contracts to close the 350,000 contracts long position and open a new short position of 50,000 contracts).
RSI-EMA IndicatorThis indicator calculates and plots 2 separate EMAs of the RSI. The default settings below work great on SPX/SPY daily chart. General rule is if an EMA is above 50, the stock's near term outlook is bullish. If an EMA is below 50, the near term outlook is bearish. Personally, I like to use a fast EMA as a buy signal and a slow EMA as a sell signal.
Default settings:
RSI = 50
EMA1 = 100
EMA2 = 200
High-Low Index [LazyBear]-- Fixed ---
Source: pastebin.com
Fixes an issue with "Combined" mode, using wrong symbols.
--- Original ---
The High-Low Index is a breadth indicator based on Record High Percent, which is based on new 52-week highs and new 52-week lows.
Readings below 50 indicate that there were more new lows than new highs. Readings above 50 indicate that there were more new highs than new lows. 0 indicates there were zero new highs (0% new highs). 100 indicates there was at least 1 new high and no new lows (100% new highs). 50 indicates that new highs and new lows were equal (50% new highs).
Readings consistently above 70 usually coincide with a strong uptrend. Readings consistently below 30 usually coincide with a strong downtrend.
More info:
stockcharts.com
List of my public indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
Just noticed @Greeny has already published this -> Linking it here.
TimWest Long Short FiltersTimWest Long Short Filters
Indicator Has 3 Separate Filters that Create Green(Bullish) or Red(Bearish) BackGround Highlights
If Price is Above or Below a certain LookBack Period - Tim Defaults to 63 on Daily Chart to Quickly View if Price is Above or Below it’s Price 1 Quarter Ago.
A Simple Moving Average Filter - Tim Defaults to 50 SMA and 200 SMA also known as the “Golden Cross”.
A Exponential Moving Average Filter - For Those Who Want To View Shorter Term Market Swings. Defaults to 50 EMA and 100 EMA used By Chuck Hughes, 7 Time World Trading Champion. Chuck Claims the 50/100 EMA's Show the Earliest Change in Market Direction the Equal - Sustainable Moves
Inputs Tab has Checkboxes to Turn On/Off any of the 3 Filters Above.
Reference Chart Post www.tradingview.com
3 projection Indicators - PBands, PO & PBAll these indicators are by Mel Widner.
Projection Bands :
-------------------------------------------------------
These project market data along the trend with the maxima and minima of the projections defining the band. The method provides a way to signal potential direction changes relative to the trend. Usage is like any other trading band.
Projection Oscillator :
-------------------------------------------------------
This indicates the relative position of price with in the bands. It fluctuates between the values 0 to 100. You can configure the "basis" to make it oscillate around a specific value (for ex., basis=50 will make it oscillate between +50 and -50). EMA of PO (length configurable, default is 5) is plotted as a signal line. There is also an option to plot the difference (oscillator - signal), just like MACD histogram. When you see a divergence in this oscillator, remember that it just indicates a potential movement with in the band (for ex., a bullish divergence shown may cause the price to cross the median and move up to the top band).
Projection Bandwidth :
-------------------------------------------------------
This shows the % width of the projection bands. A trend reversal is signaled by a high value. Low value may indicate the start of a new trend. This is also a trend strength indicator.
More info: drive.google.com
Borrowed the color theme for this chart from @liw0. Thanks :)
Chandelier Exit + Zero Lag SMA Chandelier Exit + Zero Lag SMA No Consecutive Signals
Overview
This Pine Script indicator combines the Chandelier Exit (based on ATR) with the Zero Lag SMA to generate reliable buy and sell signals for scalping on BTC/USDT, optimized for the 5-minute timeframe. Designed for crypto traders, it includes features to reduce signal noise and improve trade quality, making it ideal for fast-paced markets like Bitcoin.
Key Features
Chandelier Exit: Uses ATR (period=1, multiplier=2.0) to create dynamic trailing stops, identifying potential reversals with high sensitivity to price volatility.
Zero Lag SMA: A lag-free moving average (length=50) filters signals to ensure trades align with the short-term trend.
No Consecutive Signals: Prevents repetitive buy or sell signals by enforcing alternation (e.g., a buy signal cannot follow another buy), reducing noise in choppy markets.
Cooldown Period: Ensures a minimum of 3 bars between signals to avoid overcrowding.
Volume Filter: Signals are generated only when volume exceeds the 14-period SMA, confirming significant market activity.
Stop Loss Suggestion: Plots swing highs/lows (5-bar lookback) as visual guides for setting stop losses.
How It Works
Buy Signal: Triggered when the price closes above the Chandelier Exit long level, is above the Zero Lag SMA, volume is above the SMA, and the last signal was not a buy.
Sell Signal: Triggered when the price closes below the Chandelier Exit short level, is below the Zero Lag SMA, volume is above the SMA, and the last signal was not a sell.
Visualization:
Green triangles below bars for buy signals.
Red triangles above bars for sell signals.
White line for Zero Lag SMA.
Gray circles for swing low (buy SL) and swing high (sell SL).
Usage
Setup:
Apply to BTC/USDT on a 5-minute chart for optimal scalping results.
Adjust inputs in the settings:
ATR Length: Default 1 (sensitive for crypto).
ATR Multiplier: Default 2.0 (adjust for signal frequency).
Zero Lag SMA Length: Default 50 (trend filter).
Cooldown Bars: Default 3 (space between signals).
Volume MA Length: Default 14 (volume filter sensitivity).
Trading:
Enter long on green triangles, short on red triangles.
Set stop loss at swing low (buy) or swing high (sell), shown as gray circles.
Exit on Zero Lag SMA crossover or use a fixed risk-reward ratio (e.g., 1:2).
Use low leverage (1-5x) and test on a demo account first.
Backtesting:
Use TradingView’s Strategy Tester to evaluate performance on historical BTC/USDT data.
Best in volatile sessions (e.g., Asian/European overlaps).
Notes
Performance: Backtests suggest a high win rate (~90%+ in optimal conditions), but results depend on market conditions. Always validate with paper trading.
Customization: Adjust the ATR multiplier or cooldown period for more/less frequent signals. Add RSI or other filters for enhanced precision (reach out for help!).
Community: Feel free to share feedback, suggest improvements, or post your results in the comments. Let’s refine this together!
Disclaimer
This indicator is for educational purposes only and not financial advice. Crypto markets are volatile; always manage risk and test strategies thoroughly before live trading.
Happy scalping, and thanks for trying this indicator!
INFLECTION NEXUS - SPAINFLECTION NEXUS - SPA (Shadow Portfolio Adaptive)
Foreword: The Living Algorithm
For decades, technical analysis has been a conversation between a trader and a static chart. We apply our indicators with their fixed-length inputs, and we hope that our rigid tools can somehow capture the essence of a market that is fluid, chaotic, and perpetually evolving. When our tools fail, we are told to "adapt." But what if the tools themselves could learn that lesson? What if our indicators could adapt not just for us, but with us?
This script, INFLECTION NEXUS - SPA, is the realization of that vision. It is an advanced analytical framework built around a revolutionary core: the Shadow Portfolio Adaptive (SPA) Engine . The buy and sell signals you see on the chart are an evolution of the logic from my previous work, "Turning Point." However, this is not a simple combination of two scripts. The SPA engine so fundamentally transforms the nature of the analysis that it creates an entirely new class of indicator. This publication is a showcase of that groundbreaking, self-learning engine.
This system is undeniably complex. When you first load it, the sheer volume of information may feel overwhelming. That is a testament to the depth of its analysis. This guide is designed to be your comprehensive manual, to break down every single component, every color, every number, into simple, understandable concepts. By the end of this document, you will not only master its functions but will also possess a deeper understanding of the market dynamics it is designed to reveal.
Chapter 1: The Paradigm Shift - Why the SPA Engine is a Leap Forward
To grasp the innovation here, we must first deconstruct the severe limitations of traditional "adaptive" indicators.
Part A: The Traditional Model - Driving by the Rear-View Mirror
Conventional "adaptive" systems are fundamentally reactive. They operate on a slow, inefficient loop: they wait for their own specific, biased signal to fire, wait for that trade to close, and only after a long and statistically significant "warm-up" period of 50-100 trades do they finally make a small, retrospective adjustment. They are always adapting to a market that no longer exists.
Part B: The SPA Model - The Proactive Co-Pilot
The Shadow Portfolio Adaptive (SPA) engine is a complete re-imagining of this process. It is not reactive; it is proactive, data-saturated, and instantly aware.
Continuous, Unbiased Learning: The SPA engine does not wait for a signal to learn. Its Shadow Portfolio is constantly running 5-bar long and short trades in the background. It learns from every single 5-bar slice of market action , giving it a continuous, unbiased stream of performance data. It is the difference between reading a textbook chapter and having a live sparring partner in the ring 24/7.
Instantaneous Market Awareness - The End of the "Warm-Up": This is the critical innovation. The SPA engine does not require a 100-trade warm-up period. The learning does not start after 50 trades; it begins on the 6th bar of the chart when the first shadow trade closes. From that moment on, the system is market-aware, analyzing data, and capable of making intelligent adjustments. The SPA engine is not adapting to old wins and losses. It is adapting, in near real-time, to the market's ever-shifting character, volatility, and personality.
Chapter 2: The Anatomy of the SPA Engine - A Granular Deep Dive
The engine is composed of three primary systems that work in a sophisticated, interconnected symphony.
Section 1: The Shadow Portfolio (The Information Harvester)
What it is, Simply: Think of this as the script's eyes and ears. It's a team of 10 virtual traders (5 long, 5 short) who are constantly taking small, quick trades to feel out the market.
How it Works, Simply: On every new bar, a new "long" trader and a new "short" trader enter the market. Exactly 5 bars later, they close their positions. This cycle is perpetual and relentless.
The Critical 'Why': Because these virtual traders enter and exit based on a fixed time (5 bars), not on a "good" or "bad" signal, their results are completely unbiased . They are simply measuring: "What happened to price over the last 5 bars?" This provides the raw, untainted truth about the market's behavior that the rest of the system needs to learn effectively.
The Golden Metric (ATR Normalization): The engine doesn't just look at dollar P&L. It's smarter than that. It asks a more intelligent question: "How much did this trade make relative to the current volatility?"
Analogy: Imagine a flea and an elephant. If they both jump 1 inch, who is more impressive? The flea. The SPA engine understands this. A $10 profit when the market is dead quiet is far more significant than a $10 profit during a wild, volatile swing.
The Formula: realized_atr = (close - trade.entry) / trade.atr_entry. It takes the raw profit and divides it by the Average True Range (a measure of volatility) at the moment of entry. This gives a pure, "apples-to-apples" score for every single trade, which is the foundational data point for all learning.
Section 2: The Cognitive Map (The Long-Term Brain)
What it is, Simply: This is the engine's deep memory, its library of experiences. Imagine a giant, 64-square chessboard (8x8 grid). Each square on the board represents a very specific type of market environment.
The Two Dimensions of Thought (The 'How'): How does it know which square we are on? It looks at two things:
The Market's Personality (X-Axis): Is the market behaving like a disciplined soldier, marching in a clear trend? Or is it like a chaotic, unpredictable child, running all over the place? The engine calculates a "Regime" score to figure this out.
The Market's Energy Level (Y-Axis): Is the market sleepy and quiet, or is it wide-awake and hyperactive? The engine measures "Normalized Volatility" to determine this.
The Power of Generalization (The 'Why'): When a Shadow Portfolio trade closes, its result is recorded in the corresponding square on the chessboard. But here's the clever part: it also shares a little bit of that lesson with the squares immediately next to it (using a Gaussian Kernel).
Analogy: If you touch a hot stove and learn "don't touch," your brain is smart enough to know you probably shouldn't touch the hot oven door next to it either, even if you haven't touched it directly. The Cognitive Map does the same thing, allowing it to make intelligent inferences even in market conditions it has seen less frequently. Each square remembers what indicator settings worked best in that specific environment.
Section 3: The Adaptive Engine (The Central Nervous System)
What it is, Simply: This is the conductor of the orchestra. It takes information from all other parts of the system and decides exactly what to do.
The Symphony of Inputs: It listens to three distinct sources of information before making a decision:
The Short-Term Memory (Rolling Stats): It looks at the performance of the last rollN shadow trades. This is its immediate, recent experience.
The Long-Term Wisdom (Cognitive Map): It consults the grand library of the Cognitive Map to see what has worked best in the current market type over the long haul.
The Gut Instinct (Bin Learning): It keeps a small "mini-batch" of the most recent trades. If this batch shows a very strong, sudden pattern, it can trigger a rapid, reflexive adjustment, like pulling your hand away from a flame.
The Fusion Process: It then blends these three opinions together in a sophisticated way. It gives more weight to the opinions it's more confident in (e.g., a Cognitive Map square with hundreds of trades of experience) and uses your Adaptation Intensity (dialK) input to decide how much to listen to its "gut instinct." The final decision is then smoothed to ensure the indicator's parameters change in a stable, intelligent way.
Chapter 3: The Control Panel - A Novice's Guide to Every Input
This is the most important chapter. Let's break down what these confusing settings actually do in the simplest terms possible.
--- SECTION 1: THE DRIVER'S SEAT (SIGNAL ENGINE & BASE SETTINGS) ---
🧾 Signal Engine (Turning Point):
What it is: These are the rules for the final BUY and SELL signs.
Think of it like this: The SPA engine is the smart robot that tunes your race car. These settings are you, the driver, telling the robot what kind of race you're in.
Enable Reversal Mode: You tell the robot, "I want to race on a curvy track with lots of turns." The robot will tune the car to be agile for catching tops and bottoms.
Enable Breakout Mode: You tell the robot, "I want to race on a long, straight track." The robot will tune the car for pure speed to follow the trend.
Require New Extreme: This is a quality filter. It tells the driver, "Don't look for a turn unless we've just hit a new top speed on the straightaway." It makes sure the reversal is from a real extreme.
Min Bars Between Signals: This is the "pit stop" rule. You're telling the robot, "After you show me a sign, wait at least 10 bars before showing another one, so I don't get confused."
⚡ ATR Bands (Base Inputs):
What they are: These are the starting settings for your car before the robot starts tuning it. These are your factory defaults.
Sensitivity: This is the "Bump Detector." A low number means the car feels every tiny pebble on the road. A high number means it only notices the big speed bumps. You want to set it so it notices the important bumps (real market structure) but ignores the pebbles (noise).
ATR Period & Multiplier: These set the starting size of the "safety lane" (the green and blue bands) around your car. The robot's main job is to constantly adjust the size of this safety lane to perfectly fit the current road conditions.
📊 & 📈 Filter Settings (RSI & Volume):
What they are: These are your co-pilot's confirmation checks.
Enable RSI Filter: Your co-pilot will check the "Engine Temperature" (RSI). He won't let you hit the gas (BUY) if the engine is already overheating (overbought).
RSI Length & Lookbacks: These tune how your co-pilot's temperature gauge works. The defaults are standard.
Require Volume Spike: Your co-pilot will check the "Crowd Noise" (Volume). He won't give you a signal unless he hears the crowd roar, confirming that a lot of people are interested in this move.
🎯 Signal Quality Control:
Enable Major Levels Only: This tells your co-pilot to be extra picky. He will only confirm signals that happen after a huge, powerful move, ignoring all the small stuff.
--- SECTION 2: THE ROBOT'S BRAIN (ENGINE & LEARNING CONTROLS) ---
🎛️ Master Control:
Adaptation Intensity (dialK): THIS IS THE ROBOT'S PERSONALITY DIAL.
Turn it DOWN (1-5): The robot becomes a "Wise Old Professor." It thinks very slowly and carefully, gathers lots of data, and only makes a change when it is 100% sure. Its advice is very reliable but might come a little late.
Turn it UP (15-20): The robot becomes a "Hyper-Reactive Teenager." It has a short attention span, reacts instantly to everything it sees, and changes its mind constantly. It's super-fast to new information but might get faked out a lot.
The Default (10): A "Skilled Professional." The perfect balance of thoughtful and responsive. Start here.
🧠 Adaptive Engine:
Enable Adaptive System: This is the main power button for your robot. Turn it off, and you're driving a normal, non-smart car. Turn it on, and the robot takes over the tuning.
Use Shadow Cycle: This turns on the robot's "practice laps." The robot can't learn without practicing. This must be on for the robot to work.
Lock ATR Bands: This is a visual choice. "Locked" means the safety lanes on your screen stay where your factory defaults put them (the robot still makes changes to the signals in the background). "Unlocked" means you see the safety lanes moving and changing shape in real-time as the robot tunes them.
🎯 Learning (Global + Risk):
What they are: These are the deep-level settings for how your robot's brain processes information.
Rolling Window Size: This is the robot's "Short-Term Memory." How many of the last few practice laps should it remember? A small number means it only cares about what just happened. A big number means it remembers the last hour of practice.
Learn Rate & Smooth Alpha: This is "How big of a change should the robot make?" and "How smoothly should it make the change?" Think of it as turning the steering wheel. A high learn rate is like yanking the wheel; a low one is like a gentle turn. The smoothing makes sure the turn is graceful.
WinRate Thresholds & PnL Cap: These are rules for the robot's learning. They tell it what a "good" or "bad" outcome looks like and tell it to ignore crazy, once-in-a-lifetime events so its memory doesn't get corrupted.
--- SECTION 3: THE GARAGE (RISK, MEMORY & VISUALS) ---
⚠️ Risk Management:
What they are: These are safety rules you can give to your co-pilot for your own awareness. They appear on the dashboard.
The settings: You can set a max number of trades, a max loss for the day, and a "time out" period after a few losses.
Apply Risk to Shadow: This is an important switch. If you turn this ON, your safety rules also apply to the robot's practice laps. If you hit your max loss, the robot stops practicing and learning. It's recommended to leave this OFF so the robot can learn 24/7, even if you have stopped trading.
🗺️ Cognitive Map, STM & Checkpoints:
What it is: The robot's "Long-Term Memory" or its entire library of racing experience.
Use Cognitive Map & STM: These switches turn on the long-term and short-term memory banks. You want these on for the smartest robot.
Map Settings (Grid, Sigma, Half-Life): These are very advanced settings for neuroscientists. They control how the robot's brain is structured and how it forgets old information. The defaults are expertly tuned.
The Checkpoint System: This is the "Save Your Game" button for the robot.
To Save: Check Emit Checkpoint Now. Go to your alert log, and you will see a very long password. Copy this password.
To Load: Paste that password into the Memory Checkpoint box. Then, check Apply Checkpoint On Next Bar. The robot will instantly download all of its saved memories and experience.
🎨 Visuals & 🧩 Display Params:
What they are: These are all about how your screen looks.
You can control everything: The size and shape of the little diamonds (Entry Orbs), whether you see the purple Adapt Pulse, and where the Dashboards appear on your screen. You can change the Theme to Dark, Light, or Neon. These settings don't change how the robot thinks, only how it presents its information to you.
Chapter 4: The Command Center - Decoding the Dashboard
PANEL A (INFLECTION NEXUS): Your high-level mission control, showing the engine's classification of the current Market Context and the performance summary of the Shadow Portfolio.
PANEL B (SHADOW PORTFOLIO ADAPTIVE): Your deep diagnostic screen.
Performance Metrics: View advanced risk-adjusted stats like the Sharpe Ratio to understand the quality of the market movements the engine is learning from.
Adaptive Parameters (Live vs Base): THIS IS THE MOST CRITICAL SECTION. It shows the engine's Live parameters right next to your (Base) inputs. When the Live values deviate, the engine is communicating its learned wisdom to you. For example, a Live ATR Multiplier of 2.5 versus your Base of 1.4 is the engine telling you: "Caution. The market is currently experiencing high fake-outs and requires giving positions more room to breathe." This section is a direct translation of the engine's learning into actionable insight.
Chapter 5: Reading the Canvas - On-Chart Visuals
The Bands (Green/Blue Lines): These are not static Supertrend lines. They are the physical manifestation of the engine's current thinking. As the engine learns and adapts its ATR Period and Multiplier, you will see these bands widen, tighten, and adjust their distance from price. They are alive.
The Labels (BUY/SELL): These are the final output of the "Turning Point" logic, now supercharged and informed by the fully adaptive SPA engine.
The Purple Pulse (Dot and Background Glow): This is your visual cue that the engine is "thinking." Every time you see this pulse, it means the SPA has just completed a learning cycle and updated its parameters. It is actively recalibrating itself to the market.
Chapter 6: A Manifesto on Innovation and Community
I want to conclude with a personal note on why I dedicate countless hours to building systems like this and sharing them openly.
My purpose is to drive innovation, period. I am not in this space to follow the crowd or to re-package old ideas. The world does not need a 100th version of a slightly modified MACD. Real progress, real breakthroughs, come from venturing into the wilderness, from asking "what if?" and from pursuing concepts that lie at the very edge of possibility.
I am not afraid of being wrong. I am not afraid of being bested by my peers. In fact, I welcome it. If another developer takes an idea from this engine, improves it, and builds something even more magnificent, that is a profound win for our entire community. The only failure I recognize is the failure to try. The only trap I fear is the creative complacency of producing sterile, recycled work just to appease the status quo.
I love this community, and I believe with every fiber of my being that we have barely scratched the surface of what can be discovered and created. This script is my contribution to that shared journey. It is a tool, an idea, and a challenge to all of us: let's keep pushing.
DISCLAIMER: This script is an advanced analytical tool provided for educational and research purposes ONLY. It does not constitute financial advice. All trading involves substantial risk of loss. Past performance is not indicative of future results. Please use this tool responsibly and as part of a comprehensive trading plan.
As the great computer scientist Herbert A. Simon, a pioneer of artificial intelligence, famously said:
"Learning is any process by which a system improves performance from experience."
*Tooltips were updated with a comprehensive guide
May this engine enhance your experience.
— Dskyz, for DAFE Trading Systems
Irrationality Index by CRYPTO_ADA_BTC"The market can be irrational longer than you can stay solvent" ~ John Maynard Keynes
This indicator, the Irrationality Index, measures how far the current market price has deviated from a smoothed estimate of its "fair value," normalized for recent volatility. It provides traders with a visual sense of when the market may be behaving irrationally, without giving direct buy or sell signals.
How it works:
1. Fair Value Calculation
The indicator estimates a "fair value" for the asset using a combination of a long-term EMA (exponential moving average) and a linear regression trend over a configurable period. This fair value serves as a smoothed baseline for price, balancing trend-following and mean-reversion.
2. Volatility-Adjusted Z-Score
The deviation between price and fair value is measured in standard deviations of recent log returns:
Z = (log(price) - log(fairValue)) / volatility
This standardization accounts for different volatility environments, allowing comparison across assets.
3. Irrationality Score (0–100)
The Z-score is transformed using a logistic mapping into a 0–100 scale:
- 50 → price near fair value (rational zone)
- >75 → high irrationality, price stretched above fair value
- >90 → extreme irrationality, unsustainable extremes
- <25 → high irrationality, price stretched below fair value
- <10 → extreme bearish irrationality
4. Price vs Fair Value (% deviation)
The indicator plots the percentage difference between price and fair value:
pctDiff = (price - fairValue) / fairValue * 100
- Positive values → Percentage above fair value (optimistic / overvalued)
- Negative values → Percentage below fair value (pessimistic / undervalued)
Visuals:
- Irrationality (%) Line (0–100) shows irrationality level.
- Background Colors: Yellow= high bullish irrationality, Green= extreme bullish irrationality, Orange= high bearish irrationality, Red= extreme bearish irrationality.
- Price - FairValue (%) plot: price deviation vs fair value (%), Colored green above 0 and red below 0.
- Label: display actual price, estimated fair value, and Z-score for the latest bar.
- Alerts: configurable thresholds for high and extreme irrationality.
How to read it:
- 50 → Market trading near fair value.
- >75 / >90 → Price may be irrationally high; risk of pullback increases.
- <25 / <10 → Price may be irrationally low; potential rebound zones, but trends can continue.
- Price - FairValue (%) plot → visual guide for % price stretch relative to fair value.
Notes / Warnings:
- Measures relative deviation, not fundamental value!
- High irrationality scores do not automatically indicate trades; markets can remain can be irrational longer than you can stay solvent .
- Best used with other tools: momentum, volume, divergence, and multi-timeframe analysis.
Strong BUY/SELL with BB + RSI + MACD (with alerts)Outer Bands (same as before)
BUY when price < lower BB + RSI < 30 + MACD bullish.
SELL when price > upper BB + RSI > 70 + MACD bearish.
Middle Band (new addition)
BUY when price crosses above middle band (basis) AND RSI > 50 + MACD bullish.
SELL when price crosses below middle band (basis) AND RSI < 50 + MACD bearish.
