Nasdaq VXN Volatility Warning IndicatorToday I am sharing with the community a volatility indicator that uses the Nasdaq VXN Volatility Index to help you or your algorithms avoid black swan events. This is a similar the indicator I published last week that uses the SP500 VIX, but this indicator uses the Nasdaq VXN and can help inform strategies on the Nasdaq index or Nasdaq derivative instruments.
Variance is most commonly used in statistics to derive standard deviation (with its square root). It does have another practical application, and that is to identify outliers in a sample of data. Variance is defined as the squared difference between a value and its mean. Calculating that squared difference means that the farther away the value is from the mean, the more the variance will grow (exponentially). This exponential difference makes outliers in the variance data more apparent.
Why does this matter?
There are assets or indices that exist in the stock market that might make us adjust our trading strategy if they are behaving in an unusual way. In some instances, we can use variance to identify that behavior and inform our strategy.
Is that really possible?
Let’s look at the relationship between VXN and the Nasdaq100 as an example. If you trade a Nasdaq index with a mean reversion strategy or algorithm, you know that they typically do best in times of volatility . These strategies essentially attempt to “call bottom” on a pullback. Their downside is that sometimes a pullback turns into a regime change, or a black swan event. The other downside is that there is no logical tight stop that actually increases their performance, so when they lose they tend to lose big.
So that begs the question, how might one quantitatively identify if this dip could turn into a regime change or black swan event?
The Nasdaq Volatility Index ( VXN ) uses options data to identify, on a large scale, what investors overall expect the market to do in the near future. The Volatility Index spikes in times of uncertainty and when investors expect the market to go down. However, during a black swan event, historically the VXN has spiked a lot harder. We can use variance here to identify if a spike in the VXN exceeds our threshold for a normal market pullback, and potentially avoid entering trades for a period of time (I.e. maybe we don’t buy that dip).
Does this actually work?
In backtesting, this cut the drawdown of my index reversion strategies in half. It also cuts out some good trades (because high investor fear isn’t always indicative of a regime change or black swan event). But, I’ll happily lose out on some good trades in exchange for half the drawdown. Lets look at some examples of periods of time that trades could have been avoided using this strategy/indicator:
Example 1 – With the Volatility Warning Indicator, the mean reversion strategy could have avoided repeatedly buying this pullback that led to this asset losing over 75% of its value:
Example 2 - June 2018 to June 2019 - With the Volatility Warning Indicator, the drawdown during this period reduces from 22% to 11%, and the overall returns increase from -8% to +3%
How do you use this indicator?
This indicator determines the variance of VXN against a long term mean. If the variance of the VXN spikes over an input threshold, the indicator goes up. The indicator will remain up for a defined period of bars/time after the variance returns below the threshold. I have included default values I’ve found to be significant for a short-term mean-reversion strategy, but your inputs might depend on your risk tolerance and strategy time-horizon. The default values are for 1hr VXN data/charts. It will pull in variance data for the VXN regardless of which chart the indicator is applied to.
Disclaimer: Open-source scripts I publish in the community are largely meant to spark ideas or be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Meanreversion
S&P500 VIX Volatility Warning IndicatorToday I am sharing with the community a volatility indicator that can help you or your algorithms avoid black swan events. Variance is most commonly used in statistics to derive standard deviation (with its square root). It does have another practical application, and that is to identify outliers in a sample of data. Variance in statistics is defined as the squared difference between a value and its mean. Calculating that squared difference means that the farther away the value is from the mean, the more the variance will grow (exponentially). This exponential difference makes outliers in the variance data more apparent.
Why does this matter?
There are assets or indices that exist in the stock market that might make us adjust our trading strategy if they are behaving in an unusual way. In some instances, we can use variance to identify that behavior and inform our strategy.
Is that really possible?
Let’s look at the relationship between VIX and the S&P500 as an example. If you trade an S&P500 index with a mean reversion strategy or algorithm, you know that they typically do best in times of volatility. These strategies essentially attempt to “call bottom” on a pullback. Their downside is that sometimes a pullback turns into a regime change, or a black swan event. The other downside is that there is no logical tight stop that actually increases their performance, so when they lose they tend to lose big.
So that begs the question, how might one quantitatively identify if this dip could turn into a regime change or black swan event?
The CBOE Volatility Index (VIX) uses options data to identify, on a large scale, what investors overall expect the market to do in the near future. The Volatility Index spikes in times of uncertainty and when investors expect the market to go down. However, during a black swan event, the VIX spikes a lot harder. We can use variance here to identify if a spike in the VIX exceeds our threshold for a normal market pullback, and potentially avoid entering trades for a period of time (I.e. maybe we don’t buy that dip).
Does this actually work?
In backtesting, this cut the drawdown of my index reversion strategies in half. It also cuts out some good trades (because high investor fear isn’t always indicative of a regime change or black swan event). But, I’ll happily lose out on some good trades in exchange for half the drawdown. Lets look at some examples of periods of time that trades could have been avoided using this strategy/indicator:
Example 1 – With the Volatility Warning Indicator, the mean reversion strategy could have avoided repeatedly buying this pullback that led to SPXL losing over 75% of its value:
Example 2 - June 2018 to June 2019 - With the Volatility Warning Indicator, the drawdown during this period reduces from 22% to 11%, and the overall returns increase from -8% to +3%
How do you use this indicator?
This indicator determines the variance of the VIX against a long term mean. If the variance of the VIX spikes over an input threshold, the indicator goes up. The indicator will remain up for a defined period of bars/time after the variance returns below the threshold. I have included default values I’ve found to be significant for a short-term mean-reversion strategy, but your inputs might depend on your risk tolerance and strategy time-horizon. The default values are for 1hr VIX data. It will pull in variance data for the VIX regardless of which chart the indicator is applied to.
Disclaimer : Open-source scripts I publish in the community are largely meant to spark ideas or be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Deviation BandsThis indicator plots the 1, 2 and 3 standard deviations from the mean as bands of color (hot and cold). Useful in identifying likely points of mean reversion.
Default mean is WMA 200 but can be SMA, EMA, VWMA, and VAWMA.
Calculating the standard deviation is done by first cleaning the data of outliers (configurable).
TradeChartist Actuator™TradeChartist Actuator is an extremely functional indicator that converts the price action volatility and momentum into a meaningful trading system (based on user defined Standard Deviation Factor), that consists of expanding/contracting Volatility Range Bands, Dynamic Trend Support/Resistance Bands and 2 types of Breakout Signals in a visually stunning design. The script also neatly packs in ZigZag & manual/automatic Fibonacci Retracement tools, option to filter the signals using an external filter and other useful extras like ™TradeChartist Dollar Candles and much more.
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™TradeChartist Actuator User Manual
█ Actuator Range Bands
Actuator Range Bands consists of a Mean line, an Upper Band and a Lower Band which are based on user defined Standard Deviation Factor (Default - 1.618, Min - 0.5, Max - 2). The 1.618 factor works extremely well as the unnecessary volatility data of the bands are eliminated by Actuator's logic. In my personal tests, 1.618 works consistently better than any other value in visually showcasing the true volatility range. By eliminating the unnecessary volatility data from the original non-stabilized bands, Actuator helps detect price momentum by detecting two types of breakouts.
Bands Breakout - Filtered
When the price breaks out of the upper or lower band after a trend, there is a strong possibility of a reversal especially when the volatility expansion/contraction takes place. This is detected using a built in filter with the Filtered Bands Breakout and the user can choose to use the closing price or High/Low price as the trigger for breakouts. This trade setup is very useful especially at zones where the Actuator Range Bands contract or squeeze after an expansion as shown in the OANDA:XAUUSD 1hr chart below.
Also, after a consistent expansion of the bands with price trending in the upper channel or the lower channel, users can spot good profit taking or Short trade opportunities with confirmation of overbought price and if possible a strong bear divergence as show in the BINANCE:LUNAUSDTPERP 1hr chart below.
It can be seen from the chart above that even though Actuator is designed to detect Extreme Bands Breakout using High/Low price, it is done with a little bit of filtering by the script logic and hence didn't generate a Bear signal at the lower band support zone.
Mean Breakout - Filtered
In most Mean Reversion models, mostly oscillators, the mean plays an important role in helping traders predict the price dynamic, but it also presents a challenge whether that mean will act as support or resistance so the trader can take a position that will have a high probability of success. Filtered Mean Breakout helps exactly to identify the price dynamic at the mean zone and helps reduce the dilemma. Actuator uses Volatility Trend and Momentum of the price action at mean to determine Bull/Bear breakouts. Following NASDAQ:AAPL 1hr chart shows an example of 2 instances of Filtered Mean Breakout detection, one bull and one bear and further area where no Breakout was detected in spite of price crossing the mean.
This Breakout type is really helpful in spotting early moves and also reduces the high volatility risk of Extreme Bands Breakout in some cases.
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█ External Filter
Actuator breakout signals can be further filtered using the feature of connecting an external signal as a trade filter.
External filter like RSI , MACD etc. can be used to filter breakouts by connecting to ™TradeChartist Actuator under ╔═══ 𝗣𝗹𝘂𝗴 𝗙𝗶𝗹𝘁𝗲𝗿 𝗵𝗲𝗿𝗲 ═══ 🔌 dropdown by enabling 𝐔𝐬𝐞 𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐅𝐢𝐥𝐭𝐞𝐫.
To get the external filter to work, 𝐒𝐢𝐠𝐧𝐚𝐥 𝐓𝐲𝐩𝐞 must be set right. For plots that are non oscillatory like Moving Averages, Super Trend etc., choose type as Non Oscillatory and for Oscillators like RSI , CCI , MACD etc., choose type as Oscillatory .
For Oscillators, levels must be specified for 𝐎𝐬𝐜𝐢𝐥𝐥𝐚𝐭𝐨𝐫 𝐁𝐮𝐥𝐥 𝐅𝐢𝐥𝐭𝐞𝐫 𝐯𝐚𝐥𝐮𝐞 and 𝐎𝐬𝐜𝐢𝐥𝐥𝐚𝐭𝐨𝐫 𝐁𝐞𝐚𝐫 𝐅𝐢𝐥𝐭𝐞𝐫 𝐯𝐚𝐥𝐮𝐞, especially if the Oscillator doesnt have 0 as midline, like RSI . Even for 0 mid oscillators like CCI , filter levels like 100/-100 work effectively to filter noise.
Use 𝐁𝐮𝐥𝐥/𝐁𝐞𝐚𝐫 𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝 𝐅𝐢𝐥𝐥 under Actuator Visuals section to paint the trade zones background. It helps visually see the effect of filters on the breakout entries and also the trade performance.
The following chart shows the Filter settings with ™TradeChartist Momentum Drift Oscillator connected to Actuator as Oscillatory signal with filter values 0.
The two example charts of 1hr BINANCE:BTCUSDT below shows the difference in Actuator signals based on Oscillatory signal from ™TradeChartist Momentum Drift Oscillator and the difference can be seen from the highlighted Bull/Bear Background Fill.
Without External Filter
With External Filter
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█ Dynamic Trend Support/Resistance Bands
In addition to Volatility Range Bands, Actuator also plots Dynamic Trend Support and Resistance bands that are more sensitive to price action and helps the user determine growing support/resistance which is indicated by coloured dots. These dots normally appear when the Support or Resistance stays at the same level for a few bars and change between Bull and Bear colours based on how the price interacts with them as shown below.
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█ Useful Trade Tools
™TradeChartist Dollar Candles
Dollar Candles help detect the volatility exhaustion prices and plots $ signs to help the trader take profits or move stop loss levels to secure gains. The $ signs do not appear for every trade zone, but whenever price hits a critical level, it shows up above price bar (for Bull trend) or below price bar (for Bear trend) in real time. Users can also set alerts for Dollar Candles with Once Per Bar setting. The Daily NASDAQ:TSLA chart below shows the Dollar Candles on both Bull and Bear trends.
It is important to note that taking pockets of profits on a leveraged trade position or moving up stop loss to maximize trend gains at $ candles will help increase Average Profitability Per Trade (APPT) .
Bull/Bear Background Fill
Bull/Bear Background Fill paints the trade zones in Bull and Bear colours. This helps visualize the difference in trade zones when testing various settings and also helps analyze past performance of Actuator Signals with or without the use of External Filter.
Entry Stop Loss Reference
Reference zone for stop loss has always been a tricky one for traders. Using a fixed percentage stop at entry may not be best during high volatility moves. Over the extensive period of Actuator testing, a simple solution to this problem was found. The previous trend's Range Bands Mean Line served as a perfect reference point for Entry Stop. Also while analysing this Mean line, it was found to be a perfect horizontal support/resistance line and also helped detect unproductive trades. The example 15m chart of NASDAQ:AMD shows how the Entry Stop Loss Reference performed.
Stop Line Touch Points plot orange touch points on the Stop Line whenever the price hits it during the trade.
Actuator Colour Bars
Actuator Colour Bars paints the Momentum Strength on the price bars. This helps visually see the price bars venturing into the Overbought or the Oversold zones. Also, this feature also helps spot divergences as higher highs or lower lows with less intense Bull/Bear colour than the previous high/low shows diminishing momentum as shown in the 1h chart of OANDA:GBPJPY below.
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█ ZigZag & Fibonacci Toolkit
Actuator plots developing and completed ZigZags based on Bull and Bear trend depending on the Breakout Type and Breakout Price from the settings.
Option to enable or disable 𝐙𝐢𝐠𝐙𝐚𝐠 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐨𝐫 which can be helpful for Harmonic traders.
Option to display 𝐙𝐢𝐠𝐙𝐚𝐠 𝐇𝐢𝐠𝐡𝐬/𝐋𝐨𝐰𝐬 and 𝐑𝐒𝐈 𝐚𝐭 𝐇𝐢𝐠𝐡𝐬/𝐋𝐨𝐰𝐬 in one of two styles.
Two types of Fibonacci to choose from - 𝐀𝐮𝐭𝐨-𝐅𝐢𝐛𝐬 and 𝐅𝐢𝐛𝐬 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐋𝐨𝐨𝐤𝐛𝐚𝐜𝐤.
𝐀𝐮𝐭𝐨-𝐅𝐢𝐛𝐬 option plots Auto Fibonacci levels based on Bull/Bear trend depending on user specified Breakout Type and Breakout Price.
𝐅𝐢𝐛𝐬 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐋𝐨𝐨𝐤𝐛𝐚𝐜𝐤 plots Fibonacci levels based on the highest high and lowest low of the lookback period (𝐃𝐚𝐲𝐬 or 𝐂𝐚𝐧𝐝𝐥𝐞𝐬).
Fibonacci levels can be reversed by enabling 𝐑𝐞𝐯𝐞𝐫𝐬𝐞 from settings.
Enabling 𝐂𝐮𝐫𝐫𝐞𝐧𝐭 𝐏𝐫𝐢𝐜𝐞 𝐅𝐢𝐛 𝐋𝐚𝐛𝐞𝐥 displays the current Fib level of the developing price bar.
Option to customize Fib levels and colours.
4hr chart of BINANCE:BTCUSDT showing Auto Fibonacci levels, Zig-Zag with Trend High/Lows, Zig-Zag connectors with Fib Ratios and RSI at Trend High/Low prices.
Note:
If momentum doesn't slow down, the fibs can extend beyond 1 and may continue way beyond 4.618 fib level. These are quite rare depending on how distant the near high/low is based.
ZigZag and Fibonacci are good reference indicators and should always be used as confirmations rather than standalone indicators.
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█ Actuator Colour Scheme
Actuator employs 3 built in colour schemes namely Chilli , Flame and Sublime Grayscale and a versatile colour scheme Custom which enables the user to customise the colour combinations of the components of the Actuator script.
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█ Alerts
Alerts can be created for the following.
Actuator Bull Breakout Signal - Once Per Bar Close
Actuator Bear Breakout Signal - Once Per Bar Close
Actuator Long Dollar - Take Profit - Once Per Bar
Actuator Short Dollar - Take Profit - Once Per Bar
Actuator Stop Line Hit - Once Per Bar
Note: The script doesn't repaint, so the alerts can be used with confidence. To check this, users can do bar replays to check if the plots and markers stay in the same place.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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TradeChartist Mean Momentum Drift Oscillator (MMDO)™TradeChartist Mean Momentum Drift Oscillator (MMDO) is the Oscillator version of the ™TradeChartist Mean Momentum Drift Bands (MMDB) indicator with some added visual features to spot Momentum, divergences and Price action using ™TradeChartist Zone Visualizer model.
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Features of ™TradeChartist MMDO
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Price zone detection using ™TradeChartist Zone Visualizer model.
No User input required.
3 Visual colour schemes - Chilli, Flame and Custom.
Clear Visualization of Overbought and Oversold zones.
Colour Bars based on Momentum strength.
MDDO highs and lows tracker helps detect divergences.
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Example Charts
1. MMDO used along with ™TradeChartist MMDB (Mean Momentum Drift Bands) on 4hr chart of BINANCE:BTCUSDT
2. MMDO on 1hr chart of OANDA:EURUSD to confirm Drift Bands breakout entries on MMDB
3. MMDO on 1hr chart of BINANCE:LUNAUSDT
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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Outside DayThis strategy is taken from Perry Kaufman's book "Trading System and Methods".
You can enter on the direction of the candle, or opposite to it. I find that the opposite tends to yield better results in volatile assets, allowing a better reward to risk ratio. There is no stop loss in this strategy, only a fixed take profit and a time limitation.
34 EMA BandsThis is quite a simple script, just plotting a 34EMA on high's and low's of candles. Appears to work wonders though, so here it is.
There is some //'d code which I haven't finished working on, but it looks to be quite similar to Bollinger Bands, just using different math rather than standard deviations from the mean.
The bands itself is pretty self explanatory, price likes to use it as resistance when under it, it can trade inside it and it can use the upper EMA as support when in a strong upward trend.
Low-High-Trend StrategyWhen asked what the key to successful investing was, Warren Buffet famously said “buy low, sell high.” Was he onto something? Today I am sharing with the community a simple “buy low, sell high” strategy with an optional trend filter and take-profit target. I’ve found that this strategy works well in a variety of markets but has a higher tendency to out-perform buy & hold in markets that are ranging sideways.
How it works:
The strategy tracks the highest and lowest price over the last X number of bars (you select the look-back period). The highest price line is plotted in green and the lowest price line is potted in red. If the price crosses over the lowest price in the last X number of bars, then a buy signal is generated. Exit options include a take-profit % or selling when the price crosses over the highest price in the last X amount of bars. I.e. “Buy low, sell high.” An EMA is also plotted as a blue trend line, and there is an option to only trade if the price is above the EMA trend line.
Disclaimer: Open source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. Even though this example script beats buy and hold over the back-test time-frame, I wouldn't advise using it as a stand-alone strategy without significant additions/modifications to the strategy and risk management functions. In this example the script is being used as a medium-term strategy with just 10% leverage over account equity, a $25k start balance, and back-testing 10+ years. Modifiable slippage and commissions are included in the model.
Green line = Highest price in the look-back period
Red line = Lowest price in the look-back period
Blue line = EMA Trend
Augmented Dickey–Fuller (ADF) mean reversion testThe augmented Dickey-Fuller test (ADF) is a statistical test for the tendency of a price series sample to mean revert .
The current price of a mean-reverting series may tell us something about the next move (as opposed, for example, to a geometric Brownian motion). Thus, the ADF test allows us to spot market inefficiencies and potentially exploit this information in a trading strategy.
Mathematically, the mean reversion property means that the price change in the next time period is proportional to the difference between the average price and the current price. The purpose of the ADF test is to check if this proportionality constant is zero. Accordingly, the ADF test statistic is defined as the estimated proportionality constant divided by the corresponding standard error.
In this script, the ADF test is applied in a rolling window with a user-defined lookback length. The calculated values of the ADF test statistic are plotted as a time series. The more negative the test statistic, the stronger the rejection of the hypothesis that there is no mean reversion. If the calculated test statistic is less than the critical value calculated at a certain confidence level (90%, 95%, or 99%), then the hypothesis of a mean reversion is accepted (strictly speaking, the opposite hypothesis is rejected).
Input parameters:
Source - The source of the time series being tested.
Length - The number of points in the rolling lookback window. The larger sample length makes the ADF test results more reliable.
Maximum lag - The maximum lag included in the test, that defines the order of an autoregressive process being implied in the model. Generally, a non-zero lag allows taking into account the serial correlation of price changes. When dealing with price data, a good starting point is lag 0 or lag 1.
Confidence level - The probability level at which the critical value of the ADF test statistic is calculated. If the test statistic is below the critical value, it is concluded that the sample of the price series is mean-reverting. Confidence level is calculated based on MacKinnon (2010) .
Show Infobox - If True, the results calculated for the last price bar are displayed in a table on the left.
More formal background:
Formally, the ADF test is a test for a unit root in an autoregressive process. The model implemented in this script involves a non-zero constant and zero time trend. The zero lag corresponds to the simple case of the AR(1) process, while higher order autoregressive processes AR(p) can be approached by setting the maximum lag of p. The null hypothesis is that there is a unit root, with the alternative that there is no unit root. The presence of unit roots in an autoregressive time series is characteristic for a non-stationary process. Thus, if there is no unit root, the time series sample can be concluded to be stationary, i.e., manifesting the mean-reverting property.
A few more comments:
It should be noted that the ADF test tells us only about the properties of the price series now and in the past. It does not directly say whether the mean-reverting behavior will retain in the future.
The ADF test results don't directly reveal the direction of the next price move. It only tells wether or not a mean-reverting trading strategy can be potentially applicable at the given moment of time.
The ADF test is related to another statistical test, the Hurst exponent. The latter is available on TradingView as implemented by balipour , QuantNomad and DonovanWall .
The ADF test statistics is a negative number. However, it can take positive values, which usually corresponds to trending markets (even though there is no statistical test for this case).
Rigorously, the hypothesis about the mean reversion is accepted at a given confidence level when the value of the test statistic is below the critical value. However, for practical trading applications, the values which are low enough - but still a bit higher than the critical one - can be still used in making decisions.
Examples:
The VIX volatility index is known to exhibit mean reversion properties (volatility spikes tend to fade out quickly). Accordingly, the statistics of the ADF test tend to stay below the critical value of 90% for long time periods.
The opposite case is presented by BTCUSD. During the same time range, the bitcoin price showed strong momentum - the moves away from the mean did not follow by the counter-move immediately, even vice versa. This is reflected by the ADF test statistic that consistently stayed above the critical value (and even above 0). Thus, using a mean reversion strategy would likely lead to losses.
Mean Reversion Strategy v2 [KL]Description :
This strategy will enter a position when the following conditions are met:
a) Main signal: When source data (ATR) diverts from its moving average value, and
b) Confirmation: If predicted direction of trend is favorable.
Assumptions :
During periods of high price volatility, ATR diverts from its moving average value. Eventually, ATR should revert. But since just knowing the magnitude of increase/decrease of ATR does not indicate a trend signal, we need to introduce a model to predict the current trend.
In short:
• Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping.
• Assessment of ATR diversion : To determine "yes/no" regarding whether ATR at a given point in time has diverted, this script conducts a two-tailed hypothesis test at each candlestick period. The null hypothesis (H0) is that the fast moving average value should equal the slow moving average value (say, denoted as H0: atr14 == atr28; it is assumed that atr28 is more meaningful for the purpose of describing the current trend because it has a larger sample size). Investopedia has an article summarizing this topic .
Exit Condition :
When trailing stop loss hits.
Previous version :
This strategy is based on Version 1 published back in September . This older version considers +/- one standard deviation to be the critical values relative to average ATR when testing whether ATR has diverted from the mean. This does not take Standard Error ("SE") into account. As a result, the threshold is often too wide and it generates too many entry signals.
Percentile Rank [racer8]The Percentile is a mathematical tool developed in the field of statistics. It determines how a value compares to a set of values.
There are many applications for this like ...
... determining your rank in your college math class
... your rank in terms of height, weight, economic status, etc.
... determining the 3-month percentile of the current stock price (which is what this indicator performs)
This indicator calculates the percentile rank for the current stock price for n periods.
For example, if the stock's current price is above 80% of the previous stock's prices over a 100-period span, then it has a percentile rank of 80.
For traders, this is extremely valuable information because it tells you if the current stock price is overbought or oversold.
If the stock's price is in the 95th percentile, then it is highly likely that it is OVERBOUGHT, and that it will revert back to the mean price.
Helplful TIP: I recommend that you set the indicator to look back over at LEAST 100 periods for accuracy!
Thanks for reading! 👍
Volume Breakout (ValueRay)Easy visuals on, if volume is way over average. Good for Mean Reverting. Higher Volume tends to higher breakout chances.
Please whisper me for for ideas how to make this better. Its a very simple script, but got some alpha. If you know how to improve, let me know and i will code it into.
Bitcoin - CME Futures Friday Close
This indicator displays the weekly Friday closing price according to the CME trading hours (Friday 4pm CT).
A horizontal line is displayed until the CME opens again on Sunday 5pm CT.
This indicator is based on the thesis, that during the weekend the Bitcoin price tends to mean reverse to the CME closing price of the prior Friday. The level can also act as support/resistance. This indicator gives a visualization of this key level for the relevant time window.
Furthermore the indicator helps to easily identify, if there is an up or down gap in the CME Bitcoin contract.
[KL] Mean Reversion (ATR) StrategyThis strategy will enter into a position when price volatility is relative high, betting that price will subsequently trend in a favourable direction.
Hypothesis : During periods of high price volatility, ATR will divert from its moving average by at least +/- one standard deviation. Eventually, ATR will revert back to the mean. However, just knowing the magnitude of increase/decrease of ATR does not give a trend signal, so we need to introduce a model in this script to predict whether the next bars will be up/down.
Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping or if the drift value is positive.
Entry Conditions : Long position is entered when:
(a) ATR has diverted from mean by one standard deviation, and
(b) trend is predicted to move in our favor.
Exit Condition : When trailing stop loss is hit.
Results from backtesting against VOO (1H timeframe):
- approx 46% win rate over 491 trades, on average holding for 20 hours per trade
- price at the beginning of backtest (Jan. 2015) was $187.52, giving holding period return of ~120% had we not sold in between ("HPR of HODL'ing")
- this strategy gained ~159%, exceeding ~120% HPR of HODL'ing
Roc Mean Reversion (ValueRay)This Indicator shows the Absolute Rate of Change in correlation to its Moving Average.
Values over 3 (gray dotted line) can savely be considered as a breakout; values over 4.5 got a high mean-reverting chance (red dotted line).
This Indicator can be used in all timeframes, however, i recommend to use it <30m, when you want search for meaningful Mean-Reverting Signals.
Please like, share and subscribe. With your love, im encouraged to write and publish more Indicators.
Percentile - Price vs FundamentalsThis is done in the same lines of below scripts
Drawdown-Price-vs-Fundamentals
Drawdown-Range
Instead of using drawdown, here we are only plotting percentile of drawdown. Also added few more fundamental stats to the indicator. Also using part of the code from Random-Color-Generator/ to automatically generate colors. This in turn uses code from @RicardoSantos for convering color based on HSL to RGB
This is how the study can be used:
Study plots percentile of price and each of the listed fundamentals based on history. History can be chose All time or particular window. If any fundamental or price is near 100 - which means it is nearer to its peak. And if something is near its bottom, it is nearer to its 0th percentile.
Price of the stock is considered undervalued based on historical levels when it is below most of the fundamentals. Price is considered overvalued based on historical levels when it is above all the fundamentals. Please note, being undervalued does not guarantee immediate mean reversion. Stocks can stay undervalued for prolonged time and can go further down. Similarly overvalued stock can stay overvalued for prolonged time before correcting itself or justifying the position. Hence, further discretion needs to be used while using this study.
Few examples:
AMZN seems to be trading in range and so are the fundamentals:
MSFT at peak along with half of the fundamentals. But, debt levels are going up along with margins reducing.
LPX is trading at 15% discount whereas most of the fundamentals are at the peak.
FLGT price seems to have gone down further whereas fundamentals look pretty healthy.
MA Visualizer™TradeChartist MA Visualizer is a Moving Average based indicator aimed to visualize price action in relation to the Moving Average in a visually engaging way.
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█ MA Visualizer Features
11 different Moving Averages to choose from the settings to visualize based on MA Visualizer Length (Default - 55 period SMA).
2 Smoothing options (default - 0, 0 uses MA length as Smoothing factor, 1 uses no Smoothing).
4 colour themes to choose from and option to adjust Visualizer Vibrance.
█ Example Charts
1. 1hr chart of OANDA:XAUUSD using 55 period WMA.
2. 15m chart of OANDA:EURUSD using 144 period Tillson T3 MA.
3. 4 hr chart of OANDA:US30USD using 55 period SMMA.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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TradeChartist Vitality™TradeChartist Vitality is a visual indicator that uses both Mean Reversion and Trend Following models to visually show the vitality of Bulls and Bears on chart based on only one factor - Sensitivity in relation to the Vital Support/Resistance derived from the Vitality Bands, Price Momentum and Volatility.
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™TradeChartist Vitality Features:
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Vitality Bands comprising of Vitality Mean and 5 Bull/Bear Limits. These are determined using the user defined Sensitivity from the settings (Very Low, Low, Optimal, High). Higher the sensitivity, shorter the trend and lower the Risk/Reward ratio.
Vital Support and Resistance that decide the Bull and Bear Vitality using colour coded markers on top and bottom of the chart, based on the trend.
Information table that shows the Bull/Bear Vitality, RSI and Price information of the Vitality Mean, Bull Limits 1-5 and Bear Limits 1-5. These prices are colour coded green or red based on the real time closing price trading above or below.
Bull and Bear markers appear after the confirmation of the trend change at the start of the trend.
Option to plot Pivot Points (Traditional and Fibonacci) automatically or based on user defined time frame. These are really helpful in determining the developing price dynamic based on Ranging/Squeezing/Expanding Pivot Points.
Bar Colouring based on Bull/Bear Vitality.
4 Colour Themes for the Bands visuals.
$ signs to help users spot potential zones to Take Profit/Move SL. The $ signs appear above/below the price bars based on the trend at zones of potential price exhaustion, critical support/resistance and other factors.
Vitality Bands Transparency adjustment and Custom colour option for Pivot Points.
Alerts can be created for the following.
Long - Alerts when Bull signal is generated. Use Once Per Bar Close
Long Take Profit - Alerts when $ signs are plotted during Bull Zone. Use Once Per Bar
Short - Alerts when Bear signal is generated. Use Once Per Bar Close
Short Take Profit - Alerts when $ signs are plotted during Bear Zone. Use Once Per Bar
Test of Mean - Alerts when price tests the Volatizer Mean line. Use Once Per Bar
Note : The script doesn't repaint, so the alerts can be used with confidence. To check this, users can do bar replay to check if the plots and markers stay in the same place.
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The indicator can be used for trade entries with filter combinations or can be used as standalone Visualizer for trend confirmations, levels etc.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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TradeChartist Volatizer™TradeChartist Volatizer (Volatility Visualizer) is an exceptionally well designed script that helps visualize Price Volatility and Momentum with the help of various Visual components including Volatizer Bands and Mean line, Support/Resistance levels, Trade Signals and much more. Volatizer's ability to filter trades based on Volatizer Bands, initial Support/Resistance breach, along with the use of External Filter makes it an extremely functional and a useful indicator in addition to its visually engaging design.
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™𝗧𝗿𝗮𝗱𝗲𝗖𝗵𝗮𝗿𝘁𝗶𝘀𝘁 𝗩𝗼𝗹𝗮𝘁𝗶𝘇𝗲𝗿 𝗨𝘀𝗲𝗿 𝗠𝗮𝗻𝘂𝗮𝗹
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𝗩𝗼𝗹𝗮𝘁𝗶𝘇𝗲𝗿 𝗕𝗮𝗻𝗱𝘀
Volatizer Bands comprises of an Upper Band, a Lower Band and a Mean line, that form the important components of this script. These bands are based on consolidation of various factors including comparison of volatility and Higher Time Frame (HTF) Momentum with that of the chart time frame. This helps visualize relative Volatility of the chart's price action in relation to the bands and the mean line. The width and the acceleration of the bands depend upon two of the only user inputs required in this script. They are
Volatizer Length - This is the lookback length required to plot the strength of the price action. This length also determines the Volatizer Levels and Fills that help visualize Volatility and Momentum of the asset observed/traded. Higher the length, longer the trend and higher the Risk:Reward ratio
Sensitivity - Users can choose one of 3 Sensitivity options ( Low , Optimal , High ) to adjust the degree of sensitivity of the Bands' reaction to the price action. High Sensitivity Bands react quicker to the price action based on underlying logic.
Example : 1hr chart of BINANCE:ETHUSDT using 24/High on the left and 24/Low on the right.
𝗩𝗼𝗹𝗮𝘁𝗶𝘇𝗲𝗿 𝗠𝗲𝗮𝗻
Volatizer mean is a critical component of the Bands as it can determine the nature of the price action based on how the price tests the Volatizer Mean. When the price is extremely volatile or trending and when it is influenced by Bull or Bear momentum, the Mean line can be the magnet for Pull Backs or Throw Backs. Mean Touch Points can be enabled or disabled from the settings.
Example - 1hr chart of BINANCE:ETHUSDT clearly showing the use of the Mean line and Orange Mean Touch Points.
Example - 1hr chart of BINANCE:ETHUSDT with Volatizer Levels/Fills enabled on the left and disabled on the right.
𝗜𝗻𝗶𝘁𝗶𝗮𝗹 𝗦𝘂𝗽𝗽𝗼𝗿𝘁/𝗥𝗲𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲 𝗟𝗲𝘃𝗲𝗹𝘀
Volatizer plots automatic Initial Support/Resistance Levels when this option is enabled. This is based on the user input of Length and Sensitivity.
Example - 1hr chart of BINANCE:BTCUSDT with Initial Support/Resistance Levels enabled. Initial range for support/resistance is shown on the chart.
𝗣𝗿𝗼𝗳𝗶𝘁 𝗧𝗮𝗸𝗶𝗻𝗴 𝗭𝗼𝗻𝗲𝘀
Volatizer uses a clever logic that helps detect volatility exhaustion prices and plots $ signs to help the trader take profits or move stop loss levels to secure gains or to exit trade position. This option can be enabled or disabled by checking or unchecking Display Profit Taking Zones . These zones can also be important support/resistance zones based on the trend volatility and momentum.
Example - 1hr chart of BINANCE:BTCUSDT (Setting - 24/Low) showing $ signs to help traders. (Green $ for Bull Zones and Red $ for Bear Zones)
𝗧𝗿𝗮𝗱𝗲 𝗦𝗶𝗴𝗻𝗮𝗹𝘀 𝗮𝗻𝗱 𝗧𝗿𝗮𝗱𝗲 𝗙𝗶𝗹𝘁𝗲𝗿𝘀
The script can also be used to plot Trade Signals automatically with or without the use of Trade Filters. When the price shows bullish or bearish momentum when the price crosses above or below the mean, Bull or Bear plot appears on the chart to signal potential trend change. These signals can be filtered using one, two or all three filters listed below.
Filter Initial S/R Level Breakouts - Plots Signals only when the initial Support/Resistance levels get breached.
Filter using Volatizer Bands - Plots Signals only when the Upper/Lower bands get breached.
External Filter - Plots Signals only if crossover/breakout criteria of External Filter (Oscillatory or Non-Oscillatory Signal) is satisfied.
Example Charts for Trade Signals/ Filters using 1hr chart of NASDAQ:AMD (Setting - 24/Optimal)
1. Trade Signals without any filter
2. Trade Signals using Initial S/R Level Breakout Filter only
3. Trade Signals using Volatizer Bands Filter only
4. Trade Signals using External Filter - MDO (144) with 0 Filter values along with other 2 built in filters
𝗔𝗹𝗲𝗿𝘁𝘀
Alerts can be created using Trading View's Alert Creation box by choosing one of the following Volatizer Conditions.
Long - Alerts when Bull signal is generated. Use Once Per Bar Close
Long Take Profit - Alerts when $ signs are plotted during Bull Zone. Use Once Per Bar
Short - Alerts when Bear signal is generated. Use Once Per Bar Close
Short Take Profit - Alerts when $ signs are plotted during Bear Zone. Use Once Per Bar
Test of Mean - Alerts when price tests the Volatizer Mean line. Use Once Per Bar
Note: The indicator doesn't repaint even though a potential repaint warning appears when creating alerts. This can be confirmed by doing bar replay with vertical lines at various lines and trend change zones to get confidence using the indicator. The vertical lines will stay in the same place on both current time and when running a bar replay.
𝗩𝗼𝗹𝗮𝘁𝗶𝘇𝗲𝗿 𝗩𝗶𝘀𝘂𝗮𝗹𝘀
Visual settings like Colour scheme, Colour Bars, Fill Transparency and Initial Support/Resistance Linewidth can be adjusted/changed from the settings under Volatizer Visuals section.
𝗛𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝗩𝗼𝗹𝗮𝘁𝗶𝘇𝗲𝗿 𝗟𝗲𝗻𝗴𝘁𝗵 𝗮𝗻𝗱 𝗦𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗶𝘁𝘆 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆
1. As mentioned in the manual above, higher the length, longer the trend and higher the Risk:Reward ratio.
2. Sensitivity affects the frequency of the signals in general. Low Sensitivity will generate less frequent signals and High Sensitivity will generate more frequent signals as the Sensitivity affects how quickly the Bands react to the price action.
3. As a rule of thumb, it is recommended to use relevant numbers that seem to work well as Volatizer Length. These can be Fibonacci numbers like 5, 8 , 13, 21, 34, 55, 89, 144 etc. These can also be chart timeframe multipliers that relate to Higher Time Frame (HTF). For example, using 24 on 1hr chart will help see Volatizer Bands based on Daily volatility and momentum, 72 on 15m chart for 4hr trend and so on.
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There are several combinations of settings that can be tested on the asset traded based on timeframe and risk/reward expectations. The indicator can be used for trade entries with filter combinations or can be used as standalone Visualizer for trend confirmations, levels etc.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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HYE Combo Market [Indicator] (Vwap Mean Reversion+Trend Hunter)Indicator version of the strategy:
* Alerts added.
TIPS AND WARNINGS
1-) The standard settings of this combo script is designed and tested with daily timeframe. For lower timeframes, you should change the indicator settings and find the best value for yourself.
2-) Only the mean vwap line is displayed on the graph. For a detailed view, you can delete the "//" marks from the plot codes in the script code.
3-) This is an indicator for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this indicator.
HYE Combo Market [Strategy] (Vwap Mean Reversion + Trend Hunter)In this strategy, I used a combination of trend hunter and vwap mean reversion strategies that I published before.
Trend Hunter Strategy:
Mean Reversion Vwap Strategy:
The results are quite impressive, especially for bitcoin.
While the hodl return for bitcoin was 13419%, the strategy's return in the same period was about 5 times (65000%) of this.
s3.tradingview.com
In this combo strategy, I made some changes to the original settings of the strategies used together and added some more new features.
Trend Hunter Strategy Settings: (Original / Combo)
- Slow Tenkansen Period : 9 / 9
- Slow Kijunsen Period : 26 / 13
- Fast Tenkansen Period : 5 / 3
- Fast Kijunsen Period : 13 / 7
- BB Length : 20 / 20
- BB Stdev : 2 / 2
- TSV Length : 13 / 20
- TSV Ema Length : 7 / 7
* I also added a "vidya moving average" to be used as a confirmation tool to open a long position. (Candle close must be above the vidya line.)
Vwap Mean Reversion Strategy Settings: (Original / Combo)
- Small Vwap : 2 / 8
- Big Vwap : 5 / 10
- Percent Below to Buy : 3 / 2
- RSI Period : 2 / 2
- RSI Ema Period : 5 / 5
- Maximum RSI Level for Buy : 30
* I also added a "mean vwap line" to be used for exits in this part of the strategy. In the original version, when small vwap crossovers big vwap, we close the position, but in this strategy we will wait for the close above the mean vwap.
TIPS AND WARNINGS
1-) The standard settings of this combo strategy is designed and tested with daily timeframe. For lower timeframes, you should change the strategy settings and find the best value for yourself.
2-) Only the mean vwap line is displayed on the graph. For a detailed view, you can delete the "//" marks from the plot codes in the strategy code.
3-) This is a strategy for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this strategy.
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Bu stratejide, daha önce yayınladığım trend avcısı ve vwap ortalamaya geri dönüş stratejilerinin bir kombinasyonunu kullandım.
Sonuçlar özellikle bitcoin için oldukça etkileyici.
Bitcoin için hodl getirisi %13419 iken, stratejinin aynı dönemdeki getirisi bunun yaklaşık 5 katı (%65000) idi.
Bu kombo stratejide, birlikte kullanılan stratejilerin orijinal ayarlarında bazı değişiklikler yaptım ve bazı yeni özellikler ekledim.
Trend Avcısı Strateji Ayarları: (Orijinal / Combo)
- Yavaş Tenkansen Periyodu : 9 / 9
- Yavaş Kijunsen Periyodu : 26 / 13
- Hızlı Tenkansen Periyodu : 5 / 3
- Hızlı Kijunsen Periyodu : 13 / 7
- BB Uzunluğu : 20 / 20
- BB Standart Sapması : 2 / 2
- TSV Uzunluğu : 13 / 20
- TSV Ema Uzunluğu : 7 / 7
* Ayrıca long pozisyon açmak için onay aracı olarak kullanılmak üzere "vidya hareketli ortalama" ekledim. (Mum kapanışı vidya çizgisinin üzerinde olmalıdır.)
Vwap Ortalamaya Dönüş Stratejisi Ayarları: (Orijinal / Combo)
- Küçük Vwap : 2 / 8
- Büyük Vwap : 5 / 10
- Alış İçin Gerekli Fark Oranı : 3 / 2
- RSI Periyodu : 2 / 2
- RSI Ema Periyodu: 5 / 5
- Alış için gerekli maksimum RSI seviyesi : 30
* Stratejinin bu bölümünde pozisyondan çıkışlar için kullanılacak bir "ortalama vwap çizgisi" de ekledim. Orijinal versiyonda, küçük vwap, büyük vwap'ı yukarı kestiğinde pozisyonu kapatıyoruz, ancak bu stratejide, ortalama vwap'ın üzerindeki kapanışı bekleyeceğiz.
İPUÇLARI VE UYARILAR
1-) Bu birleşik stratejinin standart ayarları, günlük zaman dilimi ile tasarlanmış ve test edilmiştir. Daha düşük zaman dilimleri için strateji ayarlarını değiştirmeli ve kendiniz için en iyi değeri bulmalısınız.
2-) Grafikte sadece ortalama vwap çizgisi görüntülenir. Ayrıntılı bir görünüm için strateji kodundaki "plot" ile başlayan satırlarda grafikte görünmesini istediğiniz özelliğin önündeki "//" işaretlerini silebilirsiniz.
3-) Eğitim ve deneysel amaçlı bir stratejidir. Yatırım tavsiyesi olarak değerlendirilemez. Bu stratejiyi kullanarak gerçek piyasa işlem açarken dikkatli olmalı ve kendi risk değerlendirmenizi yapmalısınız.
TradeChartist Catalyst™TradeChartist Catalyst is an elegant script that combines Catalyst Trade Bands and automatic ZigZag/Fibonacci plots using an original logic to help users interact in a visually engaging and meaningful way with the charts.
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™TradeChartist Catalyst features
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1. Catalyst Trade Bands
Catalyst Trade Bands comprises Equilibrium or Mean Bands, Inner Bands, Outer Bands and a Overall Mean Line. Catalyst Trade Bands help visualize the price action in relation to the Equilibrium Bands and clearly show how far away from the mean the current price is. The Trade Bands are of two types - Normal and Weighted. Weighted Bands are very sensitive to price action and a higher Bands length is recommended.
Simple 144 vs Weighted 144 Trade Bands
2. Equilibrium Touch Points
Every time the price touches the Equilibrium, an orange touch point appears on the chart. Normally, the Equilibrium line, for an optimal sample, acts as support or resistance. Price breaching or failing this line usually signals a Pull Back, a Throw Back or a Trend Change based on how the price interacts with it. This can be used with a secondary confirmation like RSI, Stochastic etc. For example, if the price falls back significantly only to touch the Equilibrium Line and fails to test the Overall Mean Line when Stochastic is below 30, this could mean a strong Pull Back rather than a Trend Change as shown in the example chart below.
When price fails the Equilibrium Bands, the fill colour of the Equilibrium bands changes to Bearish colour. If the Overall Mean line is below the Equilibrium bands and is in a reasonable distance, Mean will act as support as shown in the example below. Price failing the mean will test Inner Bands and strong bear momentum could take price to Outer Bands and beyond.
All the components of the Catalyst Trade Bands including the Touch Points can be enabled or disabled from the settings.
3. ZigZag & Fibonacci
Catalyst automatically plots ZigZag and Auto Fibonacci Retracement based on an intelligent logic and can be tweaked by changing the Zigzag & Auto-Fibs Factor from the settings. It also plots Fib ratios and connectors along with price highs and lows of ZigZag. The ratios can be especially useful to visually detect harmonic patterns and also serves as a useful feature for Fibonacci traders.
4. Fibonacci Customisation
Catalyst users can customise Fibonacci type and levels, including levels colour from Catalyst settings. In addition to Auto-Fibs, users can also plot Fibonacci levels based on Days or Candles lookback. This is a very useful feature if the user wants to override Auto-Fibs to suit his/her needs. Users can also reverse the Fibonacci Levels by enabling Reverse from settings.
In the following example chart of OANDA:USDCAD , Fibonacci levels based on 10 days lookback is plotted.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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TradeChartist Trend Splitter ™TradeChartist Trend Splitter is a visual Trend spotting script based on two simple models fused together - Dynamic Volatility Bands and Dynamic Mean Bands. The fusion of these two models based on user defined parameters of length, Volatility Risk and Mean Bands type, along with optional Trend Splitter color bars and Trend background split will make it visually engaging for any trader to understand the price action.
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Trend Splitter User Manual
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Trend Splitter settings has option to enable and disable the Volatility Bands and also the Mean Bands.
Under each heading, user can adjust the parameters to suit the trading style, based on time-frame traded.
Volatility Bands track the price action based on volatility trend lookback (Default - 55, MIn - 5, Max - 337) and also uses a Detector plot based on user defined risk (Default is 2.618, Min - 0.618, Max - 5) to continuously track the price action.
Mean Bands track the Mean values of the price action based on TradeChartist's original Mean Reversion Model based on one of 4 time tested Fib Lengths (Default - 55, Options - 55, 89, 144, 233, 337) and detects the price testing of Mean using Orange touchpoints.
Using Price Action in relation to both Volatility Bands and the Mean Bands, the script creates Mean Bands filtered Trend splits that plot Bull or Bear Trend background.
The Mean Bands Filter can be disabled for Trend Splits by just disabling Mean Bands from the settings. Also the option to display Trend Split background can also be enabled or disabled from the settings.
The settings also includes a useful feature to enable or disable coloured price bars using one of 3 colour themes.
Users can create alerts for Price testing mean, Bull and Bear trends using Long or Short from Trend Splitter's Alert Condition.
The indicator doesn't repaint even though a potential repaint warning appears when creating alerts. This can be confirmed by doing bar replay with vertical lines at various lines and trend change zones to get confidence using the indicator. The vertical lines will stay in the same place on both current time and when running a bar replay.
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Example Charts
1. 5m chart of BINANCE:AXSUSDTPERP using Trend Splitter (144, 2.618, Normal, 55) and TradeChartist Momentum Drift Oscillator (144 with Drift Visualizer). The Trend Splitter and MDO combo work brilliantly on Lower Time Frames and even on 15s/30s charts with MDO length of 144.
Best Practice - Always wait for a very long trend (over 337 bars on both MDO and Trend Splitter before taking a reverse trend trade at either Exhaustion or Super OB/OS zones of MDO) when using very low time-frames.
2. 5m chart of NYSE:PLTR using Trend Splitter (144, 3.618, Normal, 55) connected to TradeChartist Fib Master to plot Automatic Fibs. Just use Trend Identifier of Trend Splitter from Fib Master signal dropdown from settings, having both scripts active on chart.
3. Daily chart of OANDA:XAUUSD using Trend Splitter (using only Mean Bands - Weighted/144) to spot areas of support and resistance at Mean Bands.
Best Practice - Mean Bands can also act as confirmation indicator when used with other Trading View Indicators like RSI, Stohastic, Bollinger Bands etc.
4. Daily chart of COINBASE:ETHUSD using Trend Splitter (55, 0.618, Weighted, 55) connected to TradeChartist Plug and Trade to show Trend Splitter based Entries with Targets and Past Performance to assess the settings parameters in Trend Splitter. Just use Trend Identifier of Trend Splitter from Plug and Trade signal dropdown from settings, having both scripts active on chart.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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