Strategy BackTest Display Statistics - TraderHalaiThis script was born out of my quest to be able to display strategy back test statistics on charts to allow for easier backtesting on devices that do not natively support backtest engine (such as mobile phones, when I am backtesting from away from my computer). There are already a few good ones on TradingView, but most / many are too complicated for my needs.
Found an excellent display backtest engine by 'The Art of Trading'. This script is a snippet of his hard work, with some very minor tweaks and changes. Much respect to the original author.
Full credit to the original author of this script. It can be found here: www.tradingview.com
I decided to modify the script by simplifying it down and make it easier to integrate into existing strategies, using simple copy and paste, by relying on existing tradingview strategy backtester inputs. I have also added 3 additional performance metrics:
- Max Run Up
- Average Win per trade
- Average Loss per trade
As this is a work in progress, I will look to add in more performance metrics in future, as I further develop this script.
Feel free to use this display panel in your scripts and strategies.
Thanks and enjoy :)
Strategy!
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest
This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile.
This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss.
Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.
Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy.
Sample Backtesting results as of 10th June 2022:
Backtesting parameters:
Position size: 10% of equity
Long stop: 1% below entry
Short stop: 1% above entry
Repainting: Off
Smoothing: SMA
Period: 10
8 Hour:
Number of Trades: 1046
Gross Return: 249.27 %
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 28.01 %
Profit Factor (Expectancy): 2.019
Average Loss: 0.33 %
Average Win: 1.69 %
Average Time for Loss: 1 day
Average Time for Win: 5.33 days
1 Day:
Number of Trades: 429
Gross Return: 458.4 %
CAGR Return: 15.76 %
Max Drawdown: 6.37 %
Profit Factor (Expectancy): 2.804
Average Loss: 0.8 %
Average Win: 7.2 %
Average Time for Loss: 3 days
Average Time for Win: 16 days
5 Day:
Number of Trades: 69
Gross Return: 1614.9 %
CAGR Return: 26.7 %
Max Drawdown: 5.7 %
Profit Factor (Expectancy): 10.451
Average Loss: 3.64 %
Average Win: 81.17 %
Average Time for Loss: 15 days
Average Time for Win: 85 days
Analysis:
The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.
The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.
Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account.
Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup.
As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live.
Original indicator links:
On chart version -
Oscillator version -
Update - 27/06/2022
Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone:
1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model.
2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges)
3) Adjust account balance to 10,000 - since most of us are not millionaires.
The rest of the backtesting parameters are comparable to previous results:
Backtesting parameters:
Initial capital: 10000 dollars
Position size: 10% of equity
Long stop: 2% below entry
Short stop: 2% above entry
Repainting: Off
Smoothing: SMA
Period: 10
Slippage: 10 ticks
Commission: 0.1%
This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings:
8 Hour:
Number of Trades: 1082
Gross Return: 233.02%
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 25.6%
Profit Factor (Expectancy): 1.627
Average Loss: 0.46 %
Average Win: 2.18 %
Average Time for Loss: 1.33 day
Average Time for Win: 7.33 days
Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT [Loxx]STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT is the backtest strategy for "STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones " seen below:
Included:
This backtest uses a special implementation of ATR and ATR smoothing called "True Range Double" which is a range calculation that accounts for volatility skew.
You can set the backtest to 1-2 take profits with stop-loss
Signals can't exit on the same candle as the entry, this is coded in a way for 1-candle delay post entry
This should be coupled with the INDICATOR version linked above for the alerts and signals. Strategies won't paint the signal "L" or "S" until the entry actually happens, but indicators allow this, which is repainting on current candle, but this is an FYI if you want to get serious with Pinescript algorithmic botting
You can restrict the backtest by dates
It is advised that you understand what Heikin-Ashi candles do to strategies, the default settings for this backtest is NON Heikin-Ashi candles but you have the ability to change that in the source selection
This is a mathematically heavy, heavy-lifting strategy with multi-layered adaptivity. Make sure you do your own research so you understand what is happening here. This can be used as its own trading system without any other oscillators, moving average baselines, or volatility/momentum confirmation indicators.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
What is R-squared Adaptive?
One tool available in forecasting the trendiness of the breakout is the coefficient of determination ( R-squared ), a statistical measurement.
The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average .
R-squared is used here to derive a T3 factor used to modify price before passing price through a six-pole non-linear Kalman filter.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Ultimate Hyper Scalper Strategy [PrismBot] [Lite]💎 Prism Core Initial Release
ver 3.4.r379
This strategy is built on on a modified and reworked older version of the Waddah Attar Explosion strategy. It contains several confluence indicators such as Triple EMAs, volume, consolidation, ADX, and Bull Bear Power.
The Waddah Attar Indicator strategy is based on the following conditions:
LONG
trend is up
explosion line is greater than the dead zone line or a set threshold
SHORT
trend is down
explosion line is greater than the dead zone line or a set threshold
While this is a very simple strategy on the surface, the WAE indicator is great for finding strong trending markets and as it can be considered high frequency, can be paired with other confluence such as the ADX indicator to find high volatility movements.
This strategy also contains a myriad of custom order features, such as controlling the type of position sizes you open with Risk %, volatility, ATR based stops, and much more.
If you have any questions about this strategy or its features, you can ask in the comments below, or DM me here on Tradingview.
The Ultimate Backtest - Fontiramisu█ OVERVIEW
The Ultimate Backtest allows you to create an infinite number of trading strategies and backtest them easily and quickly.
You can leverage the trading setup you created with the tradingview's real-time alert system.
The tool is constantly being improved to accommodate more in-house indicators in order to imagine more trading strategies.
█ HOW IT WORKS.
The tool is divided into 3 main parts:
1. The indicators:
These are the indicators that you will be able to set up to create your setups.
Example: rsi, exponential moving average, home made resistance/support indicator etc.
We are working to add more and more in-house indicators to multiply the trading strategies.
2. The entry/exit strategy:
The entry/exit trades management is a central point of the strategy.
Here we propose several ways to take profits and in-house optimizations to enter a position.
3. The setup: the combination of indicators
Here it is up to you to create your own recipe.
You combine the different indicators set up above to make a real strategy.
Example: RSI Divergence + Location on a support.
Let's look at this in more detail.
Below is a description of all sections
█ 1. THE INDICATORS
TREND: MA (moving average) -->
Set up a moving average from multiple methods (sma, ema, smma...) of the type and length you want.
> A long is taken if the price is above the MA.
> A short is taken if the price comes below the MA.
You can set up a smoothing MA from the existing moving average and use it in the same way.
ENVELOPE: SUPER TREND -->
The supertrend is a trend following indicator. It clearly describes the distinction between downtrends and uptrends with a red or green direction. It is calculated according to the ATR and a factor.
> A long is taken when the direction is green and the price touches the supertrend support line.
> A short is taken when the direction is red and the price touches the supertrend resistance line.
ENVELOPE: BOLLINGER BAND -->
Bollinger bands are used to evaluate the volatility and probable evolution of prices, here we exploit the envelope
> A long is taken if the price crosses the lower band.
> A short is taken if the price crosses the upper band.
CLOUD: ICHIMOKU -->
The Ichimoku cloud aims to identify the direction and reversal points of dominant market trends. It displays support and resistance levels.
> A long is taken when the price enters the green ichimoku cloud.
> A short is taken when the price enters the red ichimoku cloud.
MOMENTUM: MACD ZERO LAG / MACD / RSI -->
RSI (Relative Strength Index) reflects the relative strength of upward movements, compared to downward movements.
MACD (Moving Average Convergence Divergence) is a momentum indicator that follows the trend and shows the correlation between two moving averages of the asset price.
MACD ZERO LAG is calculated in the same way except that the exponential moving averages that make up the calculation do not lag.
> A long is taken on a potential bullish divergence.
> A short is taken on a potential bearish divergence.
For now, with these indicators, we only take a trade based on divergences but we will add overbuy/oversell etc.
MOMENTUM: MA SLOPE -->
This house indicator allows you to use the slope of a moving average as a measure of momentum.
Define the length of the moving average whose slope we will take.
We then take a fast ma of the slope then a slow ma (You define the lengths with the parameters)
The tool foresees a subtraction between the slow and fast ma to have another interpretation of the slope.
This indicator is available and can be viewed freely on my tradingview profile.
> A long is taken when there is a potential bullish divergence on the fast/slow MA or the difference.
> A short is taken when there is a potential bear divergence on the fast/slow MA or the difference.
RESISTANCE: R/S FONTIRAMISU -->
An in-house indicator that shows resistances and supports according to the chosen parameters.
Indicator available and can be viewed freely on my tradingview profile.
> A long is taken when the price arrives on a support.
> A short is taken when the price arrives on a resistance.
-----
MOMENTUM DIVERGENCE -->
Section used to set the divergence detection.
The first field allows you to select which momentum you want to calculate the divergence on.
PIVOT DETECTION -->
Used to calculate top and dip on the chart, it is used with divergences/resistances/enter-exit optimizations....
Default parameters are: Deviation: 2.5, Depth: 10.
█ 2. STRATEGY FOR ENTERING/EXITING TRADES.
STRATEGY: TP/SL -->
Enter/Exit Trade Mode" field: The first field allows you to choose between two modes:
1. TP/SL Mode:
This mode allows you to take entries with take profits that you define afterwards with the TP1 and TP2 parameters .
> The stop loss is calculated automatically by taking the last dip if it is a long and the last top if it is a short.
> You can add a "Stop Loss % Offset" which will increase the size of the stop loss by the % value you set.
> If you activate TP2, the profit taking is split between TP1 and TP2, you can select the percentage of profit taking split between TP1 and TP2 via the "Percent Exit Profit TP1" field.
> The "TPX Multiplier" fields allow you to define the desired Risk Reward, if = 1 then RR = 1/1.
> A Trailing stop option is available, if active then the profit take will be split between TP1 and Trailing stop.
For the moment you can choose between the two MA's set up above to serve as trailing stop:
> In long, if the price goes below the MA then you take the profit (or the loss)
> In short, if the price goes above the MA then you take the profit (or the loss)
2. ONLY BUY/SELL:
Here the take profits are not taken into account, we only have an alternation between the long and the shorts.
The trailing stop applies to this mode and can be interesting depending on the use.
STRATEGY: SETUP OPTIMIZER (FP) -->
Here we have 3 home made optimization tools to take more relevant trades.
1. FAVORABLE ENTRY FROM PIVOT.
Here the tool will favor entries with interesting locations depending on dips and tops before.
A red cross with "FP" will appear on the chart each time a trade does not meet this condition.
2.STOP LOSS MAX (SL).
Will only take trades where the stop loss is maximum at X%.
A red cross with "%SL" will appear on the chart each time a trade does not meet this condition.
3. MOVE ALREADY TRADED.
Will not take several trades in the same move.
This can avoid cascading losing trades on some setups.
A red cross with "MT" will appear on the chart each time a trade does not meet this condition.
█ 3. THE SETUP: THE COMBINATION OF INDICATORS
Here, let your creativity speak.
You are free to assemble the indicators in the following way:
The conditions defined inside a group (group1/group2/group3) are combined to each other via an OR operator .
Example, if "cond01 = Momentum DIv" and "cond02 = Res/Sup Location", then trades will be triggered if one of the two conditions is met.
The conditions defined between several groups are multiplied via the AND operator .
Example, if "cond01 = Momentum DIv" and "cond12 = Res/Sup Location", then trades are taken if both conditions are met at the same time.
ALL CONDITIONS:
> NONE
No conditions selected.
> Momentum Div
Triggers when a potential divergence occurs on the selected momentum (in the divergence section).
> Momentum Div UT Sup
Triggers when a potential divergence occurs on the selected momentum (in the divergence section) in the upper timeframe.
The upper timeframe of the momentum is calculated directly in the code by multiplying the set parameters by 4 (fastlenght/slowlenght...).
> Multi MA
It is set in the "Trend: MA" section and is triggered by the conditions mentioned in the "INDICATORS" section.
> Smooting MA
Is set in the "Trend: MA" section and is triggered by the conditions mentioned in the "INDICATORS" section.
> Super Trend Env
Is set in the "ENVELOPE: SUPER TREND" section and is triggered by the conditions mentioned in the "INDICATORS" section.
> BB Env
It is set in the "ENVELOPE: BOLLINGER BAND" section and is triggered by the conditions mentioned in the "INDICATORS" section.
> Ichimoku Cloud
Is set in the "CLOUD: ICHIMOKU" section and is triggered by the conditions mentioned in the "INDICATORS" section.
> Res/Sup Location
Is set in the "RESISTANCE: R/S" section and is triggered by the conditions mentioned in the "INDICATORS" section.
3ngine Global BoilerplateABOUT THE BOILERPLATE
This strategy is designed to bring consistency to your strategies. It includes a macro EMA filter for filtering out countertrend trades,
an ADX filter to help filter out chop, a session filter to filter out trades outside of desired timeframe, alert messages setup for automation,
laddering in/out of trades (up to 6 rungs), trailing take profit , and beautiful visuals for each entry. There are comments throughout the
strategy that provide further instructions on how to use the boilerplate strategy. This strategy uses `threengine_global_automation_library`
throughout and must be included at the top of the strategy using `import as bot`. This allows you to use dot notation
to access functions in the library - EX: `bot.orderCurrentlyExists(orderID)`.
HOW TO USE THIS STRATEGY
1. Add your inputs
There is a section dedicated for adding your own inputs near the top of the strategy, just above the boilerplate inputs
2. Add your calculations
If your strategy requires calculations, place them in the `Strategy Specific Calculations` section
3. Add your entry criteria
Add your criteria to strategySpecificLongConditions (this gets combined with boilerplate conditions in longConditionsMet)
Add your criteria to strategySpecificShortConditions (this gets combined with boilerplate conditions in shortConditionsMet)
Set your desired entry price (calculated on every bar unless stored as a static variable) to longEntryPrice and shortEntryPrice. ( This will be the FIRST ladder if using laddering capabilities. If you pick 1 for "Ladder In Rungs" this will be the only entry. )
4. Plot anything you want to overlay on the chart in addition to the boilerplate plots and labels. Included in boilerplate:
Average entry price
Stop loss
Trailing stop
Profit target
Ladder rungs
Moon Phases Strategy with CCI EXTRIME TPHELLO TO ALL ASTROLGY TRADING LOVERS
***im not a native english speaker and im not going to google translte it so soory for mastakes ****
this is an amzing script of moon cycle strategy
for long -
price need to be above MA
it will buy in full moon and will sell at new moon
i added an extrime CCI TP that if cci is over bought above 200 line it will close position- it cant be edited out so enjoy it.
for short-
price need to be below MA
it will short when new moon and buy back when fullmoon
i added an extrime CCI tp that if cci is oversold under -200 line it will close position - it cant be edited out so enjoy it.
just edit the new moon Reference date by your UTC TIME!!! ׂ( GOOGLE 'NEW MOON DATE')
לכל אוהבי האסטרולוגיה ומסחר בכוכבים
סקריפט פשוט מעולה!
ללונג- האסטרטגיה קונה כאשר המחיר מעל הממוצע ויש ירח מלא-היא מוכרת כאשר יש ירח חדש או כאשרס.ס.י חוצה את קו ה200
בשורט היא עושה ההפך ומוכרת כאשר יש ירח חדש והמחיר מתחת לממוצע-היא סוגרת את הפוזציה כאשר יש ירח מלא או כאשר ס.ס.י חוצה מטה את רמת המינוס 200
אנא ערכו את התאריך רפרנס לירח לפי אזור הזמן שלכם חפשו בגוגל ''תאריך ירח חדש'.
BACKTEST RETURNS SOOOOOO GOOOOD !
הבאק טסטים חוזרים מושלמים
trade with the stars and rip markets
Swing Failure Reversal StrategyThis strategy is using Swing Failure Patterns as a reversion indicator.
The strategy automatically adapts itself to the timeframe of the current chart.
Swing Failure Pattern occurs when the price trend fails to set new highs in uptrend or meet new lows in a downtrend. This pattern helps traders decide when to enter and exit the market. Usually, traders enter in the downtrend i.e. lower price highs and lower price lows, and exit in the uptrend situation i.e. higher price highs and higher price lows. Thus, traders go against the current trend. This helps the traders take advantage of early trend reversal indicators.
Types of Failure Swing :
Failure Swing Top: This occurs when the stock price goes higher whereas the RSI fails to make a higher high and falls below the recent fail point. The Fail Point is where the RSI line is below the recent swing low. This Failure Swing indicates a short position.
Failure Swing Bottom: This occurs when the stock price gets lower whereas RSI fails to make a lower low and rises over the recent fail point. Fail point is the point where the RSI line is above the recent swing high. This Failure Swing indicates a long position.
Crypto_Troll_Turtle_StrategyTurtle Strategy for high marketcap cryptocurrencies
I'm glad to launch my strategy which is based on
moving averages / bollinger bands / RSI and volume
It's basically made for scalping with an interesting return over the last two years and a perspectively low drawdown
if you're interested in the strategy and you want to use it for futures trading you can contact me for a money & risk management rules that you can use and prevent you from a huge loss !! it's for free don't worry xD you can find my contact in the author's instructions' label
The optimal timeframe to use is 1H
I'll be trying to launch telegram signals for this strategy as soon as possible for the following pairs: BTCUSDT ETHUSDT BNBUSDT timeframe: 1H
I'm open to all reviews ! thanks !
5-8-13 EMAs Strategy (Andrew's Trading Channel)============
ENGLISH
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- Description:
This strategy was designed by "Andrew's Trading Channel" (credits to him for the base strategy).
A lot of improvements have been added to the strategy, more conditions, trailing stop, custom stop loss and take profit, everything explained below.
- CONDITIONS FOR ENTERING A LONG:
EMA 5 crossovers EMA 8.
- EXIT LONG:
EMA 8 crossovers EMA 8 and closing price goes below EMA 13.
- CONDITIONS FOR ENTERING SHORT:
EMA 8 crossovers EMA 5.
- EXIT SHORT:
EMA 5 crossovers EMA 8 and closing price goes above EMA 13.
- Visual:
All EMAs are visible (5, 8 and 13 periods) with different and customizable colors/width.
Position start price, take profit, stop loss and trailing stop (if present) are shown automatically.
Background color shows green when LONG conditions are met (and of course, position is opened on the next candle), same for SHORT but red.
- Usage and recommendations:
As this is a coded strategy, you don't even have to check for indicators, just open and close trades as the strategy shows.
There're various customizable settings like optional take profit/stop loss, trailing stop (both based on ATR or any of the EMAs), open only LONGs/SHORTs or both, date range...
Take profit and stop loss ATR default values have been tested for scalping on 5 min charts, however feel free to check strategy results and increase the winning rate/profit for your favorite asset.
- Customization:
As usual I like to make as many aspects of my indicators/strategies customizable, indicators, colors etc., feel free to ask if you feel that something that should be configurable is missing or if you have any ideas to optimize the strategy.
============
ESPAÑOL
============
- Descripción:
Esta estrategia fue diseñada por "Andrew's Trading Channel" (créditos a él por la estrategia base).
Se han añadido muchas mejoras a la estrategia, más condiciones, trailing stop, stop loss y take profit personalizados, todo explicado a continuación.
- CONDICIONES PARA ENTRAR EN LONG:
Cruce de EMA 5 con EMA 8 ascendente.
- SALIR DE LONG:
Cruce de EMA 8 con EMA 5 ascendente y el precio de cierre se sitúa por debajo de la EMA 13.
- CONDICIONES PARA ENTRAR EN SHORT:
Cruce de EMA 8 con EMA 5 ascendente.
- SALIR DE SHORT:
Cruce de EMA 5 con EMA 8 ascendente y el precio de cierre se sitúa por encima de la EMA 13.
- Visual:
Todas las EMAs son visibles (5, 8 y 13 períodos) con colores/anchos y personalizables.
El precio de inicio de la posición, el take profit, el stop loss y el trailing stop (si están presentes) se muestran automáticamente.
El color de fondo es verde cuando se cumplen las condiciones de LONG (y por supuesto, la posición se abre en la siguiente vela), lo mismo para SHORT pero en rojo.
- Uso y recomendaciones:
Como esta es una estrategia programada, ni siquiera tienes que comprobar los indicadores, sólo abrir y cerrar las operaciones como te muestra la estrategia.
Hay varios ajustes personalizables como el take profit/stop loss opcional, el trailing stop (ambos basados en el ATR o en cualquiera de las EMAs), abrir sólo LONGs/SHORTs o ambos, rango de fechas...
Los valores por defecto del take profit y el stop loss ATR han sido probados para scalping en gráficos de 5 minutos, sin embargo, siéntase libre de comprobar los resultados de la estrategia y aumentar la tasa de ganancia / beneficio para su activo favorito.
- Personalización:
Como siempre me gusta hacer personalizables todos los aspectos de mis indicadores/estrategias, indicadores, colores, etc., siéntase libre de preguntar si cree que falta algo que debería ser configurable o si tiene alguna idea para optimizar la estrategia.
Buy and hold strategyA simple buy and hold strategy. A short or a long position can be chosen. The start date will determine the date where your position will start and end date is the date it will end. This works well as a baseline to your other existing strategies since buy and hold is just the simplest strategy available.
Top & Bottom Strategy by The Accumulation ZoneHey Guy's welcome back to another Strategy based on a popular Indicator!
Indicators used in this Strategy:
-> Top and Bottom by ceyhun (Basic Settings)
-> Volatility Oscillator by verifid (Basic Settings)
Long Entry Criteria:
1. New Buy Signal from the Top & Bottom Indicator
2. Bullish Spike to the upside on the Volatility Oscillator ( above the BB Bands)
3. Enter Long (SL based on ATR, RR 1.5)
Short Entry Criteria:
1. New Sell Signal from the Top & Bottom Indicator
2. Bearish Spike to the downside on the Volatility Oscillator ( below the BB Bands)
3. Enter Short (SL based on ATR, RR 1.5)
Optional Filters:
- Session Filter
- Date Filter
- EMA Filter
IMPORTANT use this only for testing purpose. Don't Risk any Money. For educational Purpose Only!
Breakout Finder Strategy by The Accumulation ZoneThe Breakout Strategy:
Indicators used:
Least Squared Moving Average by Tradingview
Smoothed Moving Average by Tradingview
MACD Support Resistance by venkatachari_n
About this Strategy:
This strategy is based on spotting a particular activity pattern involving the above listed indicators:
A fast moving average that will track closely with price while still smoothing out some price chop
A slower least squared moving average to help gauge short-term momentum
MACD Support and Resistance to help identify longer-term trends and potentially serve to also guide directional bias
If all entry conditions are met, the strategy enters a position. As well as sending an alert message for the Entry, TP/SL Signals
Long Condition:
Price close above MACD S/R Line
SMMA crossed MACD S/R Line to the upside
LSMA crossed MACD S/R Line to the upside
Short Condition:
Price close below MACD S/R Line
SMMA crossed MACD S/R Line to the downside
LSMA crossed MACD S/R Line to the downside
Strategy Settings
SL based on ATR Bands (0.9 ATR Multiplier recommended*)
TP based on RR (1.5 RR recommended*)
Optional EMA Filter (If set to 0 -> disabled)
Session Filter
Custom Strategy Backtesting Dashboard (Risk = 5%*)
*Recommended for a Daily BTC/USDT Chart
Gap Reversion StrategyToday I am releasing to the community an original short-term, high-probability gap trading strategy, backed by a 20 year backtest. This strategy capitalizes on the mean reverting behavior of equity ETFs, which is largely driven by fear in the market. The strategy buys into that fear at a level that has historically mean reverted within ~5 days. Larry Connors has published useful research and variations of strategies based on this behavior that I would recommend any quantitative trader read.
What it does:
This strategy, for 1 day charts on equity ETFs, looks for an overnight gap down when the RSI is also in/near an oversold position. Then, it places a limit order further below the opening of the gapped-down day. It then exits the position based on a higher RSI level. The limit buy order is cancelled if the price doesn't reach your limit price that day. So, the larger you make the gap and limit %, the less signals you will have.
Features:
Inputs to allow the adjustment of the limit order %, the gap %, and the RSI entry/exit levels.
An option to have the limit order be based on a % of ATR instead of a % of asset price.
An optional filter that can turn-off trades when the VIX is unusually high.
A built in stop.
Built in alerts.
Disclaimer: This is not financial advice. 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. 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!
SuperIchi StrategyTRADE CONDITIONS
Long entry:
Tenkan-Sen is above Kijun-Sen (blue line above red line)
Price closes above both Tenkan-Sen and Kijun-Sen (price closes above both blue and red lines)
Tenkan-Sen and Kijun-Sen is above Senkou Span (both blue and red lines are above cloud)
Senkou Span is green (cloud is green)
Price pulled back and closed below both Tenkan-Sen and Kijun-Sen within last X (configurable in settings) candles (price pulled back below blue and red lines)
Short entry:
Tenkan-Sen is below Kijun-Sen (blue line below red line)
Price closes below both Tenkan-Sen and Kijun-Sen (price closes below both blue and red lines)
Tenkan-Sen and Kijun-Sen is below Senkou Span (both blue and red lines are below cloud)
Senkou Span is red (cloud is red)
Price pulled back and closed above both Tenkan-Sen and Kijun-Sen within last X (configurable in settings) candles (price pulled back above blue and red lines)
Risk management:
Each trade risks 2% of account (configurable in settings)
SL size determined by swing low/high of previous X candles (configurable in settings) or using the ATR override (configurable in settings) where the max of swing high/low or ATR value will be used to calculate SL
TP is calculated by Risk:Reward ratio (configurable in settings)
TIPS
Timeframe: I have found best results running on anything 5M and above
CREDITS
SuperIchi by LuxAlgo
The Impossible TraderTHE IMPOSSIBLE TRADER
A simple, but effective High Freq Strategy script based on MACD or RSI trend, with extra customizable Alert Messages for Bots.
WHAT IT DOES
This script (works best at lower TimeFrames) just follow the trend of MACD or RSI on your asset.
Why it should work? Because in an upper trend, there are more chance of green candles than reds. And in dump trend there are more chance of red candles than greens.
While trend is positive, it will try to open Long orders as fast as possible at market price.
While trend is negative, it will try to open Short orders as fast as possible at market price.
HOW TO SETUP YOUR PREFERENCES
Capital : Insert a % of Margin you want to use for your positions (usually 30% is quite good)
Leverage : Choose leverage based on your plans
Trail Tick @ : This value (in Tick) tell the script "when" the "Trail Stop" order must be activated (from the Entry price)
Offset Tick @ : This is the price (in Tick) from the Trail Stop Price activated. Basically it is a Stop Loss that follow the price at a fixed distance.
SL Tick @ : Set a Stop Loss at amount Tick distance from the Entry Price. (Let's call it a Safety Stop Loss for bad decisions...)
TP Tick @ : Set a Take Profit at amount Tick distance from the Entry Price. Sometimes is better to exit in full Gain than keep positions.
Strategy : You can choose a Only Long, Only Short or Long+Short sametime strategy.
with MACD or RSI : You can try the strategy applied on MACD or applied on customizable RSI EMA
EMA : If you choosed RSI EMA, you can set any value for your testing (usually 80-120 works very nice)
Exit order after bars : Some Exchanges / Brokers apply fixed cost, and a strategy too fast could not be productive. This set will let you to delay the Exit Order on already Opened positions.
Keep Stop Loss active : If you are planning a delay for Exit Orders, sometime could be useful to keep activated Stop Loss.
Strategy Preset : Some preset I've found interesting, with good results.
BackTest Days : If there are too many results and script doesn't work, you can choose a closer range to show results.
EXTRA FEATURES
On Screen Display : OSD will show you some realtime stats about your strategy, like Asset Tick, Trading Period Range, Drawdown, Gains and not closed trade.
Alert Message : You can enter custom Long Entry/Exit and Short Entry/Exit message for your Bots (like AutoView, WunderBit, etc...). When alert is triggered, you can send custom message with {{strategy.order.comment}} in the text field
AutoView Alert Message : If you are user of AutoView, you can generate your calls. Those are tested only on Oanda with index like Sp500, US100, Us30.
TIPS ON USE
Some asset on TradingView require an higher initial capital. Go to this Script Settings -> Properties and rise Initial Capital.
Be aware of commissions and spread when evalutating a strategy. Go to this Script Settings -> Properties and set Commission and Slippage
Trail Stop and Ticks could be difficult to understand, but very profitable. Please take your time and study how it works.
Consider Tick like the minimum movement your asset can do. Ticks occurs "intra-bar", so some of your positions could be closed almost instantly.
Consider Trail Stop like a Stop Loss that keep always the same distance from your positions, but never came back . If you are in gain, say of 10 Ticks, and your Trail have 5 Ticks, this means for sure a close at minimum 5 Ticks from Entry Price.
On Screen Display will show you Ticks for your asset. This will help you on strategy settings, because not all asset responds on the same way.
ONLY LONG EXAMPLE
ONLY SHORT EXAMPLE
Pinbar trailing stop strategyThe strategy finds the nearest pinbar pattern and opens a position (long or short). You choose your take profit and stop loss multiplier.
Take Profit - X times the pinbar size from it's highest point.
Stop loss - X times the pinbar size from it's lowest point.
You can find more detailed screenshots and the source-code on my github page: samgozman/pinbar-strategy-tradingview
Bollinger Bands + EMA 9A 1 minute scalping strategy.
Uses Bollinger Bands (no basis line) and a 9 period EMA.
Waits for price to close below the lower Bollinger Band and the next candle to close bullish above the lower Bollinger Band but below the 9 Period EMA.
If all conditions are met, the script enters a long position with TP at the 9 Period EMA.
Boom Hunter + Hull Suite + Volatility Oscillator StrategyTRADE CONDITIONS
Long entry:
Boom Hunter (leading indicator): Trigger line crosses over Quotient 2 line (white cross over red)
Hull Suite (trend confirmation): Price closed above hull suite line and hull suite is green (represented by horizontal line at -10 in strategy pane)
Volatility Oscillator (volatility confirmation): Volatility spike trigger line is above upper band (represented by horizontal line at -30 in strategy pane)
Short entry:
Boom Hunter (leading indicator): Trigger line crosses under Quotient 2 line (white cross under red)
Hull Suite (trend confirmation): Price closed below hull suite line and hull suite is red (represented by horizontal line at -10 in strategy pane)
Volatility Oscillator (volatility confirmation): Volatility spike trigger line is below lower band (represented by horizontal line at -30 in strategy pane)
Risk management:
Each trade risks 3% of account (configurable in settings)
SL size determined by swing low/high of previous X candles (configurable in settings) or 1 ATR if swing is less than 1 ATR
TP is calculated by Risk:Reward ratio (configurable in settings)
TIPS
Timeframe: I have found good results running on BTC/USDT 5M chart
Note: To help visual identification of trade entries and exits you may wish to add the Hull Suite and Volatility Oscillator to the chart separately. It was not possible to display them in a clear way within a single panel for the strategy. Make sure you set the settings of the auxiliary indicators to match what is in the settings of this indicator if you do decide to add them.
CREDITS
Boom Hunter Pro by veryfid
Hull Suite by InSilico
Volatility Oscillator by veryfid
Price action: Double top/bottom StrategyDouble top and bottom patterns are chart patterns that occur when the underlying investment moves in a similar pattern to the letter "W" (double bottom) or "M" (double top).
In this strategy, I use Pivot High/Low to find Double top and bottom.
Entry long: when Double bottom occur.
Entry short: when Double top occur.
Risk: Reward: You can change % Stop loss and Target pfofit.
Donchian with QQW MOD AND EMA strategythe 1st indicator is E M A , and the 2nd indicator is donchian trend , and the final one is Q Q E MODe , and we have to change some settings , change this E M A length from 9 to 200 ,
and change some settings on donchian indicator , so lets change Donchian channel period from 20 to 30 , and Q Q E MOD on default sittings
for a long signal to be valid , the price must be above 200 E M A ,with NEW blue histogram appeared on our q q e mode , if , donchian trend is red
for a short signal to be valid , the price must be below 200 E M A ,with NEW red histogram appeared on our q q e mode ,if ,donchian trend is green
parabolic sar with ema and rsi, this strategy includes 3 free trading view indicators, with HIGH ken ashee candles , now lets go ahead and add them to our chart ,
the 1st indicator is parabolic saarr and the 2nd indicator is E M A , and the final one is R S I , and we have to change some settings , change this E M A length from 9 to 200 ,
and change some settings on R S I indicator , so lets remove all options except for , the R S I , and the R S I middle band , and parabolic saarr on default sittings , now our strategy is ready , lets go into trading rules .
for a long signal to be valid , the price must be above 200 E M A ,with NEW buy signal from parabolic saarr, if , R S I above the middle 50 line
for a short signal to be valid , the price must be below 200 E M A , with NEW SELL signal from parabolic saarr ,if ,R S I BELOW 50 line
now we can go ahead and take a SHORT position
our stoploss must be above the recent higher high
and the risk to reward ratio will be 2
