US Sector CorrelationsA new and interesting way to look at Breadth. As for the usefulness of it, one would have to do some proper backtesting to get a full grasp of the capabilities. This is just a concept currently. But in general, SPX holding near ATHs with very low sector correlations can be a topping indicator. SPX selling off with Correlations all very positive across each sector...can be a sign of an impending bottom. But, needs the "full bake" of proper testing and analysis versus just guessing. I like the concept and want to explore it further, and I will. This is just the start.
Cari dalam skrip untuk "spx"
Gap RiderThis Indicator allows you to make statistics on the performance of any underlying on the days in which an opening gap occurs.
Specifically, the indicator was designed for "0 dte" options trades. In fact, it is possible to find parameters that give a good statistical advantage by opening a spread in the direction of the gap, creating a trade that has a risk-return ratio of 1: 1.
The indicator shows flags on the graph (green in case of gap up, red in case of gap down) and colored boxes (green in case the stock closed in the direction of the gap, red in case the stock closed in the opposite direction to the gap, yellow in the event that the stock closed at a distance that did not allow the spread in options to close in maximum loss or maximum profit, and therefore in breakeven)
The statistics panel, on the other hand, contains all the information necessary to search for parameters that give the trader a good statistical advantage.
In the settings you can filter the days of the week, only gap up or only gap down, ATR thresholds (volatility), points or minimum percentage for which a gap is taken into account, measure of the breakeven (which for options traders should represent the half the width of the spread to open), large gaps filter that takes into consideration only gaps that open out of range compared to the previous session. The Lookback parameter of course is used to set how many bars to take into account for the statistics.
Parameters and recommended strategy:
TODAY 31/08/2021 - Lookback 500 bars (2 years)
UNDERLYING: SPX
FILTERS: only Monday and Wednesday, only gap up, only gap> 0.01%
STRATEGY: exactly at opening, cover an ATM spread in the direction of the gap (example: gap up, I open a long call spread) that has the opening price as a break even, with a risk-return ratio of 1: 1 and leave it open until closing session, or set take profit at 90-95%. It is advisable to take into consideration the SPX statistics but to operate on the ES future so as to be able to open the spread a couple of minutes before the opening of the cash session and prevent the trade from "running away" due to too sudden movements of the opening. .
RESULTS:
124 Trade
70% profitable trades
30% losing trades
Max drawdown 3 trades
So assuming a spread on ES 10 points wide, each trade would gain or lose $ 250, applying the described strategy we would have in two years, investing only $ 250, a profit of $ 12500, with a max drawdown of $ 750. We would therefore have a profit of 5000%, or rather 2500% per year on the invested capital, with a drawdown of a much lower proportion of the profit ($ 750 compared to $ 6250 of annual profit).
The strategy is infinitely scalable by increasing the options contracts used and the impact of the commissions is almost zero.
MONEY MANAGEMENT: Example on a 50K account, with a spread that earns or loses $ 500, in two years it earns $ 25,000, therefore about 12500 per year, with a max drawdown of $ 1500, therefore 25% per year on the ENTIRE ACCOUNT with a maximum drawdown of 3%.
Note: the test was performed without a break even parameter, so the actual result will be more moderate, but of the same explosive nature.
** BUG STILL LOOKING FOR SOLUTION **
only in case the filters are set to take into account ONLY the gap down, the drawdown count in the statistics panel shows an incorrect result "
Divergence of Stocks Above MA50 v.s. US-Stock MarketEnglish:
This indicator has been developed as an early warning tool to estimate the probability of correction in the US stock market. It works best in the daily chart.
Function:
1.) "Index-line"
The underlying stock index is converted to a scale between 0% and 100% based on its 52-week highs and lows. Where 100% is closing price at 52-week high and 0% is closing price at 52-week low.
2nd) "Stocks Above MA50".
For each major stock index, there is an index that determines the percentage of stocks above its 50 moving average. For example, for the S&P 500, this is the S5FI.
3) "Divergence
In an efficient market, both lines (index and number of stocks above the 50 MA) would run more or less in sync. A new high in the index would also mean a new high in the stocks trading above the 50 moving average. Often, however, a correction in the index is announced when the number of stocks trading above their 50 MA do not make a new, or even a lower, high while the underlying index marks a new high. The divergence signal measures this divergence of the indices. The higher the bar, the more pronounced the divergence.
How to read the indicator?
If a divergence occurs, then the stops should be tightened. As with any indicator, false signals can occur because a divergence does not automatically lead to a correction. The higher the divergence is indicated, the higher the probability. The strength of a correction cannot be predicted with the indicator.
For which symbols does the indicator work?
The indicator works exclusively for the following symbols:
S&P500: SPX, SPY, ES1!, US500 Index above MA50: S5FI
Russel2000: IWM, US2000, RTY1!, RUT, IWO Index above MA50: R2FI
NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index above MA50: NDFI
NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index above MA50: NCFI
NYSE: XAX, NYA Index above MA50: MMFI
DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index above MA50: DIFI
DowJonesComp: DOW, IYY Index above MA50: DCFI
Deutsch:
Dieser Indikator ist als Frühwarninstrument zur Einschätzung der Korrekturwahrscheinlichkeit im US-Aktienmarkt entwickelt worden. Er funktioniert am besten im Tages-Chart.
Funktion:
1.) „Index-line“
Der zugrunde liegende Aktienindex wird bezogen auf seine 52Wochen Hochs und Tiefs in eine Skala zwischen 0% und 100% umgerechnet. Dabei sind 100% Schlusskurs auf 52-Wochen Hoch und 0% Schlusskurs auf 52-Wochen Tief.
2.) „Stocks Above MA50“
Zu jedem Hauptaktienindex gibt es einen Index, der den Prozentwert der Aktien über Ihrem 50 gleitenden Durchschnitt ermittelt. Beim S&P 500 ist das z.B. der S5FI.
3.) „Divergence“
In einem effizienten Markt würden beide Linien (Index und Anzahl Aktien über dem 50 MA) mehr oder weniger synchron laufen. Ein neues Hoch im Index würde auch ein neues Hoch bei den Aktien, die über dem 50 gleitenden Durchschnitt notieren, bedeuten. Oft jedoch kündigt sich eine Korrektur im Index an, wenn die Anzahl der Aktien, die über ihrem 50 MA notieren kein neues, oder sogar ein niedrigeres Hoch machen, während der zu Grunde liegende Index ein neues Hoch markiert. Das Divergenz-Signal misst diese auseinanderlaufen der Indices. Je höher der Balken, umso stärker ist die Divergenz ausgeprägt.
Wie ist der Indikator zu lesen?
Wenn eine Divergenz auftritt, dann sollten die Stopps enger herangezogen werden. Es kann wie bei jedem Indikator zu Fehlsignalen kommen, da eine Divergenz nicht automatisch zu einer Korrektur führen muss. Die Wahrscheinlichkeit ist um so höher, je höher die Divergenz angezeigt wird. Die Stärke einer Korrektur kann mit dem Indikator nicht prognostiziert werden.
Für welche Symbole funktioniert der Indikator?
Der Indikator funktioniert ausschließlich für folgende Symbole:
S&P500: SPX, SPY, ES1!, US500 Index über MA50: S5FI
Russel2000: IWM, US2000, RTY1!, RUT, IWO Index über MA50: R2FI
NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index über MA50: NDFI
NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index über MA50: NCFI
NYSE: XAX, NYA Index über MA50: MMFI
DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index über MA50: DIFI
DowJonesComp: DOW, IYY Index über MA50: DCFI
CCI45/SMA50 indy for 30 min SP500SPCFD:SPX
The script determines entry points using 45 period CCI and 50 period SMA.
Long condition: When CCI crosses up 150 treshold while price above 50 period SMA
Short condition: When CCI crosses down -150 treshold while price below 50 period SMA
Trades are executed above/below 1 point of high/low for long/short positions. Stops are just 1 point below/above of SMA. After 4 points of profit stops should be tightened. If you do not plan to hold the position for a long time, it can produce quick profit within 5-6 bars namely 2.5-3 hour. Otherwise you can manage the trade using SMA as trailing stop. This can be treated as a strategy of scalping which turns out a trend trading eventually if conditions good.
Have a nice trading
CHOP Zone Entry Strategy + DMI/PSAR ExitThis is a Strategy with associated visual indicators and Long/Short and Reverse/Close Position Alerts for the Choppiness Index (CHOP) . It is used to determine if the market is choppy (trading sideways) or not choppy (trading within a trend in either direction). CHOP is not directional, so a DMI script was ported into this strategy to allow for trend confirmation and direction determination; it consists of an Average Directional Index (ADX) , Plus Directional Indicator (+DI) and Minus Directional Indicator (-DI) . In addition, a Parabolic SAR is also included to act as a trailing stop during any strong trends.
Development Notes
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This indicator, and most of the descriptions below, were derived largely from the TradingView reference manual. Feedback and suggestions for improvement are more than welcome, as well are recommended Input settings and best practices for use.
www.tradingview.com
www.tradingview.com
www.tradingview.com
Recommend using the below DMI and PSAR indicators in conjunction with this script to fully visualize and understand how entry and exit conditions are chosen. Variable inputs should correlate between the scripts for uniformity and visual compatibility.
THANKS to LazyBear and his Momentum Squeeze script for helping me quickly develop a momentum state model for coloring the Chop line by trend.
Strategy Description
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CHOP produces values that determine whether the market is choppy or trending . The closer the value is to 100 , the higher the choppiness levels , while the closer it is to 0 , the stronger the market is trending . Territories for both levels, and their associated upper and lower thresholds, are popularly defined using the Fibonacci Retracements, 61.8 and 38.2.
Basic Use
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CHOP is often used to confirm the market condition to help you stay out of sideways markets and only enter when there is movement or imminent explosions. When readings are above the upper threshold, continued sideways movement may be expected, while readings below the lower threshold are typically indicative of a continuing trend. It is also used to anticipate upcoming trendiness changes, with the general belief that extended periods of consolidation (sideways movement) are followed by extended periods of strong, trending, directional movement, and vice versa.
One limitation in this index is that you must be cautious in deciding whether the range or trend will likely continue, or if it will reverse.
Confidence in price action and trend is higher when two or more indicators are in agreement -- while this strategy combines CHOP with both DMI and PSAR, we would still recommend pairing with other indicators to determine entry or exit trade opportunities.
Recommend also choosing 'Once Per Bar Close' when creating alerts.
Inputs
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Strategy Direction - an option to only trade Short, Long, Both, or only in the direction of the Trend (Follow Trend is the Default).
Sensitivity - an incremental variable to test whether the past n candles are in the same trend state before triggering a delayed long or short alert (1 is the Default). Can help filter out noise and reduces active alerts.
Show Chop Index - two visual styles are provided for user preference, a visible Chop line with a background overlay, or a compact column and label only view.
Chop Lookback Period - the time period to be used in calculating CHOP (14 is the Default).
Chop Offset - changing this number will move the CHOP either forwards or backwards relative to the current market (0 is the Default).
Smooth Chop Line and Length - if enabled, the entered time period will be used in calculating a smooth average of the index (Enabled and 4 are the Defaults).
Color Line to Trend Direction - toggles whether the index line is colored to visually depict the current trend direction (Enabled is the Default).
Color Background - toggles the visibility of a background color based on the index state (Enabled is the Default).
Enable DMI Option - if enabled, then entry will be confirmed by and dependent on the ADX Key Level, with any close or reversal confirmed by both ADX and +/-DI to determine whether there is a strong trend present or not (Enabled is the Default).
ADX Smoothing - the time period to be used in calculating the ADX which has a smoothing component (14 is the Default).
DI Length - the time period to be used in calculating the DI (14 is the Default).
ADX Key Level - any trade with the ADX above the key level is a strong indicator that it is trending (23 to 25 is the suggested setting).
Enable PSAR Option - enables trailing stop loss orders (Enabled is the Default).
PSAR Start - the starting value for the Acceleration Force (0.015 is our chosen Default, 0.02 is more common).
PSAR Increment - the increment in which the Acceleration Force will move (0.001 is our chosen Default, 0.02 is more common).
PSAR Max Value - the maximum value of the Acceleration Factor (0.2 is the Default).
Color Candles Option - an option to transpose the CHOP condition levels to the main candle bars. Note that the outer red and green border will still be distinguished by whether each individual candle is bearish or bullish during the specified timeframe.
Note too that if both DMI and PSAR are deselected, then close determinations will default to a CHOP reversal strategy (e.g., close long when below 38.2 and close short when above 61.8). Though if either DMI or PSAR are enabled, then the CHOP reversal for close determination will automatically be disabled.
Indicator Visuals
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For the candle colors, black indicates tight chop (45 to 55), yellow is loose chop (38.2 to 45 and 55 to 61.8), dark purple is trending down (< 38.2), and dark blue is trending up (> 61.8).
The background color has additional shades to differentiate a wider range of more levels…
• < 30 is dark purple
• 30 to 38.2 is purple
• 38.2 to 45 is light purple
• 45 to 55 is black
• 55 to 61.8 is light blue
• 61.8 to 70 is blue
• > 70 is dark blue
Long, Short, Close, and Reverse labels are plotted on the Chop line, which itself can be colored based on the trend. The chop line can also be hidden for a clean and compact, columnar view, which is my preferred option (see example image below).
Visual cues are intended to improve analysis and decrease interpretation time during trading, as well as to aid in understanding the purpose of this strategy and how its inclusion can benefit a comprehensive trading plan.
DMI and Trend Strength
---------------------------
To analyze trend strength, the focus should be on the ADX line and not the +DI or -DI lines. An ADX reading above 25 indicates a strong trend , while a reading below 20 indicates a weak or non-existent trend . A reading between those two values would be considered indeterminable. Though what is truly a strong trend or a weak trend depends on the financial instrument being examined; historical analysis can assist in determining appropriate values.
DMI exits trade when ADX is below the user selected key level (e.g., default is 25) and when the +/- DI lines cross (e.g., -DI > +DI exits long position and +DI > -DI exits short position).
PSAR and Trailing Stop
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PSAR is a time and price based indicator that excels at measuring direction and duration, though not the actual strength of a trend, which is why we use this in conjunction with DMI. It is also included in this script as a trailing stop option to maximize gains during strong trends and to mitigate any false ADX strengthening signals.
This creates a parabola that is located below the candle during a Bullish trend and above during a Bearish trend. A buy or reversal is signaled when the price crosses above or below the Parabolic SAR.
Long/Short Entry
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1. CHOP must be over 61.8 (long) or under 38.2 (short).
2. If DMI is enabled, then the ADX signal line must be above the user selected Key Level (default is 25).
3. If Sensitivity is selected, then that past candle must meet the criteria in step 1, as well as all the intermediate candles in between.
4. If "Follow Trend" is selected and PSAR is enabled, then a long position can only open when the momentum and PSAR are in an uptrend, or short when both are in a downtrend, to include all intermediate candles if the Sensitivity option is set on a past candle.
Close/Reverse
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1. If DMI is enabled, then a close flag will be raised when the ADX signal drops below the Key Level (of 25), and -DI crosses over +DI (if long), or +DI crosses over -DI (if short).
2. If PSAR is enabled, then a close flag will be raised when the current trend state is opposite the last state.
3. If both DMI and PSAR are disabled, then a close flag will be raised if the Chop line drops under 38.2 (if long) or goes over 61.8 (if short).
4. If a Long or Short Entry is triggered on the same candle as any of the above close flags, then the position will be reversed, else the position will be closed.
Strategy Alerts
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1. Long Entry
2. Short Entry
3. Reverse
4. Close
The provided backtest result is based on a position sizing of 10% equity with 100k initial capital. When testing SPX, disabling the DMI performed the best, but EURUSD performed poorly without it enabled, and TSLA had a small reduction in net profit. Timeframe likewise differed between commodities with TSLA performing best at 30M, SPX at 15M, and EURUSD at 4H. I do not plan on using this as a standalone strategy, but I also was expecting better results with the inclusion of EMI and PSAR to compliment the CHOP. Key elements of this script will likely be included in future, more holistic strategies.
Disclaimer
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Past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script are not intended to provide any financial advice. Trade at your own risk.
No known repainting, though there may be if an offset is introduced in the Inputs. I did my best not to code any other variables that repaint, but cannot fully attest to this fact.
Normalized Volatility IndicatorFrom an article by Rajesh Kayakkal:
"Early bear phase signals can help you get out of the market before it turns down. This indicator tells you how.
There are many ways to identify the trend of a financial market, the most common being the 200-day exponential moving average (Ema). When price is trending down below the 200-day Ema, the market is believed to be in a bear phase. If the market is trending up above the 200-day Ema, it is considered to be in a bull phase.
Since every indicator fails at times, I wanted to find other indicators to confirm a trend. In my quest for another indicator to determine the trend for the financial markets, I found the Cboe Volatility Index (Vix) to be a good indicator of the market direction. The Vix is calculated from the weighted average of the implied volatilities of various options on the Standard & Poor’s 500 index futures.
J. Welles Wilder’s average true range can also give an indication of the financial market trends; that is, when the market is in a bull phase, the average true range narrows, and when it is in a bear phase, the average true range expands. The normalized volatility indicator (Nvi) is based on this behavior.
Normalized volatility indicator (Nvi)
Average true range (Atr) varies depending on time. But how do we determine the phase of the financial market with Atr? Perhaps some type of ratio could give us a clue. A ratio presents a relationship of a quantity with respect to another. I did some research based on a ratio of the 64-day average true range and the end-of-day value of equity indexes such as the Standard & Poor’s 500 (Spx). I selected the 64-day period since it is close to the average number of trading days in a quarter. The ratio of the 64-day average true range and closing price does discount seasonal variations in the average true range and gives a single number that can be used to compare volatility of an instrument across many decades. I call this ratio the normalized volatility indicator.
I found an interesting correlation between Nvi and cycles of major equity market indexes. The formula for the Nvi is:
Nvi = 64 - Day average true range/End-of-day price * 100
The NVI gave advanced signals before the cyclical bear phase of SPX commenced in October 2000 and was almost on the spot with the bull phase that began in 2003 and the current secular bear market cycle, which started in November 2007."
Includes options to show inverse NVI and change the ATR length and smoothing.
Reversal closing priceThe reversal closing price (RCP) is a candlestick pattern which follows two simples rules:
the low price of current candle needs to be lower than the low price of the last 2 candles
the closing price of current candle needes to be higher than the closing price of the last candle
This generates a signal for a long position. For a short position, the conditions are inverted:
the high price of current candle needs to be higher than the high price of the last 2 candles
the closing price of current candle needes to be lower than the closing price of the last candle
Since RCP is a trend follower indicator, the strategy is programmed in such a way that long positions are only placed if the short period EMA is above the long period EMA, and short positions are only placed if the short EMA is bellow the long EMA. Both periods are configurable, and should be ajusted for each asset.
This strategy uses a fixed stop loss and take profit, and the it's ratio is configurable. The stop price is one tick lower than the lowest price of X candles prior to the order execution for long positions, while in short positions it's one tick higher than the higher price. The amount of candles to lookback (X) is configurable. Both stop and take profit prices are displayed, the first as a red line, and the second as a green line.
This is the setting that I've found to work best with TVC:SPX , but you may find a better setting. While the RCP is universal, it's placement depends on the trend and it's strenght, something that is very heterogeneous among assets.
I really wish that I was able to place images, but I don't have PRO, so text will have to do.
This strategy was designed by Alexandre Wolwacz, a.k.a. Stormer.
Hide Extended Hours/non-intraday American BarsOnly works with American bar style.
Not works with Candles.
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This script can hide the extended hours/non-intraday bars and leave the intraday bars only, especially for future users, such as ES/NQ/RTY/YM, etc.,.
Now you can find the intraday support/resistance quite easily!
Example, as a ES investor, you can easily find the intraday support/resistance level ,which is almost equal to SPY / SPX , no longer need to check SPY / SPX separately again, saving your time a lot.
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IMPORTANT INSTRUCTION
In order to make the script work, you have to bring it to the most top visual layer.
Please do as the following steps:
Add the script to chart
Hover mouse on the script name, and tap the right-most 'more' button (which appears as 3 dots)
Select "Visual Order", then select "Bring to front".
Done!
Also, in order to have a better view effect and make the bars COMPLETELY "Hidden", you can adjust the hidden bar color in the "setting" menu to the exact color of your chart background.
Options Decay Speed for 0DTEUse only for:
SPX, 5 minutes time frame
This indicator is complementing options 0DTE strategy - selling options for SPX index in the same day as they are expiring. Output of the indicator (red or green color of the curve) indicates whether is profitable to sell options at given moment at delta and VIX specified in the parameters. Changing parameter "Candles" is not recommended.
Main thought is that options expire with certain speed (theta decay) when stock doesnt move. When stock moves in unfavorable direction slowly enough, decay speed can compensate for disadvantage coming from option delta. Intuitively there must be certain speed of stock value change (expressed in stock value per 5 minutes) that is exactly compensating theta decay. This indicator calculates those two values (details below) and shows, where theta decay is faster than stock movement in the last hour and thus favorable to sell options.
Indicator gets its result from comparing two values:
1) volatility in the form of highest high and lowest low for past 12 candles (one hour in total) divided by 12 - meaning average movement of stock expressed in
2) speed of options value decay in form of combination of theta decay and option delta. Formulas are approximation of Black-Scholes model as Pine script doesnt allow for advanced functions. Approximations are accurate to 2 decimal points from market open to one hour before market close and will not indicate green when accuracy is not sufficient. Its value is also expressed in so its mutualy comparable.
My focus was not on code elegance but on practical usability.
Written by Ondřej Škop.
Strategy - Bobo PAPATRHi I've revamped this bot mentioned in the linked idea to make it work with v4 of pine. In doing so there are some very significant changes to how it works. The main one is that it no longer uses traditional daily pivot calculations to calculate the bands. It creates a more dynamic intraday set of pivot points based on recent price action rather than yesterday's ohlc. As published, the bot is tuned for a 15 min time frame. But it actually works well on lower time frames you just need to adjust the lookback periods in settings a bit to re tune it. It's also tuned to ES really but will need tweaking for a different instrument at the very least.
The basic concept is recent price action is used to calculate a 'middle' around which red and green bands are located. Their position or width is largely determined by recent volatility. The middle line is again calculated from recent price action. The three lines from that form a tradeable range with green at the top and red at the bottom. The strategy is simple enough, it shorts as it sinks from outside red, and longs when rising above green. The basic principle being that once you enter that range you have a high probability of hitting the middle before you hit your stop loss. So the basic principle is you are trying to capture the inherent ranginess of liquid indices like S&P 500. That back and forth movement that happens. The bot is capturing this by fading extremes of a recent range but the problem with that is you'dd get murdered in a strong trend. To mitigate that there is a trend calculation running in the background the will prevent trading against firm trends mostly. So the bot should trade mostly in rangy conditions because that is what it is trying to do.
Bot will close issue close signals automatically upon crossing the middle, it also will close automatically at predefined stops or limits. These values are denominated in market mintick values. For example the CFD SPX500 has a mintick of 0.1. Therefore a stop value of 100 will equate to 10 points on the index. If trading the same market via ES1! the mintick value is different - 0.25. So in this case a value of 40 is required to set the stop at 10 points.
Anyway shout if you have questions. Hope it's useful.
TVC:SPX OANDA:SPX500USD
Simple EMA Trading SignalUse it on:
1. Heiken Ashi, Bitstamp: BTCUSD , M15
2. Heiken Ashi, Bitstamp: BTCUSD, D1
3. USOIL Candlesticks H1
4. EURUSD Daily Candlesticks
5. GBPUSD Daily Candlesticks
6. SPX W1 Candlesticks
7. SPX H1 Heiken Ashi
8. XAUUSD Daily
Mansfield Relative Strength indicatorUse this indicator to compare how security is performing in compare with preferred index (SPX by default).
> 0 outperforming
< 0 underperforming
Works best for weekly, but can be applied to monthly and daily charts. It will be rather useless to use it in smaller timeframes
Apply it to SPX, industry index, sector index or other security in similar sector
AK TREND ID v1.00Hello,
"Are we at the top yet ? "........ " Is it a good time to invest ? " ......." Should I buy or sell ? " These are the many questions I hear and get on the daily basis. 1000's of investors do not know when to go in and out of the market. Most of them rely on the opinion of "experts" on television to make their investment decisions. Bad idea.Taking a systematic approach when investing, could save you a lot of time and headache. If there was only a way to know when to get in and out of the market !! hmmmm. The good news is that there many ways to do that. The bad news is , are you disciplined enough to follow it ?
I coded the AK_TREND ID specifically to identified trends in the SPX or SPY only . How does it work ? very simply , I simply plot the spread between the 3 month and 8 month moving average on the chart.
If the spread > 0 @ month end = BUY
if the spread < 0 @ month end = SELL
The AK TREND ID is a LAGGING Indicator , so it will not get you in at the very bottom or get you out at the very top. I did a backtest on the SPX from 1984 to 7/2/2014 (yesterday), The rule was to buy only when the AK TREND ID was green. let's look at the result:
14 trades : 11 W 3 L , 78.75 % winning %
Biggest winner (%) = 108 %
Biggest loser (%) = -10.7 %
Average Return = 27 %
Total Return since 1984 = 351.3 %
You can see the result in detail here : docs.google.com
Although the backtesting results are good, the AK TREND ID is not to be used as a trading system. It is simply design to let you know when to invest and when to get out. I'm working a more accurate version of this Indicator , that will use both technical and fundamental data. In the mean time , I hope this will give some of you piece of mind, and eliminate emotions from your trading decision. Feel free to modify the code as you wish, but please share your finding with the rest of Trading View community.
All the best
Algo
Volatility Targeting: Single Asset [BackQuant]Volatility Targeting: Single Asset
An educational example that demonstrates how volatility targeting can scale exposure up or down on one symbol, then applies a simple EMA cross for long or short direction and a higher timeframe style regime filter to gate risk. It builds a synthetic equity curve and compares it to buy and hold and a benchmark.
Important disclaimer
This script is a concept and education example only . It is not a complete trading system and it is not meant for live execution. It does not model many real world constraints, and its equity curve is only a simplified simulation. If you want to trade any idea like this, you need a proper strategy() implementation, realistic execution assumptions, and robust backtesting with out of sample validation.
Single asset vs the full portfolio concept
This indicator is the single asset, long short version of the broader volatility targeted momentum portfolio concept. The original multi asset concept and full portfolio implementation is here:
That portfolio script is about allocating across multiple assets with a portfolio view. This script is intentionally simpler and focuses on one symbol so you can clearly see how volatility targeting behaves, how the scaling interacts with trend direction, and what an equity curve comparison looks like.
What this indicator is trying to demonstrate
Volatility targeting is a risk scaling framework. The core idea is simple:
If realized volatility is low relative to a target, you can scale position size up so the strategy behaves like it has a stable risk budget.
If realized volatility is high relative to a target, you scale down to avoid getting blown around by the market.
Instead of always being 1x long or 1x short, exposure becomes dynamic. This is often used in risk parity style systems, trend following overlays, and volatility controlled products.
This script combines that risk scaling with a simple trend direction model:
Fast and slow EMA cross determines whether the strategy is long or short.
A second, longer EMA cross acts as a regime filter that decides whether the system is ACTIVE or effectively in CASH.
An equity curve is built from the scaled returns so you can visualize how the framework behaves across regimes.
How the logic works step by step
1) Returns and simple momentum
The script uses log returns for the base return stream:
ret = log(price / price )
It also computes a simple momentum value:
mom = price / price - 1
In this version, momentum is mainly informational since the directional signal is the EMA cross. The lookback input is shared with volatility estimation to keep the concept compact.
2) Realized volatility estimation
Realized volatility is estimated as the standard deviation of returns over the lookback window, then annualized:
vol = stdev(ret, lookback) * sqrt(tradingdays)
The Trading Days/Year input controls annualization:
252 is typical for traditional markets.
365 is typical for crypto since it trades daily.
3) Volatility targeting multiplier
Once realized vol is estimated, the script computes a scaling factor that tries to push realized volatility toward the target:
volMult = targetVol / vol
This is then clamped into a reasonable range:
Minimum 0.1 so exposure never goes to zero just because vol spikes.
Maximum 5.0 so exposure is not allowed to lever infinitely during ultra low volatility periods.
This clamp is one of the most important “sanity rails” in any volatility targeted system. Without it, very low volatility regimes can create unrealistic leverage.
4) Scaled return stream
The per bar return used for the equity curve is the raw return multiplied by the volatility multiplier:
sr = ret * volMult
Think of this as the return you would have earned if you scaled exposure to match the volatility budget.
5) Long short direction via EMA cross
Direction is determined by a fast and slow EMA cross on price:
If fast EMA is above slow EMA, direction is long.
If fast EMA is below slow EMA, direction is short.
This produces dir as either +1 or -1. The scaled return stream is then signed by direction:
avgRet = dir * sr
So the strategy return is volatility targeted and directionally flipped depending on trend.
6) Regime filter: ACTIVE vs CASH
A second EMA pair acts as a top level regime filter:
If fast regime EMA is above slow regime EMA, the system is ACTIVE.
If fast regime EMA is below slow regime EMA, the system is considered CASH, meaning it does not compound equity.
This is designed to reduce participation in long bear phases or low quality environments, depending on how you set the regime lengths. By default it is a classic 50 and 200 EMA cross structure.
Important detail, the script applies regime_filter when compounding equity, meaning it uses the prior bar regime state to avoid ambiguous same bar updates.
7) Equity curve construction
The script builds a synthetic equity curve starting from Initial Capital after Start Date . Each bar:
If regime was ACTIVE on the previous bar, equity compounds by (1 + netRet).
If regime was CASH, equity stays flat.
Fees are modeled very simply as a per bar penalty on returns:
netRet = avgRet - (fee_rate * avgRet)
This is not realistic execution modeling, it is just a simple turnover penalty knob to show how friction can reduce compounded performance. Real backtesting should model trade based costs, spreads, funding, and slippage.
Benchmark and buy and hold comparison
The script pulls a benchmark symbol via request.security and builds a buy and hold equity curve starting from the same date and initial capital. The buy and hold curve is based on benchmark price appreciation, not the strategy’s asset price, so you can compare:
Strategy equity on the chart symbol.
Buy and hold equity for the selected benchmark instrument.
By default the benchmark is TVC:SPX, but you can set it to anything, for crypto you might set it to BTC, or a sector index, or a dominance proxy depending on your study.
What it plots
If enabled, the indicator plots:
Strategy Equity as a line, colored by recent direction of equity change, using Positive Equity Color and Negative Equity Color .
Buy and Hold Equity for the chosen benchmark as a line.
Optional labels that tag each curve on the right side of the chart.
This makes it easy to visually see when volatility targeting and regime gating change the shape of the equity curve relative to a simple passive hold.
Metrics table explained
If Show Metrics Table is enabled, a table is built and populated with common performance statistics based on the simulated daily returns of the strategy equity curve after the start date. These include:
Net Profit (%) total return relative to initial capital.
Max DD (%) maximum drawdown computed from equity peaks, stored over time.
Win Rate percent of positive return bars.
Annual Mean Returns (% p/y) mean daily return annualized.
Annual Stdev Returns (% p/y) volatility of daily returns annualized.
Variance of annualized returns.
Sortino Ratio annualized return divided by downside deviation, using negative return stdev.
Sharpe Ratio risk adjusted return using the risk free rate input.
Omega Ratio positive return sum divided by negative return sum.
Gain to Pain total return sum divided by absolute loss sum.
CAGR (% p/y) compounded annual growth rate based on time since start date.
Portfolio Alpha (% p/y) alpha versus benchmark using beta and the benchmark mean.
Portfolio Beta covariance of strategy returns with benchmark returns divided by benchmark variance.
Skewness of Returns actually the script computes a conditional value based on the lower 5 percent tail of returns, so it behaves more like a simple CVaR style tail loss estimate than classic skewness.
Important note, these are calculated from the synthetic equity stream in an indicator context. They are useful for concept exploration, but they are not a substitute for professional backtesting where trade timing, fills, funding, and leverage constraints are accurately represented.
How to interpret the system conceptually
Vol targeting effect
When volatility rises, volMult falls, so the strategy de risks and the equity curve typically becomes smoother. When volatility compresses, volMult rises, so the system takes more exposure and tries to maintain a stable risk budget.
This is why volatility targeting is often used as a “risk equalizer”, it can reduce the “biggest drawdowns happen only because vol expanded” problem, at the cost of potentially under participating in explosive upside if volatility rises during a trend.
Long short directional effect
Because direction is an EMA cross:
In strong trends, the direction stays stable and the scaled return stream compounds in that trend direction.
In choppy ranges, the EMA cross can flip and create whipsaws, which is where fees and regime filtering matter most.
Regime filter effect
The 50 and 200 style filter tries to:
Keep the system active in sustained up regimes.
Reduce exposure during long down regimes or extended weakness.
It will always be late at turning points, by design. It is a slow filter meant to reduce deep participation, not to catch bottoms.
Common applications
This script is mainly for understanding and research, but conceptually, volatility targeting overlays are used for:
Risk budgeting normalize risk so your exposure is not accidentally huge in high vol regimes.
System comparison see how a simple trend model behaves with and without vol scaling.
Parameter exploration test how target volatility, lookback length, and regime lengths change the shape of equity and drawdowns.
Framework building as a reference blueprint before implementing a proper strategy() version with trade based execution logic.
Tuning guidance
Lookback lower values react faster to vol shifts but can create unstable scaling, higher values smooth scaling but react slower to regime changes.
Target volatility higher targets increase exposure and drawdown potential, lower targets reduce exposure and usually lower drawdowns, but can under perform in strong trends.
Signal EMAs tighter EMAs increase trade frequency, wider EMAs reduce churn but react slower.
Regime EMAs slower regime filters reduce false toggles but will miss early trend transitions.
Fees if you crank this up you will see how sensitive higher turnover parameter sets are to friction.
Final note
This is a compact educational demonstration of a volatility targeted, long short single asset framework with a regime gate and a synthetic equity curve. If you want a production ready implementation, the correct next step is to convert this concept into a strategy() script, add realistic execution and cost modeling, test across multiple timeframes and market regimes, and validate out of sample before making any decision based on the results.
Daily Levels ImporterUser Guide: Daily Levels Importer
What This Indicator Does
This tool allows you to instantly draw multiple support and resistance lines on your TradingView chart by pasting a list of data. It avoids the need to manually draw lines one by one. It also features a dashboard to identify the ticker and filters to toggle specific line colors on or off.
1. The Data Format
The indicator reads text in a specific 3-column format (Comma Separated).
Format: \, \, \
* Ticker: The symbol name (used for the dashboard display).
* Price: The price level where the line will be drawn.
* Color Code:
r = Red
g = Green
y = Yellow
Example:
ES, 4150.25, r
ES, 4200.00, g
ES, 4175.50, y
2. How to Use It
3. Copy Your Data: Select your list of levels (from Excel, a text file, or a website) and copy them to your clipboard.
4. Open Settings: On your TradingView chart, hover over the indicator name and click the Settings (Gear Icon).
5. Paste Data:
* Find the "Paste Data Here" text box in the Inputs tab.
* Delete any existing text.
* Paste your new list.
6. Save: Click OK. The lines will instantly render on your chart.
7. Controls & Filters
You can customize the view without deleting data by using the checkboxes in the Settings menu:
* Line Filters:
* Show Red Levels: Uncheck to hide all red lines.
* Show Green Levels: Uncheck to hide all green lines.
* Show Yellow Levels: Uncheck to hide all yellow lines.
* Dashboard Location:
* Use the dropdowns to move the Ticker ID box to any corner of the screen (e.g., Top Right, Bottom Left) or change its size.
8. Troubleshooting
Lines aren't showing up?
* Ensure the prices match the asset you are viewing (e.g., don't paste SPX prices on an AAPL chart).
* Check if you accidentally unchecked the "Show " box in the settings.
"No Data" in Dashboard?
* The script reads the ticker name from the first row of your pasted data. Ensure the first row is not blank.
Is there a limit?
* Yes. TradingView allows approximately 4,000 characters in the text box. This is roughly 250 lines of price levels. If you need more, add a second instance of the indicator to the chart.
CRS (2 symbols: Ratio or Normalized) + InverseMade for Crosrate comparison By Leo Hanhart
This script is made to do a comparison between two assets under your current chart.
For example if you want to compare SPX over Growth ETF's Below a current asset to find momentum in your stock trading above it
Smart Money Alpha Signals (Performance Dashboard) Smart Money Alpha Signals: Identifying Market Leaders & Generating Alpha
GMP Alpha Signals (Global Market Performance Alpha) is a specialized analysis tool designed not merely to find stocks that are rising, but to identify "Alpha" assets—Market Leaders that defend their price or rise even under adverse conditions where the market index falls or consolidates.
This indicator visualizes the concept of Comparative Relative Strength (RS) and Smart Money accumulation patterns, helping traders capture profit opportunities even during bearish market phases.
Key Objectives (Purpose)
Alpha Capture: Identifying assets generating 'excess returns' that outperform the market Beta.
Smart Money Tracking: Detecting traces of 'institutional buying' and 'accumulation' that defend prices during index plunges.
Decoupling Identification: Spotting assets moving on independent catalysts or momentum, regardless of the broader market direction.
Stop Hunt Filtering: Distinguishing 'fake drops' where price dips temporarily, but Relative Strength remains intact.
Dashboard Guide
Interpretation of the information panel (Table) displayed on the chart.
Rel. Performance: Shows the excess return compared to the index over the set period. (Positive/Green = Stronger than the market).
Decoupling Strength: The correlation coefficient with the index. Lower values (0 or negative) indicate movement independent of market risk.
Bullish: The count/rate of rising or limiting losses when the index drops sharply (e.g., < -0.5%). (Gold = Market Crash Leader).
Defended: The count/rate of holding support levels when the index shows mild weakness (e.g., < -0.05%). (Gold = Strong Accumulation).
Bench. Defense: The defense rate of the comparison benchmark (e.g., TSLA, ETH). Your target asset must be higher to be considered the sector leader.
Input Options & Settings Guide
You can optimize settings according to your trading style and asset class (Stocks/Crypto).
(1) Main Settings
Major Index: The baseline market index for comparison.
(US Stocks: NASDAQ:NDX or TVC:SPX / Crypto: BINANCE:BTCUSDT)
Benchmark Symbol: A competitor within the sector.
(e.g., Set NVDA when analyzing Semiconductor stocks).
Correlation Lookback: The lookback period for judging decoupling. (Default: 30)
Performance Lookback: The number of bars to calculate cumulative returns and defense rates. (Default: 60)
(2) Dashboard Thresholds
These settings define the criteria for what qualifies as "Defended" or "Bullish".
Performance (Max %): Used to find assets that haven't pumped yet. Signals trigger only when Alpha is below this value.
Defended Logic:
Index Drop Condition: The index must drop by at least this amount to start checking. (e.g., -0.05%)
Asset Buffer: How much the asset must outperform the index drop.
(Example: If Index drops -1.0% and Buffer is 0.2%, the asset must be at least -0.8% to count as 'Defended').
Bullish Logic: Measures resilience during steeper market dumps (e.g., -0.5% drop) compared to the Defended Logic.
Volume Settings: Decides whether to count Defended/Bullish instances only when accompanied by volume above the SMA.
(3) Signal Logic Settings (Crucial)
Customize conditions to trigger alerts. The choice between AND / OR is crucial.
AND: Condition must be met SIMULTANEOUSLY with other active conditions (Conservative/High Certainty).
OR: Condition triggers the signal INDEPENDENTLY (Aggressive/Opportunity Capture).
Performance: Is the relative performance within the threshold? (Basic Filter).
Decoupling: Has the correlation dropped? (Start of independent move).
Bullish Rate: Is the Bullish rate high during market dumps?
Defended Rate (High): (Recommended) Is there continuous price defense occurring? (Accumulation detection).
Defended Rate (Low): (Warning) Has the defense rate broken down? (For Stop Loss).
Defended > Benchmark: Is it stronger than the Benchmark (2nd tier)?
Volume Spike: Has volume surged compared to the average? (Institutional involvement).
RSI Oversold: Is it in oversold territory? (Counter-trend trading).
Decoupling Move: Does the current bar show the "Index Down / Asset Up" pattern?
Min USD Volume: Transaction value filter (To exclude low liquidity assets).
RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
Pivots + MAs ISRSPivots + MAs ISRS is a complete market-structure tool designed for traders who want clear institutional levels combined with trend confirmation from moving averages and Fibonacci zones.
This indicator helps you identify breakouts, pullbacks, and reversal points with much higher accuracy.
It combines the best of three worlds:
🔹 1. Advanced Pivot Points (Standard TV Engine)
Includes every major professional pivot type:
Traditional
Fibonacci
Woodie
Classic
DM
Camarilla
You can choose pivot anchors such as:
Daily, Weekly, Monthly, Quarterly, Yearly, and extended periods (2, 3, 5, and 10 years).
✔ Fully customizable colors
✔ Show/hide each level individually
✔ Dynamic labels (left or right)
✔ Works with intraday + extended sessions
🔹 2. Built-in Moving Averages
The indicator includes:
3 EMAs to measure trend direction and momentum
A 5-period SMA for micro-structure and scalping precision
Great for identifying confluences between trend direction + pivot levels.
🔹 3. FiboISRS Zones
Fibonacci-based zones designed to enhance price-reaction detection:
Retracement levels
Liquidity zones
Confluences with EMAs + Pivot Points
Perfect for spotting high-probability reversal areas.
🎯 What This Indicator Helps You Do
✔ See active institutional levels on any timeframe
✔ Detect real breakouts (not fakeouts) using Pivots + MAs
✔ Identify clean pullbacks into key zones
✔ Spot reactions at S1/S2/S3 or R1/R2/R3
✔ Keep your chart clean with minimal noise
Works extremely well on:
Crypto with solid liquidity
Major indices (SPX, NASDAQ, Dow)
Forex
Gold and commodities
🧠 Pro Tip
The highest-probability setups occur when price touches:
👉 A Pivot Level
👉 An EMA (20, 50, or 200)
👉 A FiboISRS zone
When these three overlap, the market often reacts strongly.
⚡ Creator
Indicator created by Ismael Robles (ISRS) to bring a clean, institutional-grade structure to everyday traders.
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Greater Moving AverageThe purpose for this indicator is to function as a comprehensive market-state detector, with the primary goal of avoiding a market crash.
Mendoza Lines (V-pattern detection) identify early crash conditions and warn when market structure becomes unstable.
RSI/volume-shaded candles + Supertrend confirm momentum and trend, creating a unified system to avoid major drawdowns.
Enhanced Wyckoff ranges with ATR.
Mendoza lines identify abrupt V-shaped reversals which often precede high-risk crash structures. By tracking both the formation and resolution of these patterns across multiple timeframes, the indicator provides early warning signals when the market is entering unstable territory, allowing traders to step aside before liquidity collapses or structural breakdowns begin.
Ideal configurations use Heikin Ashi to smooth out candle structure. Observe SPX on a Weekly Chart, which correctly identifies exits and entries during the 2001 and 2009 crashes. On a 6 hour chart, the Tariff low is correctly identified. The improved VWAP uses a cumulative metric rather than the built in ta.vwap calculation, and functions as a macro low beacon when crossed with the 200 EMA. Historically, these crosses have aligned closely with macro cycle lows.
To round out the system, the indicator overlays RSI-based and volume-weighted candle shading to reflect internal momentum and real buying/selling pressure directly on the chart, making shifts in strength immediately visible. A Supertrend confirmation layer acts as the final filter, smoothing noise and verifying trend direction before decisions are made.
US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
Global Liquidity Index LITEGlobal Liquidity Index (GLI LITE) is an indicator that measures global liquidity by combining the balance sheets of major central banks (FED, ECB, PBOC, BOJ) and the M2 money supply of the world’s largest economies (USA, Europe, China, Japan).
Since liquidity directly influences the price of risk assets (BTC, NASDAQ, SPX, etc.), GLI is one of the most important macro signals for identifying market bull/bear regimes.
What the indicator shows:
GLI momentum line (green = liquidity expansion, orange = contraction)
Fast & Slow MA lines that define the liquidity trend
Bull/Bear background coloring
Green → global liquidity is expanding
Red → liquidity is tightening
Correlation between GLI and the asset price (e.g., BTC)
Macro trend panel (Bull / Bear / Neutral)
How to use the indicator:
Bull regime (Fast MA > Slow MA)
Liquidity is expanding and the market has a natural tailwind. Risk assets tend to perform better.
Bear regime (Fast MA < Slow MA)
Liquidity is tightening — higher risk, increased volatility, and more downside pressure.
GLI ↔ Price Correlation
If correlation is high (e.g., > 0.6), GLI can be an excellent leading indicator for price movement.
