Captain Backtest Model [TFO]Created by @imjesstwoone and @mickey1984, this trade model attempts to capture the expansion from the 10:00-14:00 EST 4h candle using just 3 simple steps. All of the information presented in this description has been outlined by its creators, all I did was translate it to Pine Script. All core settings of the trade model may be edited so that users can test several variations, however this description will cover its default, intended behavior using NQ 5m as an example.
Step 1 is to identify our Price Range. In this case, we are concerned with the highest high and the lowest low created from 6:00-10:00 EST.
Step 2 is to wait for either the high or low of said range to be taken out. Whichever side gets taken first determines the long/short bias for the remainder of the Trade Window (i.e. if price takes the range high, bias is long, and vice versa). Bias must be determined by 11:15 EST, otherwise no trades will be taken. This filter is intended to weed out "choppy" trading days.
Step 3 is to wait for a retracement and enter with a close through the previous candle's high (if long biased) or low (if short biased). There are a couple toggleable criteria that we use to define a retracement; one is checking for opposite close candles that indicate a pullback; another is checking if price took the previous candle's low (if long biased) or high (if short biased).
This trade model was initially tested for index futures, particularly ES and NQ, using a 5m chart, however this indicator allows us to backtest any symbol on any timeframe. Creators @imjesstwoone and @mickey1984 specified a 5 point stop loss on ES and a 25 point stop loss on NQ with their testing.
I've personally found some success in backtesting NQ 5m using a 25 point stop loss and 75 point profit target (3:1 R). Enabling the Use Fixed R:R parameter will ensure that these stops and targets are utilized, otherwise it will enter and hold the position until the close of the Trade Window.
Strategy!
buy/sell signals with Support/Resistance (InvestYourAsset) 📣The present indicator is a MACD based buy/sell signals indicator with support and resistance, that can be used to identify potential buy and sell signals in a security's price.
📣It is based on the MACD (Moving Average Convergence Divergence) indicator, which is a momentum indicator that shows the relationship between two moving averages of a security's price.
📣 The indicator also plots support and resistance levels, which can be used to confirm buy and sell signals. The support and resistance can also be used as a stoploss for existing position.
👉 To use the indicator, simply add it to your trading chart. The indicator will plot three sections:
📈 Price and Signals: This section plots the security's price and the MACD buy and sell signals.
📈 MACD Oscillator: This section plots the MACD oscillator, which is a histogram that shows the difference between the two moving averages.
📈 Moving Averages: This section plots the two moving averages that the MACD oscillator is based on.
📈 Support and Resistance: This section plots support and resistance levels, which are calculated based on the security's recent price action.
👉 To identify buy and sell signals, you can look for the following:
📈 Buy signal: When shorter Moving Average crosses over longer Moving Average.
📈 Sell signal: When shorter moving average crosses under longer moving average.
📈 You can also look for divergences between the MACD oscillator and the security's price. A divergence occurs when the MACD oscillator is moving in one direction, but the security's price is moving in the opposite direction. Divergences can be a sign of a potential trend reversal.
👉 To confirm buy and sell signals, you can look for support and resistance levels take a look at below snapshot. If a buy signal occurs at a support level, it is a stronger signal than if it occurs at a random price level. Similarly, if a sell signal occurs at a resistance level, it is a stronger signal than if it occurs at a random price level.
⚡ Here is a example of how to use the indicator to identify buy signal:
☑ Add the indicator to your trading chart.
☑Look for a buy signal when short MA crosses over Long MA.
☑Look for the buy signal to occur at a support level.
☑Enter a long position at the next candle.
☑Place a stop loss order below the support level.
☑Take profit when the MACD line crosses below the signal line, or when the security reaches a resistance level.
⚡ Here is an example of how to use the indicator to identify a sell signal:
☑Add the indicator to your trading chart.
☑Look for a sell signal, when shorter moving average crosses under longer moving average.
☑Look for the sell signal to occur at a resistance level.
☑Enter a short position at the next candle.
☑Place a stop loss order above the resistance level.
☑Take profit when the MACD line crosses above the signal line, or when the security reaches a support level.
✅Things to consider while using the indicator:
📈Look for buy signals in an uptrend and sell signals in a downtrend. This will increase the likelihood of your trades being successful.
📈Place your stop losses below the previous swing low or support for buy signals and above the previous swing high or resistance for sell signals. This will help to limit your losses if the trade goes against you.
📈Consider taking profits at key resistance and support levels. This will help you to lock in your profits and avoid giving them back to the market.
Follow us for timely updates regarding indicators that we may publish in future and give it a like if you appreciate the indicator.
Multimarket Direction indicatorTrendline trading with resistant and support made by me.
Im bad coder and just jump into the tradingview pine script 1 days before so please don't hates me
- I don't know why my script is ded before lol
Signals to trade up
1. The big candles up cross the ema200 (last 5 candles for confirmation)
2. Wait for showing the up triangle.
3. Lookup the resistant/support line. If near the resistant please consider to wait if it break then join the trade
4. Only out trade when it has a down triagle or the candles has big down candles at the resistant/support line.
That it...
RSI Box Strategy (pseudo- Grid Bot)This is a strategy intended primarily for algorithmic traders. It's a pseudo-grid bot that uses a dynamic, volume-weighted grid that only updates when the RSI meets certain conditions. It's also a breakout strategy, whereas normal grid bots are not (typical grid bots sell when a higher grid is reached, whereas this strategy sells when a lower grid is breached under specific conditions). This strategy also sells 100% of pyramiding orders on close.
In a nutshell, the strategy updates its grid to the volume-weighted highest/lowest values of your given source ("src" in the settings) each time that there is a RSI crossunder/crossover. From this range it produces an evenly-spaced grid of five lines, and uses the current source to determine which grid line is closest to the source. Then, if the source crosses over the line directly above the current line, it enters a buy order. If the source crosses under the line directly below the current line, it enters a sell order.
You can configure shorts, source, RSI length, and overbought/oversold levels in the settings.
For the strategy results below: fees are at 0.1% per trade, with order size 1% of equity and a max pyramiding value of 33. For a greater R/R profile, you can increase the order size, which will increase drawdown but potentially yield better results.
Risk Reward Optimiser [ChartPrime]█ CONCEPTS
In modern day strategy optimization there are few options when it comes to optimizing a risk reward ratio. Users frequently need to experiment and go through countless permutations in order to tweak, adjust and find optimal in their data.
Therefore we have created the Risk Reward Optimizer.
The Risk Reward Optimizer is a technical tool designed to provide traders with comprehensive insights into their trading strategies.
It offers a range of features and functionalities aimed at enhancing traders' decision-making process.
With a focus on comprehensive data, it is there to help traders quickly and efficiently locate Risk Reward optimums for inbuilt of custom strategies.
█ Internal and external Signals:
The script can optimize risk to reward ratio for any type of signals
You can utilize the following :
🔸Internal signals ➞ We have included a number of common indicators into the optimizer such as:
▫️ Aroon
▫️ AO (Awesome Oscillator)
▫️ RSI (Relative Strength Index)
▫️ MACD (Moving Average Convergence Divergence)
▫️ SuperTrend
▫️ Stochastic RSI
▫️ Stochastic
▫️ Moving averages
All these indicators have 3 conditions to generate signals :
Crossover
High Than
Less Than
🔸External signal
▫️ by incorporating your own indicators into the analysis. This flexibility enables you to tailor your strategy to your preferences.
◽️ How to link your signal with the optimizer:
In order to be able to analysis your signal we need to read it and to do so we would need to PLOT your signal with a defined value
plot( YOUR LONG Condition ? 100 : 0 , display = display.data_window)
█ Customizable Risk to Reward Ratios:
This tool allows you to test seven different customizable risk to reward ratios , helping you determine the most suitable risk-reward balance for your trading strategy. This data-driven approach takes the guesswork out of setting stop-loss and take-profit levels.
█ Comprehensive Data Analysis:
The tool provides a table displaying key metrics, including:
Total trades
Wins
Losses
Profit factor
Win rate
Profit and loss (PNL)
This data is essential for refining your trading strategy.
🔸 It includes a tooltip for each risk to reward ratio which gives data for the:
Most Profitable Trade USD value
Most Profitable Trade % value
Most Profitable Trade Bar Index
Most Profitable Trade Time (When it occurred)
Position and size is adjustable
█ Visual insights with histograms:
Visualize your trading performance with histograms displaying each risk to reward ratio trade space, showing total trades, wins, losses, and the ratio of profitable trades.
This visual representation helps you understand the strengths and weaknesses of your strategy.
It offers tooltips for each RR ratio with the average win and loss percentages for further analysis.
█ Dynamic Highlighting:
A drop-down menu allows you to highlight the maximum values of critical metrics such as:
Profit factor
Win rate
PNL
for quick identification of successful setups.
█ Stop Loss Flexibility:
You can adjust stop-loss levels using three different calculation methods:
ATR
Pivot
VWAP
This allows you to align risk-reward ratios with your preferred risk tolerance.
█ Chart Integration:
Visualize your trades directly on your price chart, with each trade displayed in a distinct color for easy tracking.
When your take-profit (TP) level is reached , the tool labels the corresponding risk-reward ratio for that specific TP, simplifying trade management.
█ Detailed Tooltips:
Tooltips provide deeper insights into your trading performance. They include information about the most profitable trade, such as the time it occurred, the bar index, and the percentage gain. Histogram tooltips also offer average win and loss percentages for further analysis.
█ Settings:
█ Code:
In summary, the Risk Reward Optimizer is a data-driven tool that offers traders the ability to optimize their risk-reward ratios, refine their strategies, and gain a deeper understanding of their trading performance. Whether you're a day trader, swing trader, or investor, this tool can help you make informed decisions and improve your trading outcomes.
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different
The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How It Works: Detailed Explanation
1. SuperTrend Calculation
The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends.
2. KNN Algorithm
The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points.
3. Signal Generation
Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend.
4. Trading Logic
The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions.
Local picture
█ Trade Direction
The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions.
█ Usage
ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process.
Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages.
Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically.
█ Default Settings
The default settings are configured to offer a balanced approach suitable for most scenarios:
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
These settings can be modified to suit various trading styles and asset classes.
Swing based support and resistanceThis indicator provided here is for identifying swing-based support and resistance levels. It uses two swing lengths, which can be adjusted by the user, to identify swings in the price data. For each swing length, the script calculates the support level as the low of the swing if the trend is up, or the high of the swing if the trend is down. It then plots the support and resistance levels on the chart, along with buy and sell signals.
The buy and sell signals are generated by comparing the current closing price to the support and resistance levels. If the closing price is above the support level, the script plots a buy signal. If the closing price is below the level, the script plots a sell signal.
To use the script, you would first need to add it to your trading platform. Once it is added, you can configure the swing lengths and other parameters to suit your trading style. You can then apply the script to a chart and begin using the support and resistance levels and buy and sell signals to make trading decisions.
Points to be noted while using the indicator:
# The script is designed to be used on a daily chart. However, you can also use it on other timeframes, such as weekly or monthly charts.
# The swing lengths that you choose will depend on your trading style. If you are a swing trader, you may want to use longer swing lengths. If you are a day trader, you may want to use shorter swing lengths.
# Remember, the support and resistance levels generated by the script are not exact price points. They are rather zones where demand and supply can change. Therefore, you should always use other technical analysis tools and indicators to confirm your trading decisions.
# Overall, the script is a useful tool for identifying swing-based support and resistance levels. It can be used by traders of all experience levels to generate trading ideas and improve their trading performance.
To use the swing-based support and resistance indicator with respect to price, you can follow these steps:
=> Identify the support and resistance levels that have been generated by the indicator.
=> Look for price action that is taking place near these levels.
=> If the price is above the level, look for bullish reversals or continuations.
=> If the price is below the level, look for bearish reversals or continuations.
For Example,
=> Bullish reversal: The price is above the level and forms a bullish candlestick pattern, such as a bullish hammer or engulfing pattern.
=> Bullish continuation: The price is above the level and bounces off of the level.
=> Bearish reversal: The price is below the level and forms a bearish candlestick pattern, such as a bearish hammer or engulfing pattern.
=> Bearish continuation: The price is below the level and rejects the level.
$$ You can also use the indicator to identify potential trading entry and exit points. For example, you could enter a long trade when the price breaks above a resistance level and exit the trade when the price retraces to the resistance level. Or, you could enter a short trade when the price breaks below a support level and exit the trade when the price rallies to the support level.
This swing-based support and resistance indicator is just one tool that you can use to trade. You should always use other technical analysis tools and indicators, such as price action and trend analysis, to confirm your trading decisions.
Additionally:
=> Be aware of the overall trend direction. If the trend is up, you should be looking for bullish reversals or continuations. If the trend is down, you should be looking for bearish reversals or continuations.
=> Use a stop loss order to limit your risk on each trade.
=> Consider using a position sizing strategy to manage your risk.
=> Do your own research and backtest any trading strategy before using it in a live trading environment.
Follow us for timely updates regarding future indicators and give it a like if you appreciate the indicator.
OKX: MA CrossoverEXAMPLE Scripte from my stream , how to use OKX webhooks for create strategy on Pine with real\demo trading on your OKX account. This strategy only for test the functional forward orders to OKX. The backtest not included commisions and other.
OKX MA Crossover. This strategy generate JSONs for place orders on the exchange by alerts and webhooks.
In the script 2 function to generate entry and exit orders, and input parameters that needed for setup exchange.
Use it for test this stack and to write you own strategy for trade on the OKX Exchange.
AI SuperTrend - Strategy [presentTrading]
█ Introduction and How it is Different
The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning algorithm, with the tried-and-true SuperTrend indicator. This blend aims to provide traders with more accurate, responsive, and context-aware trading signals.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How it Works: Detailed Explanation
SuperTrend Calculation
Volume-Weighted Moving Average (VWMA): A VWMA of the close price is calculated based on the user-defined length (len). This serves as the central line around which the upper and lower bands are calculated.
Average True Range (ATR): ATR is calculated over a period defined by len. It measures the market's volatility.
Upper and Lower Bands: The upper band is calculated as VWMA + (factor * ATR) and the lower band as VWMA - (factor * ATR). The factor is a user-defined multiplier that decides how wide the bands should be.
KNN Algorithm
Data Collection: An array (data) is populated with recent n SuperTrend values. Corresponding labels (labels) are determined by whether the weighted moving average price (price) is greater than the weighted moving average of the SuperTrend (sT).
Distance Calculation: The absolute distance between each data point and the current SuperTrend value is calculated.
Sorting & Weighting: The distances are sorted in ascending order, and the closest k points are selected. Each point is weighted by the inverse of its distance to the current point.
Classification: A weighted sum of the labels of the k closest points is calculated. If the sum is closer to 1, the trend is predicted as bullish; if closer to 0, bearish.
Signal Generation
Start of Trend: A new bullish trend (Start_TrendUp) is considered to have started if the current trend color is bullish and the previous was not bullish. Similarly for bearish trends (Start_TrendDn).
Trend Continuation: A bullish trend (TrendUp) is considered to be continuing if the direction is negative and the KNN prediction is 1. Similarly for bearish trends (TrendDn).
Trading Logic
Long Condition: If Start_TrendUp or TrendUp is true, a long position is entered.
Short Condition: If Start_TrendDn or TrendDn is true, a short position is entered.
Exit Condition: Dynamic trailing stops are used for exits. If the trend does not continue as indicated by the KNN prediction and SuperTrend direction, an exit signal is generated.
The synergy between SuperTrend and KNN aims to filter out noise and produce more reliable trading signals. While SuperTrend provides a broad sense of the market direction, KNN refines this by predicting short-term price movements, leading to a more nuanced trading strategy.
Local picture
█ Trade Direction
The strategy allows traders to choose between taking only long positions, only short positions, or both. This is particularly useful for adapting to different market conditions.
█ Usage
ToolTips: Explains what each parameter does and how to adjust them.
Inputs: Customize values like the number of neighbors in KNN, ATR multiplier, and moving average type.
Plotting: Visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy/sell orders.
█ Default Settings
The default settings are selected to provide a balanced approach, but they can be modified for different trading styles and asset classes.
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
By combining both machine learning and traditional technical analysis, this strategy offers a sophisticated and adaptive trading solution.
YinYang RSI Volume Trend StrategyThere are many strategies that use RSI or Volume but very few that take advantage of how useful and important the two of them combined are. This strategy uses the Highs and Lows with Volume and RSI weighted calculations on top of them. You may be wondering how much of an impact Volume and RSI can have on the prices; the answer is a lot and we will discuss those with plenty of examples below, but first…
How does this strategy work?
It’s simple really, when the purchase source crosses above the inner low band (red) it creates a Buy or Long. This long has a Trailing Stop Loss band (the outer low band that's also red) that can be adjusted in the Settings. The Stop Loss is based on a % of the inner low band’s price and by default it is 0.1% lower than the inner band’s price. This Stop Loss is not only a stop loss but it can also act as a Purchase Available location.
You can get back into a trade after a stop loss / take profit has been hit when your Reset Purchase Availability After condition has been met. This can either be at Stop Loss, Entry or None.
It is advised to allow it to reset in case the stop loss was a fake out but the call was right. Sometimes it may trigger stop loss multiple times in a row, but you don’t lose much on stop loss and you gain lots when the call is right.
The Take Profit location is the basis line (white). Take Profit occurs when the Exit Source (close, open, high, low or other) crosses the basis line and then on a different bar the Exit Source crosses back over the basis line. For example, if it was a Long and the bar’s Exit Source closed above the basis line, and then 2 bars later its Exit Source closed below the basis line, Take Profit would occur. You can disable Take Profit in Settings, but it is very useful as many times the price will cross the Basis and then correct back rather than making it all the way to the opposing zone.
Longs:
If for instance your Long doesn’t need to Take Profit and instead reaches the top zone, it will close the position when it crosses above the inner top line (green).
Please note you can change the Exit Source too which is what source (close, open, high, low) it uses to end the trades.
The Shorts work the same way as the Long but just opposite, they start when the purchase source crosses under the inner upper band (green).
Shorts:
Shorts take profit when it crosses under the basis line and then crosses back.
Shorts will Stop loss when their outer upper band (green) is crossed with the Exit Source.
Short trades are completed and closed when its Exit Source crosses under the inner low red band.
So, now that you understand how the strategy works, let’s discuss why this strategy works and how it is profitable.
First we will discuss Volume as we deem it plays a much bigger role overall and in our strategy:
As I’m sure many of you know, Volume plays a huge factor in how much something moves, but it also plays a role in the strength of the movement. For instance, let’s look at two scenarios:
Bitcoin’s price goes up $1000 in 1 Day but the Volume was only 10 million
Bitcoin’s price goes up $200 in 1 Day but the Volume was 40 million
If you were to only look at the price, you’d say #1 was more important because the price moved x5 the amount as #2, but once you factor in the volume, you know this is not true. The reason why Volume plays such a huge role in Price movement is because it shows there is a large Limit Order battle going on. It means that both Bears and Bulls believe that price is a good time to Buy and Sell. This creates a strong Support and Resistance price point in this location. If we look at scenario #2, when there is high volume, especially if it is drastically larger than the average volume Bitcoin was displaying recently, what can we decipher from this? Well, the biggest take away is that the Bull’s won the battle, and that likely when that happens we will see bullish movement continuing to happen as most of the Bears Limit Orders have been fulfilled. Whereas with #2, when large price movement happens and Bitcoin goes up $1000 with low volume what can we deduce? The main takeaway is that Bull’s pressured the price up with Market Orders where they purchased the best available price, also what this means is there were very few people who were wanting to sell. This generally dictates that Whale Limit orders for Sells/Shorts are much higher up and theres room for movement, but it also means there is likely a whale that is ready to dump and crash it back down.
You may be wondering, what did this example have to do with YinYang RSI Volume Trend Strategy? Well the reason we’ve discussed this is because we use Volume multiple times to apply multiplications in our calculations to add large weight to the price when there is lots of volume (this is applied both positively and negatively). For instance, if the price drops a little and there is high volume, our strategy will move its bounds MUCH lower than the price actually dropped, and if there was low volume but the price dropped A LOT, our strategy will only move its bounds a little. We believe this reflects higher levels of price accuracy than just price alone based on the examples described above.
Don’t believe us?
Here is with Volume NOT factored in (VWMA = SMA and we remove our Volume Filter calculation):
Which produced -$2880 Profit
Here is with our Volume factored in:
Which produced $553,000 (55.3%)
As you can see, we wen’t from $-2800 profit with volume not factored to $553,000 with volume factored. That's quite a big difference! (Please note previous success does not predict future success we are simply displaying the $ amounts as example).
Now how about RSI and why does it matter in this strategy?
As I’m sure most of you are aware, RSI is one of the leading indicators used in trading. For this reason we figured it would only make sense to incorporate it into our calculations. We fiddled with RSI for quite awhile and sometimes what logically seems to be the right way to use it isn’t. Now, because of this, our RSI calculation is a little odd, but basically what we’re doing is we calculate the RSI, then turn it into a percentage (between 0-1) that can easily be multiplied to the price point we need. The price point we use is the difference between our high purchase zone and our low purchase zone. This allows us to see how much price movement there is between zones. We multiply our zone size with our RSI multiplication and we get the amount we will add +/- to our basis line (white line). This officially creates the NEW high and low purchase zones that we are actually using and displaying in our trades.
If you found that confusing, here are some examples to why it is an important calculation for this strategy:
Before RSI factored in:
Which produced 27.8% Profit
After RSI factored in:
Which produced 553% Profit
As you can see, the RSI makes not only the purchase zones more accurate, but it also greatly increases the profit the strategy is able to make. It also helps ensure an relatively linear profit slope so you know it is reliable with its trades.
This strategy can work on pretty much anything, but you should tweak the values a bit for each pair you are trading it with for best results.
We hope you can find some use out of this simple but effective strategy, if you have any questions, comments or concerns please let us know.
HAPPY TRADING!
Strategy Gaussian Anomaly DerivativeConcept behind this Strategy :
Considering a normal "buy/sell" situation, an asset would be bought in average at the median price following a Gaussian like concept. A higher or lower average trend would significate that the current perceived value is respectively higher or lower than the current median price, which mean that the buyers are evaluating the price underpriced or overpriced.
This behaviour would be even more relevent depending on its derivative evolution.
Therefore, this Strategy setup is based on this Gaussian like concept anomaly of average close positionning compare to high-low average derivative, such as the derivative of the following ploted basic signal : 1-(high+low)/(2*close).
This Strategy can actually be used like a trend change and continuation strength indicator aswell.
In the Setup Signal part :
You can define the filtering of the basis signal "1-(high+low)/(2*close)" on EMA or SMA as you wish.
You can define the corresponding period and the threathold as a mutiply of the average 1/3 of all time value of the basis signal.
You can define the SMA filtering period of the Derivative signal and the corresponding threathold on the same mutiply of the average 1/3 of all time value of the derivative.
In the Setup Strategy part :
You can set up your strategy assesment based on Long and/or Short. You can also define the considered period.
The most successful tuned strategies I did were based on the derivative indicator with periods on the basis signal and the derivative under 30, can be 1 to 3 of te derivative and 7 to 21 for the basis signal. The threathold depends on the asset volatility aswell, 1 is usually the most efficient but 0 to 10 can be relevent depending on the situation I met. You can find an example of tuning for this strategy based on Kering's case hereafter.
I hoping that you will enjoy using this Strategy, don't hesitate to comment, to question, to correct or complete it ! I would be very curious about similar famous approaches that would have already been made.
Thank to you !
Dual-Supertrend with MACD - Strategy [presentTrading]## Introduction and How it is Different
The Dual-Supertrend with MACD strategy offers an amalgamation of two trend-following indicators (Supertrend 1 & 2) with a momentum oscillator (MACD). It aims to provide a cohesive and systematic approach to trading, eliminating the need for discretionary decision-making.
Key advantages over traditional single-indicator strategies:
- Dual Supertrend Validation: Utilizes two Supertrend indicators with different ATR periods and factors to confirm the trend direction. This double-check mechanism minimizes false signals.
- Momentum Confirmation: The MACD histogram acts as a momentum filter, confirming entries and exits, thus adding an extra layer of validation.
- Objective Entry and Exit: The strategy generates buy and sell signals based on a combination of trend direction and momentum, leaving no room for subjective interpretation.
- Automated Trade Management: The strategy includes built-in settings for commission, slippage, and initial capital, automating the trade execution process.
- Adaptability: The strategy allows for easy customization of all its parameters, adapting to a trader's specific needs and varying market conditions.
BTCUSD 8hr chart Long Condition
BTCUSD 6hr chart Long Short Condition
## Strategy, How it Works
The strategy operates on a set of clearly defined rules, primarily focusing on the trend direction confirmed by the Dual-Supertrend and the momentum as indicated by the MACD histogram.
### Entry Rules
- Long Entry: When both Supertrend indicators are bullish and the MACD histogram is above zero.
- Short Entry: When both Supertrend indicators are bearish and the MACD histogram is below zero.
### Exit Rules
- Exit long positions when either of the Supertrends turn bearish or the MACD histogram drops below zero.
- Exit short positions when either of the Supertrends turn bullish or the MACD histogram rises above zero.
### Trade Management
- The strategy uses a fixed commission rate and slippage in its calculations.
- Automated risk management features are integrated to avoid overexposure.
## Trade Direction
The strategy allows for trading in both bullish and bearish markets. Users can select their preferred trading direction ("long", "short", or "both") to align with their market outlook and trading objectives.
## Usage
- The strategy is best applied on timeframes where the trend is evident.
- Users can modify the ATR periods, factors for Supertrends, and MACD settings to suit their trading needs.
## Default Settings
- ATR Period for Supertrend 1: 10
- Factor for Supertrend 1: 3.0
- ATR Period for Supertrend 2: 20
- Factor for Supertrend 2: 5.0
- MACD Fast Length: 12
- MACD Slow Length: 26
- MACD Signal Smoothing: 9
- Commission: 0.1%
- Slippage: 1 point
- Trading Direction: Both
The strategy comes with these default settings to offer a balanced trading approach but can be customized according to individual trading preferences.
Strategy:Reversal-CatcherWhat
This is a plain and vanilla reversal based strategy for intraday (15m) timeframe on Futures prices of the assets.
Now what all it comprises of?
It finds out the dynamic support & resistance from Bollinger Band (20 period, 1.5 std dev).
It finds out the potential divergence of price deviation from 5 period exponential moving average (EMA).
If the previous candle (N-1) shows a divergence it confirms the reversal by checking the present candle (N) to be closed inside the Bollinger Band.
It confirms the momentum by checking RSI shows a crossover/crossunder to oversold (30) / overbought (70) region.
It also confirms whether the trend is up (then only reversal trade to short) or down (then only reversal trade to long). The trend is checked with EMA-21 and EMA-50.
Re-affirmation Condition : It re-affirms the position of two successive candles called as `hhLLong` and `hhLLShort` in the script.
Why
In Indian context, retail participants are pre-dominantly (yes- 80% of Indian daily volume) Options buyers mainly in weekly indices (Nifty, BankNifty, FinNifty, CNXMidcap, Sensex, Bankx .. well everyday is expiry now in India, except -- Thank God -- Saturday & Sunday).
And in Index Options the momentum plays a big role.
If one can catch a good reversal point the potential of high Risk-to-Reward trade (hence earn handsomely) is very likely (please note: there is no holy grail in trading. Nothing works 100%).
So this is the attempt to catch a reversal.
Re-affirmation of Reversal
hhLLong : It's a reversal point after an uptrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLong in script.
hhLLShort : It's a reversal point after a downtrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLShort in script.
Unique-ness
What's unique in it? Why we decided to publicly share this:
Already given the context of The Great Indian Options Buyers community. It should be helpful to them, we believe.
It takes Very Less Number of Trades with High Accuracy . Please check the result in NSE:NIFTY1! in 15m timeframe. 71% accuracy with roughly a trade in a month.
There is no point giving brokers' the brokerages taking 10 trades a day and ending not-so-good EoD. Better lets take less trades with better result possibility. .
Mention
There are many people uses this variation of Bolling Band, 5EMA
Many people use RSI, trends and relative positioning of candles.
--> We are grateful to all of them. It's really difficult to mention everyone's name. But all people somehow influence the thought process. Thanks for all of them.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context : We are not SEBI registered, will never be SEBI registered.
Financial Ratios Fundamental StrategyWhat are financial ratios?
Financial ratios are basic calculations using quantitative data from a company’s financial statements. They are used to get insights and important information on the company’s performance, profitability, and financial health.
Common financial ratios come from a company’s balance sheet, income statement, and cash flow statement.
Businesses use financial ratios to determine liquidity, debt concentration, growth, profitability, and market value.
The common financial ratios every business should track are
1) liquidity ratios
2) leverage ratios
3)efficiency ratio
4) profitability ratios
5) market value ratios.
Initially I had a big list of 20 different ratios for testing, but in the end I decided to stick for the strategy with these ones :
Current ratio: Current Assets / Current Liabilities
The current ratio measures how a business’s current assets, such as cash, cash equivalents, accounts receivable, and inventories, are used to settle current liabilities such as accounts payable.
Interest coverage ratio: EBIT / Interest expenses
Companies generally pay interest on corporate debt. The interest coverage ratio shows if a company’s revenue after operating expenses can cover interest liabilities.
Payables turnover ratio: Cost of Goods sold (or net credit purchases) / Average Accounts Payable
The payables turnover ratio calculates how quickly a business pays its suppliers and creditors.
Gross margin: Gross profit / Net sales
The gross margin ratio measures how much profit a business makes after the cost of goods and services compared to net sales.
With this data, I have created the long and long exit strategy:
For long, if any of the 4 listed ratios,such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is ascending after a quarter, its a potential long entry.
For example in january the gross margin ratio is at 10% and in april is at 15%, this is an increase from a quarter to another, so it will get a long entry trigger.
The same could happen if any of the 4 listed ratios follow the ascending condition since they are all treated equally as important
For exit, if any of the 4 listed ratios are descending after a quarter, such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is descending after a quarter, its a potential long exit.
For example in april we entered a long trade, and in july data from gross margin comes as 12% .
In this case it fell down from 15% to 12%, triggering an exit for our trade.
However there is a special case with this strategy, in order to make it more re active and make use of the compound effect:
So lets say on july 1 when the data came in, the gross margin data came descending (indicating an exit for the long trade), however at the same the interest coverage ratio came as positive, or any of the other 3 left ratios left . In that case the next day after the trade closed, it will enter a new long position and wait again until a new quarter data for the financial is being published.
Regarding the guidelines of tradingview, they recommend to have more than 100 trades.
With this type of strategy, using Daily timeframe and data from financials coming each quarter(4 times a year), we only have the financial data available since 2016, so that makes 28 quarters of data, making a maximum potential of 28 trades.
This can however be "bypassed" to check the integrity of the strategy and its edge, by taking for example multiple stocks and test them in a row, for example, appl, msft, goog, brk and so on, and you can see the correlation between them all.
At the same time I have to say that this strategy is more as an educational one since it miss a risk management and other additional filters to make it more adapted for real live trading, and instead serves as a guiding tool for those that want to make use of fundamentals in their trades
If you have any questions, please let me know !
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
TradeLibrary "Trade"
A Trade Tracking Library
Monitor conditions with less code by using Arrays. When your conditions are met in chronologically, a signal is returned and the scanning starts again.
Create trades automatically with Stop Loss, Take Profit and Entry. The trades will automatically track based on the market movement and update when the targets are hit.
Sample Usage
Enter a buy trade when RSI crosses below 70 then crosses above 80 before it crosses 40.
Note: If RSI crosses 40 before 80, No trade will be entered.
rsi = ta.rsi(close, 21)
buyConditions = array.new_bool()
buyConditions.push(ta.crossunder(rsi, 70))
buyConditions.push(ta.crossover(rsi, 80))
buy = Trade.signal(buyConditions, ta.crossunder(rsi, 40))
trade = Trade.new(close-(100*syminfo.mintick), close +(200*syminfo.mintick), condition=buy)
plot(trade.takeprofit, "TP", style=plot.style_circles, linewidth=4, color=color.lime)
alertcondition(trade.tp_hit, "TP Hit")
method signal(conditions, reset)
Signal Conditions
Namespace types: bool
Parameters:
conditions (bool )
reset (bool)
Returns: Boolean: True when all the conditions have occured
method update(this, stoploss, takeprofit, entry)
Update Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
stoploss (float)
takeprofit (float)
entry (float)
Returns: nothing
method clear(this)
Clear Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
Returns: nothing
method track(this, _high, _low)
Track Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
_high (float)
_low (float)
Returns: nothing
new(stoploss, takeprofit, entry, _high, _low, condition, update)
New Trade with tracking
Parameters:
stoploss (float)
takeprofit (float)
entry (float)
_high (float)
_low (float)
condition (bool)
update (bool)
Returns: a Trade with targets and updates if stoploss or takeprofit is hit
new()
New Empty Trade
Returns: an empty trade
Trade
Fields:
stoploss (series__float)
takeprofit (series__float)
entry (series__float)
sl_hit (series__bool)
tp_hit (series__bool)
open (series__integer)
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
Liquidity Breakout - Strategy [presentTrading]- Introduction and How It Is Different
The Liquidity Breakout Strategy is a unique trading strategy that focuses on identifying and leveraging patterns in market price data. This strategy, mainly inspired by the script "Master Pattern" by LuxAlgo, takes a different approach from many traditional strategies that rely on technical indicators or fundamental analysis. Instead, the Liquidity Breakout is based on the concept of contraction detection and liquidity levels. This approach allows traders to identify potential trading opportunities that other strategies might miss.
BTCUSDT 6h
The strategy is different from other trading strategies because it uses a unique combination of pattern detection, liquidity levels, and user-defined trading direction. This combination allows the strategy to adapt to various market conditions and trading styles, making it a versatile tool for traders.
- Strategy: How It Works
1. Contraction Detection: The strategy uses a lookback period defined by the user (default is 10 bars) to identify contractions in the market. A contraction is a period where the market is consolidating, often followed by a significant price movement. The strategy identifies contractions by finding pivot highs and pivot lows within the lookback period. If a pivot high is lower than the previous pivot high and a pivot low is higher than the previous pivot low, a contraction is detected.
2. liquidity Levels:
What are Liquidity levels? Liquidity levels, also known as liquidity pools or zones, are price levels at which there is a significant amount of trading activity. They are often areas where large institutional traders (like banks or hedge funds) have placed orders. These levels are important because they can act as support or resistance levels, and price often reacts at these levels.
In the context of this strategy, liquidity levels are used to identify potential entry and exit points for trades. When the price reaches a liquidity level, it could indicate a potential trading opportunity. For example, if the price breaks through a liquidity level, it could signal the start of a new trend. On the other hand, if the price approaches a liquidity level and then reverses, it could signal a potential reversal.
The strategy uses these two elements to identify potential trading opportunities. When a contraction is detected, the strategy will look for a breakout in the direction of the trend. If the breakout occurs at a liquidity level, the strategy will execute a trade.
The strategy also allows traders to set their stop loss based on either the Average True Range (ATR) or a fixed percentage. This flexibility allows traders to manage their risk according to their personal risk tolerance and trading style.
- Trade Direction
One of the unique features of the Master Pattern Strategy is the ability to choose the trading direction. Traders can choose to trade in the "Long" direction, the "Short" direction, or "Both". This feature allows traders to adapt the strategy to their personal trading style and market outlook.
For example, if a trader believes that the market is in an uptrend, they can choose to trade only in the "Long" direction. Conversely, if the market is in a downtrend, they can choose to trade only in the "Short" direction. If the trader believes that the market is volatile and there are opportunities in both directions, they can choose to trade in "Both" directions.
- Usage
To use the strategy, traders need to input their preferred settings, including the contraction detection lookback period, liquidity levels, stop loss type, and trading direction. Once these settings are input, the strategy will automatically detect potential trading opportunities and execute trades according to the defined parameters.
- Default Settings
The default settings for the Master Pattern Strategy are as follows:
Contraction Detection Lookback: 10
Liquidity Levels: 20
Stop Loss Type: ATR
ATR Length: 20
ATR Multiplier: 3.0
Fixed Percentage: 0.01
Trading Direction: Both
These settings can be adjusted according to the trader's personal preferences and market conditions. It's recommended that traders experiment with different settings to find the ones that work best for their trading style and goals.
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
SuperTrend Enhanced Pivot Reversal - Strategy [PresentTrading]
- Introduction and How it is Different
The SuperTrend Enhanced Pivot Reversal is a unique approach to trading that combines the best of two worlds: the precision of pivot reversal points and the trend-following power of the SuperTrend indicator. This strategy is designed to provide traders with clear entry and exit points, while also filtering out potentially false signals using the SuperTrend indicator.
BTCUSDT 6hr
ETHBTC 6hr
Unlike traditional pivot reversal strategies, this approach uses the SuperTrend indicator as a filter. This means that it only takes trades that align with the overall trend, as determined by the SuperTrend indicator. This can help to reduce the number of false signals and improve the overall profitability of the strategy.
The Pivot Reversal Strategy with SuperTrend Filter is particularly well-suited to the cryptocurrency market for the reason of High Volatility. This means that prices can change rapidly in a very short time, making it possible to make a profit quickly. The strategy's use of pivot points allows traders to take advantage of these rapid price changes by identifying potential reversal points
- Strategy: How it Works
The strategy works by identifying pivot reversal points, which are points in the price chart where the price is likely to reverse. These points are identified using a combination of the ta.pivothigh and ta.pivotlow functions, which find the highest and lowest points in the price chart over a certain period.
Once a pivot reversal point is identified, the strategy checks the direction of the SuperTrend indicator. If the SuperTrend is positive (indicating an uptrend), the strategy will only take long trades. If the SuperTrend is negative (indicating a downtrend), the strategy will only take short trades.
The strategy also includes a stop loss level, which is set as a percentage of the entry price. This helps to limit potential losses if the price moves in the opposite direction to the trade.
- Trade Direction
The trade direction can be set to "Long", "Short", or "Both". This allows the trader to choose whether they want to take only long trades (buying low and selling high), only short trades (selling high and buying low), or both. This can be useful depending on the trader's view of the market and their risk tolerance.
- Usage
To use the Pivot Reversal Strategy with SuperTrend Filter, simply input the desired parameters into the script and apply it to the price chart of the asset you wish to trade. The strategy will then identify potential trade entry and exit points, which will be displayed on the price chart.
- Default Settings
The default settings for the strategy are as follows:
ATR Length: 5
Factor: 2.618
Trade Direction: Both
Stop Loss Level: 20%
Commission: 0.1%
Slippage: 1
Currency: USD
Each trade: 10% of account equity
Initial capital: $10,000
These settings can be adjusted to suit the trader's preferences and risk tolerance. Always remember to test any changes to the settings using historical data before applying them to live trades.
Volatility Capture RSI-Bollinger - Strategy [presentTrading]- Introduction and how it is different
The 'Volatility Capture RSI-Bollinger - Strategy ' is a trading strategy that combines the concepts of Bollinger Bands (BB), Relative Strength Index (RSI), and Simple Moving Average (SMA) to generate trading signals. The uniqueness of this strategy is it calculates which is a dynamic level between the upper and lower Bollinger Bands based on the closing price. This unique feature allows the strategy to adapt to market volatility and price movements.
The market in Crypto and Stock are highly volatile, making them suitable for a strategy that uses Bollinger Bands. The RSI can help identify overbought or oversold conditions in this often speculative market.
BTCUSD 4hr chart
(700.hk) 3hr chart
Remember, the effectiveness of a trading strategy also depends on other factors such as the timeframe used, the specific settings of the indicators, and the overall market conditions. It's always recommended to backtest and paper trade a strategy before using it in live trading.
- Strategy, How it Works
Dynamic Bollinger Band: The strategy works by first calculating the upper and lower Bollinger Bands based on the user-defined length and multiplier. It then uses the Bollinger Bands and the closing price to dynamically adjust the presentBollingBand value. In the end, it generates a long signal when the price crosses over the present Bolling Band and a short signal when the price crosses under the present Bolling Band.
RSI: If the user has chosen to use RSI for signals, the strategy also calculates the RSI and its SMA, and uses these to generate additional long and short signals. The RSI-based signals are only used if the 'Use RSI for signals' option is set to true.
The strategy then checks the chosen trading direction and enters a long or short position accordingly. If the trading direction is set to 'Both', the strategy can enter both long and short positions.
Finally, the strategy exits a position when the close price crosses under the present Bolling Band for a long position, or crosses over the present Bolling Band for a short position.
- Trade direction
The strategy also includes a trade direction parameter, allowing the user to choose whether to enter long trades, short trades, or both. This makes the strategy adaptable to different market conditions and trading styles.
- Usage
1. Set the input parameters as per your trading preferences. You can choose the price source, the length of the moving average, the multiplier for the ATR, whether to use RSI for signals, the RSI and SMA periods, the bought and sold range levels, and the trading direction.
2. The strategy will then generate buy and sell signals based on these parameters. You can use these signals to enter and exit trades.
- Default settings
1. Source: hlc3
2. Length: 50
3. Multiplier: 2.7183
4. Use RSI for signals: True
5. RSI Period: 10
6. SMA Period: 5
7. Bought Range Level: 55
8. Sold Range Level: 50
9. Trade Direction: Both
- Strategy's default Properties
1. Default Quantity Type: 'strategy.percent_of_equity'
2. commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1: These parameters set the commission and slippage for the strategy. The commission is set to 0.1% of the trade value, and the slippage (the difference between the expected price of a trade and the price at which the trade is executed) is set to 1.
3. default_qty_type = strategy.percent_of_equity, default_qty_value = 15: These parameters set the default quantity for trades. The default_qty_type is set to strategy.percent_of_equity, which means that the size of each trade will be a percentage of the account equity. The default_qty_value is set to 15, which means that each trade will be 15% of the account equity.
4. initial_capital= 10000: This parameter sets the initial capital for the strategy to $10,000.
PresentTrend - Strategy [presentTrading]- Introduction and how it is different
The PresentTrend strategy is a unique custom trend-following strategy. This combination allows the strategy to take advantage of both short-term and long-term market trends, making it suitable for various market conditions.
BTCUSDT 4hr chart
(700.hk) 3D chart
- Strategy, How it Works
RSI or MFI: The first part uses a custom indicator based on either the Relative Strength Index (RSI) or the Money Flow Index (MFI). The indicator calculates a PresentTrend value, which generates buy and sell signals based on its crossover and crossunder, indicating potential trend reversals.
ATR: The second part is a popular trend-following indicator that uses the Average True Range (ATR).
The strategy enters a long position when all buy signals from both strategies are true, and a short position when all sell signals are true. This ensures trades are entered when both short-term and long-term trends align, potentially increasing the strategy's reliability.
- Trade direction
The strategy also includes a trade direction parameter, allowing the user to choose whether to enter long trades, short trades, or both. This makes the strategy adaptable to different market conditions and trading styles.
- Usage
1. Set the input parameters for the custom trend-following strategy.
2. Choose whether to use the RSI or MFI for the custom strategy.
3. Choose the trade direction: long, short, or both.
4. The strategy will generate buy and sell signals based on the conditions of both strategies.
5. Enter a trade when a buy or sell signal is generated, depending on the chosen trade direction.
Please note that this strategy is meant to be a tool to aid in your trading decisions and not a standalone trading system. Always use proper risk management and make sure to test the strategy thoroughly before using it in live trading.
- Default settings
1. Source: 'hlc3', a balanced price level for calculations.
2. Length: 14, a common setting for many technical indicators.
3. Multiplier: 1.618 (the golden ratio), used in calculating the upper and lower thresholds.
4. RSI or MFI: Set to use MFI by default, both are momentum indicators.
5. Trade Direction: 'Both', allowing for both long and short trades.
The default settings are designed to provide a balanced approach to trend detection. However, these can be adjusted based on the user's preferences and the specific characteristics of the market being traded.
- Strategy's default Properties
1. Default Quantity Type: 'strategy.percent_of_equity'
2. commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1: These parameters set the commission and slippage for the strategy. The commission is set to 0.1% of the trade value, and the slippage (the difference between the expected price of a trade and the price at which the trade is executed) is set to 1.
3. default_qty_type = strategy.percent_of_equity, default_qty_value = 10: These parameters set the default quantity for trades. The default_qty_type is set to strategy.percent_of_equity, which means that the size of each trade will be a percentage of the account equity. The default_qty_value is set to 10, which means that each trade will be 10% of the account equity.
4. initial_capital= 10000: This parameter sets the initial capital for the strategy to $10,000.
Risk to Reward - FIXED SL BacktesterDon't know how to code? No problem! TradingView is an excellent platform for you. ✅ ✅
If you have an indicator that you want to backtest using a risk-to-reward ratio or fixed take profit/stop loss levels, then the Risk to Reward - FIXED SL Backtester script is the perfect solution for you.
introducing Risk to Reward - FIXED SL Backtester Script which will allow you to test any indicator / Signal with RR or Fixed SL system
How does it work ?!
Once you connect the script to your indicator, it will analyze your entry points and perform calculations based on them. It will then open trades for you according to the specified inputs in the script settings.
HOW TO CONNECT IT to your indicator?
simply open your indicator code and add the below line of code to it
plot(Signal ? 100 : 0,"Signal",display = display.data_window)
Replace Signal with the long condition from your own indicator. You can also modify the value 100 to any number you prefer. After that, open the settings.
Once the script is connected to your indicator, you can choose from two options:
Risk To Reward Ratio System
Fixed TP/ SL System
🔸if you select the Risk to Reward System ⤵️
The Risk-to-Reward System requires the calculation of a stop loss. That's why I have included three different types of stop-loss calculations for you to choose from:
ATR Based SL
Pivot Low SL
VWAP Based SL
Your stop loss and take profit levels will be automatically calculated based on the selected stop loss method and your risk-to-reward ratio.
You can also adjust their values to match your desired risk level. The trades will be displayed on the chart.
with the ability to change their values to match your risk.
once this is done, trades will be displayed on the chart
🔸if you select the Fixed system ⤵️
You have 2 inputs, which are FIXED TP & Fixed SL
input the values you want, and trades will be on your chart...
I have also added a Breakeven feature for you.
with this Breakeven feature the trade will not just move SL to Entry ?! NO NO, it will place it above entry by a % you input yourself, so you always win! 🚀
Here is an example
Enjoy, and have fun, if you have any questions do not hesitate to ask
