Nadaraya-Watson Envelope Strategy (Non-Repainting) Log ScaleIn the diverse world of trading strategies, the Nadaraya-Watson Envelope Strategy offers a different approach. Grounded in mathematical analysis, this strategy utilizes the Nadaraya-Watson kernel regression, a method traditionally employed for interpreting complex data patterns.
At the core of this strategy lies the concept of 'envelopes', which are essentially dynamic volatility bands formed around the price based on a custom Average True Range (ATR). These envelopes help provide guidance on potential market entry and exit points. The strategy suggests considering a buy when the price crosses the lower envelope and a sell when it crosses the upper envelope.
One distinctive characteristic of the Nadaraya-Watson Envelope Strategy is its use of a logarithmic scale, as opposed to a linear scale. The logarithmic scale can be advantageous when dealing with larger timeframes and assets with wide-ranging price movements.
The strategy is implemented using Pine Script v5, and includes several adjustable parameters such as the lookback window, relative weighting, and the regression start point, providing a level of flexibility.
However, it's important to maintain a balanced view. While the use of mathematical models like the Nadaraya-Watson kernel regression may provide insightful data analysis, no strategy can guarantee success. Thorough backtesting, understanding the mathematical principles involved, and sound risk management are always essential when applying any trading strategy.
The Nadaraya-Watson Envelope Strategy thus offers another tool for traders to consider. As with all strategies, its effectiveness will largely depend on the trader's understanding, application, and the specific market conditions.
在腳本中搜尋"the strat"
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
Monthly Strategy Performance TableWhat Is This?
This script code adds a Monthly Strategy Performance Table to your Pine Script strategy scripts so you can see a month-by-month and year-by-year breakdown of your P&L as a percentage of your account balance.
The table is based on realized equity rather than open equity, so it only updates the metrics when a trade is closed.
That's why some numbers will not match the Strategy Tester metrics (such as max drawdown), as the Strategy Tester bases metrics like max drawdown on open trade equity and not realized equity (closed trades).
The script is still a work-in-progress, so make sure to read the disclaimer below. But I think it's ready to release the code for others to play around with.
How To Use It
The script code includes one of my strategies as an example strategy. You need to replace my strategy code with your own. To do that just copy the source code below into a blank script, delete lines 11 -> 60 and paste your strategy code in there instead of mine. The script should work with most systems, but make sure to read the disclaimer below.
It works best with a significant amount of historical data, so it may not work very effectively on intraday timeframes as there is a severe limitation of available bars on TradingView. I recommend using it on 4HR timeframes and above, as anything less will produce very little usable data. Having a premium TradingView plan will also help boost the number of available bars.
You can hover your mouse over a table cell to get more information in the form of tooltips (such as the Long and Short win rate if you hover over your total return cell).
Credit
The code in this script is based on open-source code originally written by QuantNomad, I've made significant changes and additions to the original script but all credit for the idea and especially the display table code goes to them - I just built on top of it:
Why Did I Make This?
None of this is trading or investment advice, just my personal opinion based on my experience as a trader and systems developer these past 6+ years:
The TradingView Strategy Tester is severely limited in some important ways. And unless you use complex Excel formulas on exported test data, you can't see a granular perspective of your system's historical performance.
There is much more to creating profitable and tradeable systems than developing a strategy with a good win rate and a good return with a reasonable drawdown.
Some additional questions we need to ask ourselves are:
What did the system's worst drawdown look like?
How long did it last?
How often do drawdowns occur, and how quickly are they typically recovered?
How often do we have a break-even or losing month or year?
What is our expected compounded annual growth rate, and how does that growth rate compare to our max drawdown?
And many more questions that are too long to list and take a lifetime of trading experience to answer.
Without answering these kinds of questions, we run the risk of developing systems that look good on paper, but when it comes to live trading, we are uncomfortable or incapable of enduring the system's granular characteristics.
This Monthly Performance Table script code is intended to help bridge some of that gap with the Strategy Tester's limited default performance data.
Disclaimer
I've done my best to ensure the numbers this code outputs are accurate, and according to my testing with my personal strategy scripts it appears to work fine. But there is always a good chance I've missed something, or that this code will not work with your particular system.
The majority of my TradingView systems are extremely simple single-target systems that operate on a closed-candle basis to minimize many of the data reliability issues with the Strategy Tester, so I was unable to do much testing with multiple targets and pyramiding etc.
I've included a Debug option in the script that will display important data and information on a label each time a trade is closed. I recommend using the Debug option to confirm that the numbers you see in the table are accurate and match what your strategy is actually doing.
Always do your own due diligence, verify all claims as best you can, and never take anyone's word for anything.
Take care, and best of luck with your trading :)
Kind regards,
Matt.
PS. If you're interested in learning how this script works, I have a free hour-long video lesson breaking down the source code - just check out the links below this script or in my profile.
Slight Swing Momentum Strategy.Introduction:
The Swing Momentum Strategy is a quantitative trading strategy designed to capture mid-term opportunities in the financial markets by combining swing trading principles with momentum indicators. It utilizes a combination of technical indicators, including moving averages, crossover signals, and volume analysis, to generate buy and sell signals. The strategy aims to identify market trends and capitalize on price momentum for profit generation.
Highlights:
The strategy offers several key highlights that make it unique and potentially attractive to traders:
Swing Trading with Momentum: The strategy combines the principles of swing trading, which aim to capture short-to-medium-term price swings, with momentum indicators that help identify strong price trends and potential breakout opportunities.
Technical Indicator Optimization: The strategy utilizes a selection of optimized technical indicators, including moving averages and crossover signals, to filter out the noise and focus on high-probability trading setups. This optimization enhances the strategy's ability to identify favourable entry and exit points.
Risk Management: The strategy incorporates risk management techniques, such as position sizing based on equity and dynamic stop loss levels, to manage risk exposure and protect capital. This helps to minimize drawdowns and preserve profits.
Buy Condition:
The buy condition in the strategy is determined by a combination of factors, including A1, A2, A3, XG, and weeklySlope. Let's break it down:
A1 Condition: The A1 condition checks for specific price relationships. It verifies that the ratio of the highest price to the closing price is less than 1.03, the ratio of the opening price to the lowest price is less than 1.03, and the ratio of the highest price to the previous day's closing price is greater than 1.06. This condition looks for a specific pattern indicating potential bullish momentum.
A2 Condition: The A2 condition checks for price relationships related to the closing price. It verifies that the ratio of the closing price to the opening price is greater than 1.05 or that the ratio of the closing price to the previous day's closing price is greater than 1.05. This condition looks for signs of upward price movement and momentum.
A3 Condition: The A3 condition focuses on volume. It checks if the current volume crosses above the highest volume over the last 60 periods. This condition aims to identify increased buying interest and potentially confirms the strength of the potential upward price movement.
XG Condition: The XG condition combines the A1 and A2 conditions and checks if they are true for both the current and previous bars. It also verifies that the ratio of the closing price to the 5-period EMA crosses above the 9-period SMA of the same ratio. This condition helps identify potential buy signals when multiple factors align, indicating a strong bullish momentum and potential entry point.
Weekly Trend Factor: The weekly slope condition calculates the slope of the 50-period SMA over a weekly timeframe. It checks if the slope is positive, indicating an overall upward trend on a weekly basis. This condition provides additional confirmation that the stock is in an upward trend.
When all of these conditions align, the buy condition is triggered, indicating a favourable time to enter a long position.
Sell Condition:
The sell condition is relatively straightforward in the strategy:
Sell Signal: The sell condition simply checks if the closing price crosses below the 10-period EMA. When this condition is met, it indicates a potential reversal or weakening of the upward price momentum, and a sell signal is generated.
Backtest Outcome:
The strategy was backtested over the period from January 22nd, 1999 to May 3rd, 2023, using daily candlestick charts for the NASDAQ: NVDA. The strategy used an initial capital of 1,000,000 USD, The order quantity is defined as 10% of the equity. The strategy allows for pyramiding with 1 order, and the transaction fee is set at 0.03% per trade. Here are the key outcomes of the backtest:
Net Profit: 539,595.84 USD, representing a return of 53.96%.
Percent Profitable: 48.82%
Total Closed Trades: 127
Profit Factor: 2.331
Max Drawdown: 68,422.70 USD
Average Trade: 4,248.79 USD
Average Number of Bars in Trades: 11, indicating the average duration of the trades.
Conclusion:
In conclusion, the Swing Momentum Strategy is a quantitative trading approach that combines swing trading principles with momentum indicators to identify and capture mid term trading opportunities. The strategy has demonstrated promising results during backtesting, including a significant net profit and a favourable profit factor.
Dynamic Stop Loss DemoWhat does this script do ?
This script is for pine script programmers and explains how to implement a dynamic stop-loss strategy. It is different from trailing stop-loss. Trailing stop-loss can only set the retracement value, but this script can take profit on part of the position at a fixed price and allows users to decide whether to take profit on all positions based on whether a certain track is breached or other conditions author want. In this demo, it use rsi crossover and crossunder to decide the strategy condition, and use close price as open price, and use lowest low / highest high as stop price, and use 1.5 risk ratio to calculate the fixed first profit price. It will take 50% position size when the first profit price was reached. Then it will close all rest positions when the inverse condition come out or the dynamic stop(calculated by ATR) breached or when the price back to the open price or the stop price.
How is this script implemented
When start strategy by strategy.entry , it gives a custom id which contains direction, openPrice, stopPrice, profitPrice, qty, etc. It can be get from the global variable strategy.posiition_entry_name .
Optimized Zhaocaijinbao strategyIntroduction:
The Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It generates buy and sell signals by using a combination of exponential moving averages, moving averages, volume and slope indicators. It generates buy signals when the stock is above the 35-day moving average, the trading volume is higher than the 20-day moving average, and the stock is in an upward trend on a weekly timeframe."招财进宝" is a Chinese phrase that can be translated to "Attract Wealth and Bring in Treasure" in English. It is a common expression used to wish for good luck and prosperity in various contexts, such as in business or personal finances.
Highlights:
The strategy has several special optimizations that make it unique.
Firstly, the strategy is optimized for T+1 trading in the Chinese stock market and is only suitable for long positions. The optimizations are also applicable to international stock markets.
Secondly, the trend strategy is optimized to only show indicators on the right side and oscillations. This helps to prevent false signals in choppy markets.
Thirdly, the strategy uses a risk factor for dynamic position sizing to ensure position sizes are adjusted according to the current net asset value and risk preferences. This helps to lower drawdown risks.
The strategy has good resilience even without using stop loss modules in backtesting, making it suitable for trading hourly, 2-hourly, and daily K-line charts (depending on the stock being traded). We recommend experimenting with backtesting using SSE 1-hour or 2-hour or daily Kline charts.
Backtesting outcomes:
The strategy was backtested over the period from October 13th, 2005 to April 14th, 2023, using daily candlestick charts for the commodity code SSE:600763, with a currency of CNY and tick size of 0.01. The strategy used an initial capital of 1,000,000 CNY, with order sizes set to 10% equity and a pyramid of 1 order. The strategy also had a Max Position Size of 0.01 and a Risk Factor of 2.
Here is a summary of the performance of the trading strategy:
Total net profit: 288,577.32 CNY, representing a return of 128.86%
Total number of closed trades: 61
Winning trades: 37, representing a win rate of 60.66%
Profit factor: 2.415
Largest losing trade: 222,021.46 CNY, representing a loss of 14.08%
Average trade: 21,124.22 CNY, representing a return of 3.1%
Average holding period for all trades: 12 days
Conclusion:
In conclusion, the Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It is suitable for both Chinese stocks and global stocks. While the Optimized Zhaocaijinbao strategy has performed well in backtesting, it is important to note that past performance is not a guarantee of future results. Traders should conduct their own research and analysis and exercise caution when using any trading strategy.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Advanced VWAP_Pullback Strategy_Trend-Template QualifierGeneral Description and Unique Features of this Script
Introducing the Advanced VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends. Mark Minervini, a 2x US Investment Champion, developed the Trend-Template, which covers eight different and independent characteristics that can be adjusted and optimized in this trend-following strategy to ensure the best results. The strategy will only trigger buy-signals in case the optimized qualifiers are being met.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strategy
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Stop-loss limits and profit targets can be set variably. You also have the option to make use of the trailing stop exit strategy.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from Jan 2020 until March 2023
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
- This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
- The combination of the Trend-Template and the RSI qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
- Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
Weird Renko StratThis strategy uses Renko, it generates a signal when there is a reversal in Renko. When using historical data, it provides a good entry and an okay exit. However, in a real-time environment, this strategy is subject to repaint and may produce a false signal.
As a result, the backtesting result should not be used as a metric to predict future results. It is highly recommended to forward-test the strategy before using it in real trading. I forward test it from 12/18/2022 to 12/21/2022 in paper trading, using the alert feature in Tradingview. I made 60 trades trading the BTCUSDT BINANCE 3 min with 26 as the param and under the condition that I use 20x margin, compounding my yield, and having 0 trading fee, a steady loss is generated: from $10 to $3.02.
This is quite interesting. As if I flip the signal from "Long" to "Short" and another way too, it will be a steady profit from $10 to $21.85. Hence, if I'm trying to anti-trade the real-time alert signal, the current "4 Days Result" will be good. Nevertheless, I still have to forward-test it for longer to see if it will fail eventually.
Dive into the setting of the strategy
- Margin is the leverage you use. 1 means 1x, 10 means 10x. It affects the backtest yield when you backtest
- Compound Yield button is for compound calculation, disable it to go back to normal backtesting
- Anti Strategy button is to do the opposite direction trade, when the original strat told you to "Long", you "Short" instead. Enable it to use the feature
- Param is the block size for the Renko chart
- Drawdown is just a visual tool for you in case you want to place a stop loss (represent by the semitransparent red area in the chart)
- From date Thru Date is to specify the backtest range of the strategy, This feature is turned off by default. It is controlled by the Max Backtest Timeframe which will be explain below
- Max Backtest Timeframe control the From date Thru Date function, disable it to enable the From Date Thru Date function
Param is the most important input in this strategy as it directly affects performance. It is highly recommended to backtest nearly all the possible parameters before deploying it in real trading. Some factors should be considered:
- Price of the asset (like an asset of 1 USD vs an asset of 10000 USD required different param)
- Timeframe (1-minute param is different than 1-month param)
I believe this is caused by the volatility of the selected timeframe since different timeframe has different volatility. Param should be fine-tuned before usage.
Here is the param I'm using:
BTCUSDT BINANCE 3min: 26
BTCUSDT BINANCE 5min: 28
BTCUSDT BINANCE 1day: 15
Background of the strategy:
- The strategy starts with $10 at the start of backtesting (customizable in setting)
- The trading fee is set to 0.00% which is not common for most of the popular exchanges (customizable in setting)
- The contract size is not a fixed amount, but it uses your balance to buy it at the open price. If you are using the compound mode, your balance will be your current total balance. If you are using the non-compound mode, it will just use the $10 you start with unless you change the amount you start with. If you are using a margin higher than 1, it will calculate the corresponding contract size properly based on your margin. (Only these options are allowed, you are not able to change them without changing the code)
RSI Divergence Strategywhat is "RSI Divergence Strategy"?
it is a RSI strategy based this indicator:
what it does?
it gives buy or sell signals according to RSI Divergences. it also has different variables such as "take profit", "stop loss" and trailing stop loss.
how it does it?
it uses the "RSI Divergence" indicator to give signal. For detailed information on how it works, you can visit the link above. The quantity of the inputs is proportional to the rsi values. Long trades are directly traded with "RSI" value, while short poses are traded with "100-RSI" value.
How to use it?
The default settings are for scalp strategy but can be used for any type of trading strategy. you can develop different strategies by changing the sections. It is quite simple to use.
RSI length is length of RSİ
source is source of RSİ
RSİ Divergence lenght is length of line on the RSI
The "take profit", "stop" and "trailing stop" parts used in the "buy" group only affect buys. The "sell" group is similarly independent of the variables in the "buy" group.
The "zoom" section is used to enlarge or reduce the indicator. it only changes the appearance, it does not affect the results of the strategy.
EMA RSI Strategy
Simple strategy
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If the last two closes are in ascending order, the rsi is below 50 and ascending, and the current candle is above 200 ema, then LONG. If the last two closes are in descending order, the rsi is above 50 and descending, and the current candle is below 200 ema, then SHORT.
LONG Exit strategy:
ATR: Last 14 day
Lowest: The lowest value of the last 14 candles
Limit points = (Trade Price - Lowest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
SHORT Exit strategy:
ATR: Last 14 day
Highest: The higher value of the last 14 candles
Limit points = (Trade Price - Highest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
Backtest results for the AUDUSD pair gave positive results over the last three months.
I am testing this strategy using a python bot in a real environment this week and will update the results at the end of the week.
Disclaimer
This is not financial advice. You should seek independent advice to check how the strategy information relates to your unique circumstances.
We are not liable for any loss caused, whether due to negligence or otherwise arising from the use of, or reliance on, the information provided directly or indirectly by this strategy.
rt maax EMA cross strategythis just sample of our strategies we published with open source, to learning our investor the way of trading and analysis, this strategy just for study and learning
in this strategy we use expontial moving avarage 20 , 50 , 200 and the we build this strategy when the price move up ema 200 and ema 20,50 cross up the 200 ema in this conditions the strargey will open long postion
and the oppisit it is true for short postion in this sitation the price should be under ema 200 and the ema 20 , 50 should cross under 200 ema then the strategy will open the short postion
we try this strategy on forex ,crypto and futures and it give us very good result ,, also we try this postion on multi time frame we find the stragey give us good result on 1 hour time frame .
in the end our advice for you before you use any stratgy you should have the knowledg of the indecators how it is work and also you should have information about the market you trade and the last news for this market beacuse it effect so much on the price moving .
so we hope this strategy give you brefing of the way we work and build our strategy
Multi Trend Cross Strategy TemplateToday I am sharing with the community trend cross strategy template that incorporates any combination of over 20 built in indicators. Some of these indicators are in the Pine library, and some have been custom coded and contributed over time by the beloved Pine Coder community. Identifying a trend cross is a common trend following strategy and a common custom-code request from the community. Using this template, users can now select from over 400 different potential trend combinations and setup alerts without any custom coding required. This Multi-Trend cross template has a very inclusive library of trend calculations/indicators built-in, and will plot any of the 20+ indicators/trends that you can select in the settings.
How it works : Simple trend cross strategies go long when the fast trend crosses over the slow trend, and/or go short when the fast trend crosses under the slow trend. Options for either trend direction are built-in to this strategy template. The script is also coded in a way that allows you to enable/modify pyramid settings and scale into a position over time after a trend has crossed.
Use cases : These types of strategies can reduce the volatility of returns and can help avoid large market downswings. For instance, those running a longer term trend-cross strategy may have not realized half the down swing of the bear markets or crashes in 02', 08', 20', etc. However, in other years, they may have exited the market from time to time at unfavorable points that didn't end up being a down turn, or at times the market was ranging sideways. Some also use them to reduce volatility and then add leverage to attempt to beat buy/hold of the underlying asset within an acceptable drawdown threshold.
Special thanks to @Duyck, @everget, @KivancOzbilgic and @LazyBear for coding and contributing earlier versions of some of these custom indicators in Pine.
This script incorporates all of the following indicators. Each of them can be selected and modified from within the indicator settings:
ALMA - Arnaud Legoux Moving Average
DEMA - Double Exponential Moving Average
DSMA - Deviation Scaled Moving Average - Contributed by Everget
EMA - Exponential Moving Average
HMA - Hull Moving Average
JMA - Jurik Moving Average - Contributed by Everget
KAMA - Kaufman's Adaptive Moving Average - Contributed by Everget
LSMA - Linear Regression , Least Squares Moving Average
RMA - Relative Moving Average
SMA - Simple Moving Average
SMMA - Smoothed Moving Average
Price Source - Plotted based on source selection
TEMA - Triple Exponential Moving Average
TMA - Triangular Moving Average
VAMA - Volume Adjusted Moving Average - Contributed by Duyck
VIDYA - Variable Index Dynamic Average - Contributed by KivancOzbilgic
VMA - Variable Moving Average - Contributed by LazyBear
VWMA - Volume Weighted Moving Average
WMA - Weighted Moving Average
WWMA - Welles Wilder's Moving Average
ZLEMA - Zero Lag Exponential Moving Average - Contributed by KivancOzbilgic
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!
[Sniper] SuperTrend + SSL Hybrid + QQE MODHi. I’m DuDu95.
**********************************************************************************
This is the script for the series called "Sniper".
*** What is "Sniper" Series? ***
"Sniper" series is the project that I’m going to start.
In "Sniper" Series, I’m going to "snipe and shoot" the youtuber’s strategy: to find out whether the youtuber’s video about strategy is "true or false".
Specifically, I’m going to do the things below.
1. Implement "Youtuber’s strategy" into pinescript code.
2. Then I will "backtest" and prove whether "the strategy really works" in the specific ticker (e.g. BTCUSDT) for the specific timeframe (e.g. 5m).
3. Based on the backtest result, I will rate and judge whether the youtube video is "true" or "false", and then rate the validity, reliability, robustness, of the strategy. (like a lie detector)
*** What is the purpose of this series? ***
1. To notify whether the strategy really works for the people who watched the youtube video.
2. To find and build my own scalping / day trading strategy that really works.
**********************************************************************************
*** Strategy Description ***
This strategy is from " QQE MOD + supertrend + ssl hybrid" by korean youtuber "코인투데이".
"코인투데이" claimed that this strategy will make you a lot of money in any crypto ticker in 15 minute timeframe.
### Entry Logic
1. Long Entry Logic
- Super Trend Short -> Long
- close > SSL Hybrid baseline upper k
- QQE MOD should be blue
2. Short Entry Logic
- Super Trend Long -> Short
- close < SSL Hybrid baseline lower k
- QQE MOD should be red
### Exit Logic
1. Long Exit Logic
- Super Trend Long -> Short
2. Short Entry Logic
- Super Trend Short -> Long
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
3. SuperTrend and SSL Hybrid Baseline is by default drawn on the chart.
4. If you check EMA filter, EMA would be drawn on the chart.
5. Should add QQE MOD indicator manually if you want to see QQE MOD.
**********************************************************************************
*** Rating: True or False?
### Rating:
→ 3.5 / 5 (0 = Trash, 1 = Bad, 2 = Not Good, 3 = Good, 4 = Great, 5 = Excellent)
### True or False?
→ True but not a 'perfect true'.
→ It did made a small profit on 15 minute timeframe. But it made a profit so it's true.
→ It worked well in longer timeframe. I think super trend works well so I will work on this further.
### Better Option?
→ Use this for Day trading or Swing Trading, not for Scalping. (Bigger Timeframe)
→ Although the result was not good at 15 minute timeframe, it was quite profitable in 1h, 2h, 4h, 8h, 1d timeframe.
→ Crypto like BTC, ETH was ok.
→ The result was better when I use EMA filter.
### Robust?
→ Yes. Although result was super bad in 5m timeframe, backtest result was "consistently" profitable on longer timeframe (when timeframe was bigger than 15m, it was profitable).
→ Also, MDD was good under risk management option on.
**********************************************************************************
*** Conclusion?
→ I recommend you not to use this on short timeframe as the youtuber first mentioned.
→ In my opinion, I can use on longer timeframe like 2h or bigger with EMA filter, stoploss and risk management.
[Sniper] SSL Hybrid + QQE MOD + Waddah Attar StrategyHi. I’m DuDu95.
**********************************************************************************
This is the script for the series called "Sniper".
*** What is "Sniper" Series? ***
"Sniper" series is the project that I’m going to start.
In "Sniper" Series, I’m going to "snipe and shoot" the youtuber’s strategy: to find out whether the youtuber’s video about strategy is "true or false".
Specifically, I’m going to do the things below.
1. Implement "Youtuber’s strategy" into pinescript code.
2. Then I will "backtest" and prove whether "the strategy really works" in the specific ticker (e.g. BTCUSDT) for the specific timeframe (e.g. 5m).
3. Based on the backtest result, I will rate and judge whether the youtube video is "true" or "false", and then rate the validity, reliability, robustness, of the strategy. (like a lie detector)
*** What is the purpose of this series? ***
1. To notify whether the strategy really works for the people who watched the youtube video.
2. To find and build my own scalping / day trading strategy that really works.
**********************************************************************************
*** Strategy Description ***
This strategy is from "SSL QQE MOD 5MIN SCALPING STRATEGY" by youtuber "Daily Investments".
"Daily Investments" claimed that this strategy will make you some money from 100 trades in any ticker in 5 minute timeframe.
### Entry Logic
1. Long Entry Logic
- close > SSL Hybrid Baseline.
- QQE MOD should turn into blue color.
- Waddah Attar Explosion indicator must be green.
2. Short Entry Logic
- close < SSL Hybrid Baseline
- QQE MOD should turn into red color.
- Waddah Attar Explosion indicator must be red.
### Exit Logic
1. Long Exit Logic
- When QQE MOD turn into red color.
2. Short Entry Logic
- When QQE MOD turn into blue color.
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
3. SSL Hybrid Baseline is by default drawn on the chart.
4. If you check EMA filter, EMA would be drawn on the chart.
5. Should add QQE MOD and Waddah Attar Explosion indicator manually if you want to see QQE MOD.
**********************************************************************************
*** Rating: True or False?
### Rating:
→ 1.5 / 5 (0 = Trash, 1 = Bad, 2 = Not Good, 3 = Good, 4 = Great, 5 = Excellent)
### True or False?
→ False
→ Doesn't Work on 5 minute timeframe. Also, it doesn't work on crypto.
### Better Option?
→ Use this for Day trading or Swing Trading, not for Scalping. (Bigger Timeframe)
→ Although the result was bad at 5 minute timeframe, it was profitable in 1h, 2h, 4h, 8h, 1d timeframe.
→ BTC, ETH was ok.
→ The result was better when I use EMA filter (only on longer timeframe).
### Robust?
→ So So. Although result was bad in short timeframe (e.g. 30m 15m 5m), backtest result was "consistently" profitable on longer timeframe.
→ Also, MDD was not that bad under risk management option on.
**********************************************************************************
*** Conclusion?
→ Don't use this on short timeframe.
→ Better use on longer timeframe with filter, stoploss and risk management.
Strategy PnL LibraryLibrary "Strategy_PnL_Library"
TODO: This is a library that helps you learn current pnl of open position and use it to create your own dynamic take profit or stop loss rules based on current level of your profit. It should only be used with strategies.
inTrade()
inTrade: Checks if a position is currently open.
Returns: bool: true for yes, false for no.
notInTrade()
inTrade: Checks if a position is currently open. Interchangeable with inTrade but just here for simple semantics.
Returns: bool: true for yes, false for no.
pnl()
pnl: Calculates current profit or loss of position after the commission. If the strategy is not in trade it will always return na.
Returns: float: Current Profit or Loss of position, positive values for profit, negative values for loss.
entryBars()
entryBars: Checks how many bars it's been since the entry of the position.
Returns: int: Returns a int of strategy entry bars back. Minimum value is always corrected to 1 to avoid lookback errors.
pnlvelocity()
pnlvelocity: Calculates the velocity of pnl by following the change in open profit compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl velocity.
pnlacc()
pnlacc: Calculates the acceleration of pnl by following the change in profit velocity compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl acceleration.
pnljerk()
pnljerk: Calculates the jerk of pnl by following the change in profit acceleration compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl jerk.
pnlhigh()
pnlhigh: Calculates the highest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float highest value the pnl has reached.
pnllow()
pnllow: Calculates the lowest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float lowest value the pnl has reached.
pnldev()
pnldev: Calculates the deviance of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float deviance value of the pnl.
pnlvar()
pnlvar: Calculates the variance value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float variance value of the pnl.
pnlstdev()
pnlstdev: Calculates the stdev value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float stdev value of the pnl.
pnlmedian()
pnlmedian: Calculates the median value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float median value of the pnl.
[MT Trader] Backtest template w/ Supertrend Strategy---EN: In this strategy template you will find some functions already pre-programmed to be used in your strategies to speed up the programming process, among them we can highlight the default stop loss and take profit functions, which will help to set easily and quickly, defining the price range in which we want to prevent large losses or protect our profits from unexpected market movements.
🔴 Stop Loss: Among the functions of the stop loss are the 4 most known, first we have the fixed percentage range (%) and price ($), when the price reaches this fixed price will limit the losses of the operation avoiding larger losses, then we have the average true range (ATR), a moving average of true range and X period that can give us good reference points to place our stop loss, finally the last point higher or lower is the most used by traders to place their stop loss.
In addition, the price range between the entry and stop loss can be converted into a trailing stop loss.
🟢 Take Profit: We have 3 options for take profit, just like stop loss, the fixed range of percentage(%) and price($), are available, in addition to this we have the 1:# ratio option, which multiplies by X number the range between the entry and stop loss to use it as take profit, perfect for strategies that use ATR or last high/low point for their strategy.
📈 Heikin Ashi Entrys: The heikin ashi entries are trades that are calculated based on heikin ashi candles but their price is executed in Japanese candles, thus avoiding the false results that occur in heikin candlestick charts, making that in certain cases better results are obtained in the strategies that are executed with this option compared to Japanese candlesticks.
📊 Dashboard: A more visual and organized way to see the results and data needed for our strategy.
Feel free to use this template to program your own strategies, if you find bugs or want to request a new feature let me know in the comments or through my telegram @hvert_mt
__________________________________________________________________________________________________________________________________________________
---ES: En esta plantilla de estrategia podrás encontrar algunas funciones ya pre-programadas para ser usadas en tus estrategias para acelerar procesos de programación, entre ellas podemos destacar las funciones por defecto de stop loss y take profit, que ayudaran a establecer de manera fácil y rápida, definiendo los rango de precio en los que queremos prevenirnos de perdidas grandes o proteger nuestras ganancias de movimientos inesperados del mercado.
🔴 Stop Loss: Entre las funciones del stop loss están las 4 más conocidas, en primer lugar tenemos el rango de porcentaje fijo(%) y el precio($), cuando el precio alcance este precio fijo se limitaran las perdidas de la operación evitando perdidas mas grandes, después tenemos el promedio de rango verdadero(ATR), una media móvil del rango verdadero y X periodo que nos puede dar buenos puntos de referencia para colocar nuestro stop loss, por ultimo el ultimo punto mas alto o mas bajo es de los mas usados por los traders para colocar su stop loss.
Adicional a esto, el rango de precio entre la entrada y el stop loss se puede convertir en un trailing stop loss.
🟢 Take Profit: Tenemos 3 opciones para take profit, al igual que en el stop loss, el rango fijo de porcentaje(%) y precio($) se encuentran disponibles, adicional a esto tenemos la opción de ratio 1:#, que multiplica por X numero el rango entre la entrada y el stop loss para usarlo como take profit, perfecto para estrategias que usen ATR o ultimo punto alto/bajo.
📈 Entradas Heikin Ashi: Las entradas Heikin Ashi son trades que son calculados en base a las velas Aeikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas.
📊 Panel de Control: Una manera mas visual y organizada de ver los resultados y datos necesarios de nuestra estrategia.
Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mi Telegram: @hvert_mt
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.
BEST Strategy Template w/ Custom SL/TP Size - EducationalHello traders
I'm getting this question at least once per week: "how to define a custom exit quantity for my stop loss and a different one for my take profit"
Instead of answering every day the same question in my DMs, I've decided to publish an educational strategy template script using this
Features
- Select to use or not the SL and/or TP
- Define how many pips/USD the SL/TP should be set at from the entry
- Define what quantity percentage you want to close at SL and/or at TP (lines 301 to 320 in the code)
- Classical custom trailing stop where the SL is moved to breakeven once the TP is hit
- Get real-time backtesting stats based on the options you've selected
Update
You might not know it yet but from last week (or maybe the week before), the qty/qty_percent from the strategy.exit function refers now to the initial position size (and not the remaining position size like before)
For example:
strategy.exit("EX1", qty_percent = 50, stop = constant)
strategy.exit("EX2", qty_percent = 20, stop = constant)
What happened before
After "EX1" reaches SL levels, "EX2" exits 20% from the % of the remaining position size.
If the initial position size = 100 contracts
EX1 exits 50 contracts
EX2 exits 20% of 50 contracts = 10 contracts
What's happening now
After "EX1" reaches SL levels, "EX2" exits 20% from the % of the original position size.
If the initial position size = 100 contracts
EX1 exits 50 contracts
EX2 exits 20 (20% of 100 contracts) contracts
I think this is an improvement and I really enjoy this new behavior.
See you in a few days with another post :)
ALL THE BEST
Dave
