Moving Average profit targets with var sizeProfit target:
Profit targets are those scenarios where the system expects to be greater than the actual return at the end of the transaction: they may be short-term benefits, such as a favorable price shock model.
In short-term transactions, profit objectives are essential. Price fluctuations make any favorable event likely to turn around in an instant. Moreover, profit objectives are more difficult to integrate into the longer-term trading system, because they are afraid of losing larger profits at risk, so they will replace them with smaller but more frequent gains. As a follower of the trend, once you make a profit and stop earning, but the trend direction is still intact, you need to find a way to re-enter the transaction to avoid losing the rare but very large market situation.
Profit target is best calculated based on price volatility (V), and the most commonly used method:
For Long, the system buy point (E), needs to be multiplied by the average true volatility or annualized volatility :E+f×V.
The net value multiplier f used to calculate the profit level is usually obtained through data mining.
Pesquisar nos scripts por "profit"
Profitable Contrarian scalpingUses the 5 period and 10 period VMWAs that have been smoothed with a 5 period SMA of the close price. Normally, a short crossover long formation signals a buy signal, but as scalpers know, the 1 minute chart moves so fast and with so much volatility that lagging indicators get wrecked by the market. According, this strategy operates under the assumption that by the time this lagging indicator makes a signal, the price is ready to reverse. Losses are taken swiftly in the case of a continuation pattern. This indicator averages a 55-65% profitable rate and is almost always a positive P/L on the 1 minute chart of the most commonly traded assets.
Of course, there may be validity for this indicator outside the 1 minute chart, but I have found such success to be very limited. Accordingly, use this indicator on SPY, TQQQ, TSLA, AMZN, and major cryptos on the 1 min chart.
Trailing Take Profit - Close Based📝 Description
This script demonstrates a new approach to the trailing take profit.
Trailing Take Profit is a price-following technique. When used, instead of setting a limit order for the take profit target exiting from your position at the specified price, a stop order is conditionally set when the take profit target is reached. Then, the stop price (a.k.a trailing price), is placed below the take profit target at a distance defined by the user percentagewise. On regular time intervals, the stop price gets updated by following the "Trail Barrier" price (high by default) upwards. When the current price hits the stop price you exit the trade. Check the chart for more details.
This script demonstrates how to implement the close-based Trailing Take Profit logic for long positions, but it can also be applied for short positions if the logic is "reversed".
📢 NOTE
To generate some entries and showcase the "Trailing Take Profit" technique, this script uses the crossing of two moving averages. Please keep in mind that you should not relate the Backtesting results you see in the "Strategy Tester" tab with the success of the technique itself.
This is not a complete strategy per se, and the backtest results are affected by many parameters that are outside of the scope of this publication. If you choose to use this new approach of the "Trailing Take Profit" in your logic you have to make sure that you are backtesting the whole strategy.
⚔️ Comparison
In contrast to my older "Trailing Take Profit" publication where the trailing take profit implementation was tick-based, this new approach is close-based, meaning that the update of the stop price occurs at the bar close instead of every tick.
While comparing the real-time results of the two implementations is like comparing apples to oranges, because they have different dynamic behavior, the new approach offers better consistency between the backtesting results and the real-time results.
By updating the stop price on every bar close, you do not rely on the backtester assumptions anymore (check the Reasoning section below for more info).
The new approach resembles the conditional "Trailing Exit" technique, where the condition is true when the current price crosses over the take profit target. Then, the stop order is placed at the trailing price and it gets updated on every bar close to "follow" the barrier price (high). On the other hand, the older tick-based approach had more "tight" dynamics since the trailing price gets updated on every tick leaving less room for price fluctuations by making it more probable to reach the trailing price.
🤔 Reasoning
This new close-based approach addresses several practical issues the older tick-based approach had. Those issues arise mainly from the technicalities of the TV Backtester. More specifically, due to the assumptions the Broker Emulator makes for the price action of the history bars, the backtesting results in the TV Backtester are exaggerated, and depending on the timeframe, the backtesting results look way better than they are in reality.
The effect above, and the inability to reason about the performance of a strategy separated people into two groups. Those who never use this feature, because they couldn't know for sure the actual effect it might have in their strategy, (even if it turned out to be more profitable) and those who abused this type of "repainting" behavior to show off, and hijack some boosts from the community by boasting about the "fake" results of their strategies.
Even if there are ways to evaluate the effectiveness of the tick-based approach that is applied in an existing strategy (this is out of the topic of this publication), it requires extra effort to do the analysis. Using this closed-based approach we can have more predictable results, without surprises.
⚠️ Caveats
Since this approach updates the trailing price on bar close, you must wait for at least one bar to close after the price crosses over the take profit target.
Profitable Strategy Forex 80 by LukasHello all,
Herewith I publish my Forex strategy, it's works for major pairs only.
I ran more than a thousand test to get this result! :))
The strategy have more than 8 Buy and Sell signal condition with 2 core signal provider.
You can turn on/off each 7 signal and find the most profitable combination for each pairs.
If you trade on lower timeframe, you can turn on "Higher Timeframe MA".
It's also will trigger buy/sell when breakout from monthly high / low when entry condition meets.
You can set weekly or monthly.
I work on 4H timeframe when develop the script, so best use is 4H.
Basically i want to make reliable strategy that can automate trade
without the need to check chart every minutes! Hahha
So i think higher time frame is the best time to start,
and I found 4H chart on Forex have more clear structure and volatility .
I make the signal visible, it consist of 3 line represent The Pairs, Base and Counter pairs,
basically when Green line on top it means Base currency is strong, vice versa.
You may share your setting in the comment section, so others can try it :)
For this result I turn on Signal A,C,D,E,F
Signal A and B use special RSI
Signal C and D use special MACD
Signal E use RSI
Signal F use EMA and DEMA combination
In my opinion each pairs has unique character, some of them move faster than others.
So, adjust the setting for each pairs will benefit you more.
For further develop of this strategy, please give me feedback! :)
Profit MAX MTF HeatMapThis is a powerfull strategy which is made from combining 3 multi timeframes into one for profit max indicator
In this case we have daily, weekly and montly.
Our long conditions are the next ones :
if we have an uptrend on all 3 at the same time, we go long.
If we have a downtrend on all 3 of them at the same time we go short.
For exit, for long, as soon as one of the 3 converts into downtrend we exit the trade.
For exit, for short, as soon as one of the 3 converts into uptrend we exit the trade.
This tool can be used on all types of markets, and can also be changed the time frames.
Profit Maximizer StrategyFirst I would like to thank to @KivancOzbilgic for developing this indicator.
All the credit goes to him.
I just created a strategy, in order to try to find the perfect parameters, timeframe and currency for it.
I will provide below the same description like he has in the publish of profit maximizer
Profit Maximizer - PMax combines the powerful sides of MOST (Moving Average Trend Changer) and SuperTrend (ATR price detection) in one indicator.
Backtest and optimization results of PMax are far better when compared to its ancestors MOST and SuperTrend. It reduces the number of false signals in sideways and give more reliable trade signals.
PMax is easy to determine the trend and can be used in any type of markets and instruments. It does not repaint.
The first parameter in the PMax indicator set by the three parameters is the period/length of ATR.
The second Parameter is the Multiplier of ATR which would be useful to set the value of distance from the built in Moving Average.
I personally think the most important parameter is the Moving Average Length and type.
PMax will be much sensitive to trend movements if Moving Average Length is smaller. And vice versa, will be less sensitive when it is longer.
As the period increases it will become less sensitive to little trends and price actions.
In this way, your choice of period, will be closely related to which of the sort of trends you are interested in.
We are under the effect of the uptrend in cases where the Moving Average is above PMax;
conversely under the influence of a downward trend, when the Moving Average is below PMax.
Built in Moving Average type defaultly set as EMA but users can choose from 8 different Moving Average types like:
SMA : Simple Moving Average
EMA : Exponential Movin Average
WMA : Weighted Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average aka VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
Tip: In sideways VAR would be a good choice
You can use PMax default alarms and Buy Sell signals like:
1-
BUY when Moving Average crosses above PMax
SELL when Moving Average crosses under PMax
2-
BUY when prices jumps over PMax line.
SELL when prices go under PMax line.
PROFIT + V2We are glad to introduce you our new strategy PROFIT +.
The strategy PROFIT + is based on price and volume correlation analysis.
The entries are quick with tight stop loss. Best suits fot those who like
to get quick profit in the beginning of the price move.
It was tested on BTC , Bitmex exchange on 1 hour timeframe,
but it can also be used on 30, 15 and 10 minutes tf.
There is also ALERT INDICATOR for the strategy to receive notification
when there is a buy/sell signal.
To get acces to the strategy pm me.
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Рады представить нашу новую торговую стратегию PROFIT+.
Стратегия PROFIT + основана на анализе корреляции цены и объёма.
Входы в стратегии быстрые с коротким стопом. Больше подходит для
тех кто любит забирать быстрый профит в самом начале движения.
Стратегия была тестирована на инструменте BTC биржа BITMEX
на 1 часовом таймфрейме, но она также работает на 30, 15 и 10 минутных тф.
Для стратегии также доступен ИНДИКАТОР АЛЕРТ для получения оповещения
при появлении buy/sell сигналов.
Для получения доступа к стратегии пишите мне в личные сообщения.
Profit Runner Strategy v2.0This is the strategy version of the recently posted Profit Runner v2.0 study. We include both together so that users can use the strategy for backtesting and figuring out the optimal settings for their specific usage and then implement those settings in the study version(which includes alerts for automated trading).
Green background highlights are buy signals and red background highlights are sell signals. Red and green filled area show the user's stop loss .
QuantBuilder | FractalystWhat's the strategy's purpose and functionality?
QuantBuilder is designed for both traders and investors who want to utilize mathematical techniques to develop profitable strategies through backtesting on historical data.
The primary goal is to develop profitable quantitive strategies that not only outperform the underlying asset in terms of returns but also minimize drawdown.
For instance, consider Bitcoin (BTC), which has experienced significant volatility, averaging an estimated 200% annual return over the past decade, with maximum drawdowns exceeding -80%. By employing this strategy with diverse entry and exit techniques, users can potentially seek to enhance their Compound Annual Growth Rate (CAGR) while managing risk to maintain a lower maximum drawdown.
While this strategy employs quantitative techniques, including mathematical methods such as probabilities and positive expected values, it demonstrates exceptional efficacy across all markets. It particularly excels in futures, indices, stocks, cryptocurrencies, and commodities, leveraging their inherent trending behaviors for optimized performance.
In both trending and consolidating market conditions, QuantBuilder employs a combination of multi-timeframe probabilities, expected values, directional biases, moving averages and diverse entry models to identify and capitalize on bullish market movements.
How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
1. Trading:
- Designed for traders looking to capitalize on bullish markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for both swing and intraday trading with a focus on probabilities and risk per trade approach.
2. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully/partially investing in the asset during bullish conditions.
How does the strategy identify market structure? What are the underlying calculations?
The strategy utilizes an efficient logic with for loops to pinpoint the first swing candle featuring a pivot of 2, establishing the point at which the break of structure begins.
What entry criteria are used in this script? What are the underlying calculations?
The script utilizes two entry models: BreakOut and fractal.
Underlying Calculations:
Breakout: The script assigns the most recent swing high to a variable. When the price closes above this level and all other conditions are met, the script executes a breakout entry (conservative approach).
Fractal: The script identifies a swing low with a period of 2. Once this condition is met, the script executes the trade (aggressive approach).
How does the script calculate probabilities? What are the underlying calculations?
The script calculates probabilities by monitoring price interactions with liquidity levels. Here’s how the underlying calculations work:
Tracking Price Hits: The script counts the number of times the price taps into each liquidity side after the EQM level is activated. This data is stored in an array for further analysis.
Sample Size Consideration: The total number of price interactions serves as the sample size for calculating probabilities.
Probability Calculation: For each liquidity side, the script calculates the probability by taking the average of the recorded hits. This allows for a dynamic assessment of the likelihood that a particular side will be hit next, based on historical performance.
Dynamic Adjustment: As new price data comes in, the probabilities are recalculated, providing real-time aduptive insights into market behavior.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
How does the script calculate expected values? What are the underlying calculations?
The script calculates expected values by leveraging the probabilities of winning and losing trades, along with their respective returns. The process involves the following steps:
This quantitative methodology provides a robust framework for assessing the expected performance of trading strategies based on historical data and backtesting results.
How is the contextual bias calculated? What are the underlying calculations?
The contextual bias in the QuantBuilder script is calculated through a structured approach that assesses market structure based on swing highs and lows. Here’s how it works:
Identification of Swing Points: The script identifies significant swing points using a defined pivot logic, focusing on the first swing high and swing low. This helps establish critical levels for determining market structure.
Break of Structure (BOS) Assessment:
Bullish BOS: The script recognizes a bullish break of structure when a candle closes above the first swing high, followed by at least one swing low.
Bearish BOS: Conversely, a bearish break of structure is identified when a candle closes below the first swing low, followed by at least one swing high.
Bias Assignment: Based on the identified break of structure, the script assigns directional biases:
A bullish bias is assigned if a bullish BOS is confirmed.
A bearish bias is assigned if a bearish BOS is confirmed.
Quantitative Evaluation: Each identified bias is quantitatively evaluated, allowing the script to assign numerical values representing the strength of each bias. This quantification aids in assessing the reliability of market sentiment across multiple timeframes.
What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
- Initial Stop-loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14)
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
- Trailing Stop-Loss:
One of the key elements of this strategy is its ability to detect structural liquidity and structural invalidation levels across multiple timeframes to trail the stop-loss once the trade is in running profits.
By utilizing this approach, the strategy allows enough room for price to run.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
To facilitate studying historical data, all conditions and filters can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Quantitive Strategy Builder to Create a Profitable Edge and System?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
QuantBuilder stands out due to its unique combination of quantitative techniques and innovative algorithms that leverage historical data for real-time trading decisions. Unlike most algorithmic strategies that work based on predefined rules, this strategy adapts to real-time market probabilities and expected values, enhancing its reliability. Key features include:
Mathematical Framework: The strategy integrates advanced mathematical concepts, such as probabilities and expected values, to assess trade viability and optimize decision-making.
Multi-Timeframe Analysis: By utilizing multi-timeframe probabilities, QuantBuilder provides a comprehensive view of market conditions, enhancing the accuracy of entry and exit points.
Dynamic Market Structure Identification: The script employs a systematic approach to identify market structure changes, utilizing a blend of swing highs and lows to detect contextual/direction bias of the market.
Built-in Trailing Stop Loss: The strategy features a dynamic trailing stop loss based on multi-timeframe analysis of market structure. This allows traders to lock in profits while adapting to changing market conditions, ensuring that exits are executed at optimal levels without prematurely closing positions.
Robust Performance Metrics: With detailed performance tables and visualizations, users can easily evaluate strategy effectiveness and adjust parameters based on historical performance.
Adaptability: The strategy is designed to work across various markets and timeframes, making it versatile for different trading styles and objectives.
Suitability for Investors and Traders: QuantBuilder is ideal for both investors and traders looking to rely on mathematically proven data to create profitable strategies, ensuring that decisions are grounded in quantitative analysis.
These original elements combine to create a powerful tool that can help both traders and investors to build and refine profitable strategies based on algorithmic quantitative analysis.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
AlgoBuilder [Mean-Reversion] | FractalystWhat's the strategy's purpose and functionality?
This strategy is designed for both traders and investors looking to rely and trade based on historical and backtested data using automation.
The main goal is to build profitable mean-reversion strategies that outperform the underlying asset in terms of returns while minimizing drawdown.
For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown.
Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors.
In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based moving averages and bands mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels.
Additionally, the strategy has also a feature that includes a built-in probability function for traders who want to implement probabilities right into their trading strategies.
Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, profit factor, average trade, average risk-reward ratio (RR), and more.
This aids optimization to meet specific goals and risk tolerance levels effectively.
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How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
Trading:
1. Trading:
- Designed for traders looking to capitalize on bullish trending markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for active trading with a focus on mean-reversion and risk per trade approach.
◓: Mode | %: Risk percentage per trade
3. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions.
- ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 10% of equity to buy the asset)
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What's is FRMA? How does the triple bands work? What are the underlying calculations?
Middle Band (FRMA):
The middle band is the core of the FRMA system. It represents the Fractalyst Moving Average, calculated by identifying the most recent external swing highs and lows in the market structure.
By determining these external swing pivot points, which act as significant highs and lows within the market range, the FRMA provides a unique moving average that adapts to market structure changes.
Upper Band:
The upper band shows the average price of the most recent external swing highs.
External swing highs are identified as the highest points between pivot points in the market structure.
This band helps traders identify potential overbought conditions when prices approach or exceed this upper band.
Lower Band:
The lower band shows the average price of the most recent external swing lows.
External swing lows are identified as the lowest points between pivot points in the market structure.
The script utilizes this band to identify potential oversold conditions, triggering entry signals as prices approach or drop below the lower band.
Adjustments Based on User Inputs:
Users can adjust how the upper and lower bands are calculated based on their preferences:
Upper/Lower: This method calculates the average bands using the prices of external swing highs and lows identified in the market.
Percentage Deviation from FRMA: Alternatively, users can opt to calculate the bands based on a percentage deviation from the middle FRMA. This approach provides flexibility to adjust the width of the bands relative to market conditions and volatility.
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What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
This comparison filter can be turned on (>) or off.
For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions.
⍺: MA Period | Σ: MA Timeframe
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What entry modes are used in this strategy? What are the underlying calculations?
The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal.
1. Breakout Entries :
- The strategy looks for pivot high points with a default period of 3.
- It stores the most recent high level in a variable.
- When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot high left bars period | ◨: Pivot high right bars period
2. Fractal Entries :
- The strategy looks for pivot low points with a default period of 3.
- When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot low left bars period | ◨: Pivot low right bars period
2. Hunt Entries :
- The strategy identifies a candle that wicks through the lower FRMA band.
- It waits for the next candle to close above the low of the wick candle.
- When this condition is met and the bar is closed, the strategy takes the buy entry.
By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points.
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What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
Initial Stop-Loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14).
Example - ATR (14) * 2
⍺: ATR period | Σ: ATR Multiplier
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
Example - ADR (20) * 2
⍺: ADR period | Σ: ADR Multiplier
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
Application in Strategy (ATR/ADR):
- The strategy calculates the current bar's ADR/ATR with a user-defined period.
- It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
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What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
Example:
If the entry price is $100, the initial risk is $10, and the RR ratio is 2, the break-even level is $100 + ($10 * 2) = $120.
FRMA Based:
Moves the stop-loss to break-even when the price hits the FRMA level at which the entry was taken.
Calculation:
Break-even level = FRMA level at the entry
Example:
If the FRMA level at entry is $102, the break-even level is set to $102 when the price reaches $102.
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
When Both Percentage (%) Based and RR Based Take Profit Levels Are Off:
The script will adjust the take profit level to the higher FRMA band set within user inputs.
Calculation:
Take profit level = Higher FRMA band length/timeframe specified by the user.
This ensures that when neither percentage-based nor risk-to-reward-based take profit methods are enabled, the strategy defaults to using the higher FRMA band as the take profit level, providing a consistent and structured approach to profit-taking.
For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price.
These calculations are crucial for managing risk and optimizing profitability in the strategy.
⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price
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What's the ADR filter? What does it do? What are the underlying calculations?
The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss.
Users can define the minimum ADR they want to be met before the script looks for entry conditions.
ADR Bias Filter:
- Compares the current bar ADR with the ADR (Defined by user):
- If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆)
- If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇)
Calculations:
1. Calculate ADR:
- Average the high prices over the specified period.
- Average the low prices over the same period.
- Find the difference between these average values in %.
2. Current ADR vs. ADR (DbU):
- Calculate the ADR for the current bar.
- Calculate the ADR (DbU).
- Compare the two values to determine if volatility has increased or decreased.
By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy.
>: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago.
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What's the probability filter? What are the underlying calculations?
The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions.
This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher.
Calculations:
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels.
3. Understanding probability calculations
1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive
2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
Example - BSL > 55%
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What's the range length Filter? What are the underlying calculations?
The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement.
Calculations:
Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100
Range Bias Identification:
Bullish Bias: The current range price has broken above the previous external swing high.
Bearish Bias: The current range price has broken below the previous external swing low.
Example - Range length filter is enabled | Range must be above 1%
>: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range
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What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences.
Example - Day filter | Session Filter
θ: Session time | Exchange time-zone
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What tables are available in this script?
Table Type:
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- OFF: Hides the performance table.
Profit Color:
- Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods.
Loss Color:
- Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods.
These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization.
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User-input styles and customizations:
To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
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How to Use This Algobuilder to Create a Profitable Edge and System:
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 100 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade value is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
Automation:
- Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm.
- Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management.
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What makes this strategy original?
1. Incorporating direct integration of probabilities into the strategy.
2. Utilizing built-in market structure-based moving averages across various timeframes.
4. Offering both investing and trading strategies, facilitating optimization from different perspectives.
5. Automation for efficient execution.
6. Providing a summary table for instant access to key parameters of the strategy.
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How to use automation?
For Traders:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Enter your PineConnector License ID in the designated field.
3. Specify the desired risk level.
4. Provide the Metatrader symbol.
5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol.
6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}.
7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address.
8. Double-check all settings on PineConnector to ensure the connection is successful.
9. Create the alert for entry/exit automation.
For Investors:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Choose "Investing" in the user-input settings.
3. Create an alert with a specified name.
4. Customize the notifications tab to receive alerts via email.
5. Buying/selling alerts will be triggered instantly upon entry or exit order execution.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
DCA-Integrated Trend Continuation StrategyIntroducing the DCA-Integrated Trend Continuation Strategy 💼💰
The DCA-Integrated Trend Continuation Strategy represents a robust trading methodology that harnesses the potential of trend continuation opportunities while seamlessly incorporating the principles of Dollar Cost Averaging (DCA) as a risk management and backup mechanism. This strategy harmoniously blends these two concepts to potentially amplify profitability and optimize risk control across diverse market conditions.
This strategy is well-suited for both trending and ranging markets. During trending markets, it aims to capture and ride the momentum of the trend while optimizing entry points. In ranging markets or pullbacks, the DCA feature comes into play, allowing users to accumulate more assets at potentially lower prices and potentially increase profits when the market resumes its upward trend. This cohesive approach not only enhances the overall effectiveness of the strategy but also fosters a more resilient and adaptable trading approach in ever-changing market dynamics.
💎 How it Works:
▶️ The strategy incorporates a customizable entry signal based on candlestick patterns, enabling the identification of potential trend continuation opportunities. By focusing on consecutive bullish candles, it detects the presence of bullish momentum, indicating an optimal time to enter a long position.
To refine the precision of the signals, traders can set a specific percentage threshold for the closing price of the candle, ensuring it is above a certain percentage of its body. This condition verifies strong bullish momentum and confirms significant upward movement within the candle, thereby increasing the reliability of the signal.
In addition, the strategy offers further confirmation by examining the relationship between the closing price of the signal candle and its previous candles. If the closing price of the signal candle is higher than its preceding candles, it provides an additional layer of assurance before entering a position. This approach is particularly effective in detecting sharp movements and capturing significant price shifts, as it focuses on identifying instances where the closing price shows clear strength and outperforms the previous candle's price action. By prioritizing such occurrences, the strategy aims to capture robust trends and capitalize on notable market movements.
▶️ During market downturns, the strategy incorporates intelligent management of price drops, offering flexibility through fixed or customizable price drop percentages. This unique feature allows for additional entries at specified drop percentages, enabling traders to accumulate positions at more favorable prices.
By strategically adjusting the custom price drop percentages, you can optimize your entry points to potentially maximize profitability. Utilizing lower percentages for initial entries takes advantage of price fluctuations, potentially yielding higher returns. On the other hand, employing higher percentages for final entries adopts a more cautious approach during significant market downturns, emphasizing enhanced risk management. This adaptive approach ensures that the strategy effectively navigates challenging market conditions while seeking to optimize overall performance.
▶️ To enhance performance and mitigate risks, the strategy integrates average purchase price management. This feature dynamically adjusts the average buy price percentage decrease after each price drop, expediting the achievement of the target point even in challenging market conditions. By reducing recovery times and ensuring investment safety, this strategy optimizes outcomes for traders.
▶️ Risk management is at the core of this strategy, prioritizing the protection of capital. It incorporates an account balance validation mechanism that conducts automatic checks prior to each entry, ensuring alignment with available funds. This essential feature provides real-time insights into the affordability of price drops and the number of entries, enabling traders to make informed decisions and maintain optimal risk control.
▶️ Furthermore, the strategy offers take profit options, allowing traders to secure gains by setting fixed percentage profits from the average buy price or using a trailing target. Stop loss protection is also available, enabling traders to set a fixed percentage from the average purchase price to limit potential losses and preserve capital.
▶️ This strategy is fully compatible with third-party trading bots, allowing for easy connectivity to popular trading platforms. By leveraging the TradingView webhook functionality, you can effortlessly link the strategy to your preferred bot and receive accurate signals for position entry and exit. The strategy provides all the necessary alert message fields, ensuring a smooth and user-friendly trading experience. With this integration, you can automate the execution of trades, saving time and effort while enjoying the benefits of this powerful strategy.
🚀 How to Use:
To effectively utilize the DCA-Integrated Trend Continuation Strategy, follow these steps:
1. Choose your preferred DCA Mode - whether by quantity or by value - to determine how you want to size your positions.
2. Customize the entry conditions of the strategy to align with your trading preferences. Specify the number of consecutive bullish candles, set a desired percentage threshold for the close of the signal candle relative to its body, and determine the number of previous candles to compare with.
3. Adjust the pyramiding parameter to suit your risk tolerance and desired returns. Whether you prefer a more conservative approach with fewer pyramids or a more aggressive stance with multiple pyramids, this strategy offers flexibility.
4. Personalize the price drop percentages based on your risk appetite and trading strategy. Choose between fixed or custom percentages to optimize your entries in different market scenarios.
5. Configure the average purchase price management settings to control the percentage decrease in the average buy price after each price drop, ensuring it aligns with your risk tolerance and strategy.
6. Utilize the account balance validation feature to ensure the strategy's actions align with your available funds, enhancing risk management and preventing overexposure.
7. Set take profit options to secure your gains and implement stop loss protection to limit potential losses, providing an additional layer of risk management.
8. Use the date and time filtering feature to define the duration during which the strategy operates, allowing for specific backtesting periods or integration with a trading bot.
9. For automated trading, take advantage of the compatibility with third-party trading bots to seamlessly integrate the strategy with popular trading platforms.
By following these steps, traders can harness the power of the DCA-Integrated Trend Continuation Strategy to potentially maximize profitability and optimize their trading outcomes in both trending and ranging markets.
⚙️ User Settings:
To ensure the backtest result is representative of real-world trading conditions, particularly in the highly volatile Crypto market, the default strategy parameters have been carefully selected to produce realistic results with a conservative approach. However, you have the flexibility to customize these settings based on your risk tolerance and strategy preferences, whether you're focusing on short-term or long-term trading, allowing you to potentially achieve higher profits. The backtesting was conducted using the BTCUSDT pair in 15-minute timeframe on the Binance exchange. Users can configure the following options:
General Settings:
- Initial Capital (Default: $10,000)
- Currency (Default: USDT)
- Commission (Default: 0.1%)
- Slippage (Default: 5 ticks)
Order Size Management:
- DCA Mode (Default: Quantity)
- Order Size in Quantity (Default: 0.01)
- Order Size in Value (Default: $300)
Strategy's Entry Conditions:
- Number of Consecutive Bullish Candles (Default: 3)
- Close Over Candle Body % (Default: 50% - Disabled)
- Close Over Previous Candles Lookback (Default: 14 - Disabled)
- Pyramiding Number (Default: 30)
Price Drop Management:
- Enable Price Drop Calculations (Default: Enabled)
- Enable Current Balance Check (Default: Enabled)
- Price Drop Percentage Type (Default: Custom)
- Average Price Move Down Percentage % (Default: 50%)
- Fixed Price Drop Percentage % (Default: 0.5%)
- Custom Price Drop Percentage % (Defaults: 0.5, 0.5, 0.5, 1, 3, 5, 5, 10, 10, 10)
TP/SL:
- Take Profit % (Default: 3%)
- Stop Loss % (Default: 100%)
- Enable Trailing Target (Default: Enabled)
- Trailing Offset % (Default: 0.1%)
Backtest Table (Default: Enabled)
Date & Time:
- Date Range Filtering (Default: Disabled)
- Start Time
- End Time
Alert Message:
- Alert Message for Enter Long
- Alert Message for Exit Long
By providing these customizable settings, the strategy allows you to tailor it to your specific needs, enhancing the adaptability and effectiveness of your trading approach.
🔐 Source Code Protection:
The source code of the DCA-Integrated Trend Continuation Strategy is designed to be robust, reliable, and highly efficient. Its original and innovative implementation merits protecting the source code and limiting access, ensuring the exclusivity of this strategy. By safeguarding the code, the integrity and uniqueness of the strategy are preserved, giving users a competitive edge in their trading activities.
Trend Follower Intraday [ Adjustable TF ]Trend Follower Intraday for 3 minute Time-Frame (Adjustable) , that has the time condition for Indian Markets as well.
Unlike the Free Scripts - Risk Management , Position Sizing , Partial Exit etc. are also included .
Send us a Message to know more about the strategy.
// ══════════════════════════════════════════════════════════════════════════ //
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) EMA1 crosses above EMA2 , is a Long condition .
2) EMA1 crosses below EMA2 , is a Short condition .
3) Green Section indicates Long position.
4) Red Section indicates Short position.
5) Allowed hours specifies the trade entry timing.
6) ATR STOP is the stop-loss value on chart , can be adjusted in INPUTS.
7) Target 1 is the 1st target value on chart , can be adjusted in INPUTS.
8) RISK is Maximum Risk per trade for the intraday trade can be changed .
9) Total Capital used can be adjusted under INPUTS.
10) ATR TRAIL is used for trailing after entry, as mentioned in the inputs below.
11) Check trades under the list of trades .
12) Trade only in liquid stocks .
13) Risk only 1-5% of total capital.
14) Inputs can be changed for better back-test results, but also manually check the trades before setting alerts
15) SQUARE OFF TIME - As you change the time frame , also change the square-off time to the candle's closing time.
Eg: For 3min Time-frame , Hour = 2Hrs | Minute = 57min
16) Strategy stops for the day if you have a loss .
17) COMMISSION value is set to 20Rs and SLIPPAGE value is set to 2 . Go to properties to change it .
*The input values and the results are mentioned under "BACKTEST RESULTS" below*
// ══════════════════════════════ //
// ————————> RISK MANAGEMENT <——————— //
// ══════════════════════════════ //
Risk management is done based on max loss per trade and can be adjusted in the INPUTS.
// ═══════════════════════════ //
// ————————> POSITION SIZE <——————— //
// ═══════════════════════════ //
Quantity of each trade is different based on the loss
// ═════════════════════════ //
// ————————> PROPERTIES <——————— //
// ═════════════════════════ //
COMMISSION , SLIPPAGE ,RECALCULATE is already mentioned in the code.
COMMISSION can be charges , based on the broker charges.
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the INPUT.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'Allowed hours' under Inputs specifies the time at which Entries should happen .
"Close All" function closes all the trades before 3pm , at the open of the next candle.
To change the time to close all trades , check INPUT.
All open trades get closed by 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 123 CLOSED TRADES ) <————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:JSWENERGY (3 min Time-Frame and with a capital of 3,00,000 ) gives us 81% profitability , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.957 ,net Profit of 43,000Rs .
Sharpe Ratio = 0.745
Sortino Ratio = 2.091
No strategy in the world promises 100% profits in all market conditions , so always define your risk before trading.
Also check Back-Test results manually ,before setting Alerts
The Graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) EMA1 ————————————————> 38
2) EMA2 ————————————————> 118
3) ALLOWED HRS ———————————> 9:35 TO 14:30
4) ATR STOP ——————————————> 3.2
5) RISK ——————————————————> 3000
6) ATR TRAIL ———————————————> 2.6
7) TARGET 1 ————————————————> 2.4
8) MAX POSITION VALUE ——————————> 3,00,000
8) MAX DRAWDOWN —————————————> 9,000
8) SQUARE-OFF ————————————————> 14:57
NSE:JSWENERGY
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NSE:JSWENERGY
Send us a message for FREE TRIALS | Instant Access
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Long Term Profitable Swing | AbbasA Story of a Profitable Swing Trading Strategy
Imagine you're sailing across the ocean, looking for the perfect wave to ride. Swing trading is quite similar—you're navigating the stock market, searching for the ideal moments to enter and exit trades. This strategy, created by Abbas, helps you find those waves and ride them effectively to profitable outcomes.
🌊 Finding the Perfect Wave (Entry)
Our journey begins with two simple signs that tell us a great trading opportunity is forming:
- Moving Averages: We use two lines that follow price trends—the faster one (EMA 16) reacts quickly to recent price moves, and the slower one (EMA 30) gives us a longer-term perspective. When the faster line crosses above the slower line, it's like a clear signal saying, "Hey! The wave is rising, and prices might move higher!"
- RSI Momentum: Next, we check a tool called the RSI, which measures momentum (how strongly prices are moving). If the RSI number is above 50, it means there's enough strength behind this rising wave to carry us forward.
When both signals appear together, that's our green light. It's time to jump on our surfboard and start riding this promising wave.
⚓ Safely Riding the Wave (Risk Management)
While we're riding this wave, we want to ensure we're safe from sudden surprises. To do this, we use something called the Average True Range (ATR), which measures how volatile (or bumpy) the price movements are:
- Stop-Loss: To avoid falling too hard, we set a safety line (stop-loss) 8 times the ATR below our entry price. This helps ensure we exit if the wave suddenly turns against us, protecting us from heavy losses.
- Take Profit: We also set a goal to exit the trade at 11 times the ATR above our entry. This way, we capture significant profits when the wave reaches a nice high point.
🌟 Multiple Rides, Bigger Adventures
This strategy allows us to take multiple positions simultaneously—like riding several waves at once, up to 5. Each trade we make uses only 10% of our trading capital, keeping risks manageable and giving us multiple opportunities to win big.
🗺️ Easy to Follow Settings
Here are the basic settings we use:
- Fast EMA**: 16
- Slow EMA**: 30
- RSI Length**: 9
- RSI Threshold**: 50
- ATR Length**: 21
- ATR Stop-Loss Multiplier**: 8
- ATR Take-Profit Multiplier**: 11
These settings are flexible—you can adjust them to better suit different markets or your personal trading style.
🎉 Riding the Waves of Success
This simple yet powerful swing trading approach helps you confidently enter trades, clearly know when to exit, and effectively manage your risk. It’s a reliable way to ride market waves, capture profits, and minimize losses.
Happy trading, and may you find many profitable waves to ride! 🌊✨
Please test, and take into account that it depends on taking multiple longs within the swing, and you only get to invest 25/30% of your equity.
Post-Open Long Strategy with ATR-based Stop Loss and Take ProfitThe "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit
The "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Entry and Exit Conditions:
Long Entry:
The price breaks above the identified resistance.
The market is in a lateralization phase with low volatility.
The price is above the 10 and 200-period EMAs.
RSI is above 30, and ADX is above 10.
No short-term downtrend is detected.
The last two candles are not both bearish.
The current candle is a "panic candle" (negative close).
Order Execution: The order is executed at the close of the candle that meets all conditions.
Exit from Position:
Dynamic Stop Loss: Set at 2 times the ATR below the entry price.
Dynamic Take Profit: Set at 4 times the ATR above the entry price.
The position is automatically closed upon reaching the Stop Loss or Take Profit.
How to Use the Strategy:
Application on Volatile Instruments:
Ideal for financial instruments that show significant volatility during the target market opening hours, such as indices or major forex pairs.
Recommended Timeframes:
Intraday timeframes, such as 5 or 15 minutes, to capture significant post-open moves.
Parameter Customization:
The default parameters are optimized but can be adjusted based on individual preferences and the instrument analyzed.
Backtesting and Optimization:
Backtesting is recommended to evaluate performance and make adjustments if necessary.
Risk Management:
Ensure position sizing respects risk management rules, avoiding risking more than 1-2% of capital per trade.
Originality and Benefits of the Strategy:
Unique Combination of Indicators: Integrates various technical metrics to filter signals, reducing false positives.
Volatility Adaptability: The use of ATR for Stop Loss and Take Profit allows the strategy to adapt to real-time market conditions.
Focus on Post-Lateralization Breakout: Aims to capitalize on significant moves following consolidation periods, often associated with strong directional trends.
Important Notes:
Commissions and Slippage: Include commissions and slippage in settings for more realistic simulations.
Capital Size: Use a realistic trading capital for the average user.
Number of Trades: Ensure backtesting covers a sufficient number of trades to validate the strategy (ideally more than 100 trades).
Warning: Past results do not guarantee future performance. The strategy should be used as part of a comprehensive trading approach.
With this strategy, traders can identify and exploit specific market opportunities supported by a robust set of technical indicators and filters, potentially enhancing their trading decisions during key times of the day.
CONSOLIDATION BAND BREAKOUT [5MIN TF]CONSOLIDTION BREAKOUT STRATEGY for 5 minute Time-Frame , that has the time condition adjustable for Indian Markets.
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Unlike the Free Scripts - Risk Management , Position Sizing , Partial Exit etc. are also included .
Message to know more about the strategy.
// ══════════════════════════════════════════════════════════════════════════ //
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above upper Level ,indicated by Red Line, is a Long condition .
2) Price crosses below lower Level ,indicated by Green Line , is a Short condition .
3) Candle close crosses above ema1 , is a part of the Long condition .
4) Candle close crosses below ema1 , is a part of the Short condition .
5) Allowed hours specifies the trade entry timing.
6) ATR STOP is the stop-loss value on chart , can be adjusted in INPUTS.
7) Target 1 is the 1st target value on chart , can be adjusted in INPUTS.
8) RISK is Maximum Risk per trade for the intraday trade can be changed .
9) Total Capital used can be adjusted under INPUTS.
10) ATR TRAIL is used for trailing after entry, as mentioned in the inputs below.
11) Check trades under the list of trades .
12) Trade only in liquid stocks .
13) Risk only 1-5% of total capital.
14) Inputs can be changed for better back-test results, but also manually check the trades before setting alerts
15) SQUARE OFF TIME - As you change the time frame , also change the square-off time to that candle's closing time.
Eg: For 3min Time-frame , Hour = 2Hrs | Minute = 57min
16) Strategy stops for the day if you have a loss .
*The input values and the results are mentioned under "BACKTEST RESULTS" below*
// ══════════════════════════════ //
// ————————> RISK MANAGEMENT <——————— //
// ══════════════════════════════ //
Risk management is done based on max loss per trade and can be adjusted in the INPUTS.
// ═══════════════════════════ //
// ————————> POSITION SIZE <——————— //
// ═══════════════════════════ //
Quantity of each trade is different based on the loss
// ═════════════════════════ //
// ————————> PROPERTIES <——————— //
// ═════════════════════════ //
COMMISSION , SLIPPAGE ,RECALCULATE is already mentioned .
COMMISSION can be charges , based on the broker charges.
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the INPUT.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'Allowed hours' under Inputs specifies the time at which Entries should happen .
"Close All" function closes all the trades before 3pm , at the open of the next candle.
To change the time to close all trades , check INPUT.
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 123 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:TCS (5 min Time-Frame and with a capital of 1,00,000 ) gives us 77% profitability , as shown below
It was tested for a period a 1 year with a Profit Factor of 2.143 ,net Profit of 10,886 Rs .
The Initial Capital and Risk can be increased for better results.
The graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) LENGTH ——————————————> 79
2) MUT_STDEV ————————————> 2.3
3) ALLOWED HRS ———————————> 9:25 TO 14:30
4) ATR STOP ——————————————> 2.2
5) RISK ——————————————————> 400
6) ATR TRAIL ———————————————> 2.6
7) TARGET 1 ————————————————> 2.1
8) MAX POSITION VALUE ——————————> 1,00,000
8) MAX DRAWDOWN —————————————> 2,000
8) SQUARE-OFF ————————————————> 14:55
NSE:TCS
Apply it to your charts Now !!
Send us a message to know more about this strategy
Thank You ☺ NSE:TCS
Omni Trader Accompanying Backtesting StrategyVersion 1.0
Purpose
This backtesting strategy indicator is a accompanying tool for use with my popular trading and alert indicator: Omni Trader | RMI EMA RSI VOL | Margin Focused Indicator
Reference Indicator Link:
Features
This strategy has been programmed to act exactly how the accompanying indicator would be used with an automated strategy such as Autoview or through manual trading
Has identical coloured signals with correct icons for reference with the indicators standard alert conditions (LONG/SHORT)
The ability to toggle on or off all the logic and UI presets you could previously use to enhance the standard indicator
Fully customisable in the settings regarding trading strategy to match exactly how you have the reference indicator set up with alerts or how you are trading manually with it.
Ability to choose a timeframe, want to ignore the crypto boom at the latter stages of 2017? Sure you can, change the time frames in the settings to see a more recent representation of your trades.
Stop Loss & Take Profit enabled in this back tester for fine tuning of your strategy, especially useful for automated users to refine the most profitable settings for your style.
Access
This indicator is free for existing owners of my Omni Trader | RMI EMA RSI VOL | Margin Focused Indicator linked above as an accompanying tool to improve their strategy and net more profit. If you would like access to any of my indicators or would like to know more please find me on my community discord channel where you can find indicator details/documentation and general help:
Discord Link: discord.gg
Thank you for the immense support everyone, happy trading!
- Falco
High-Low Breakout Strategy with ATR traling Stop LossThis script is a TradingView Pine Script strategy that implements a High-Low Breakout Strategy with ATR Trailing Stop.created by SK WEALTH GURU, Here’s a breakdown of its key components:
Features and Functionality
Custom Timeframe and High-Low Detection
Allows users to select a custom timeframe (default: 30 minutes) to detect high and low levels.
Tracks the high and low within a user-specified period (e.g., first 30 minutes of the session).
Draws horizontal lines for high and low, persisting for a specified number of days.
Trade Entry Conditions
Long Entry: If the closing price crosses above the recorded high.
Short Entry: If the closing price crosses below the recorded low.
The user can choose to trade Long, Short, or Both.
ATR-Based Trailing Stop & Risk Management
Uses Average True Range (ATR) with a multiplier (default: 3.5) to determine a dynamic trailing stop-loss.
Trades reset daily, ensuring a fresh start each day.
Trade Execution and Partial Profit Taking
Stop-loss: Default at 1% of entry price.
Partial profit: Books 50% of the position at 3% profit.
Max 2 trades per day: If the first trade hits stop-loss, the strategy allows one re-entry.
Intraday Exit Condition
All positions close at 3:15 PM to ensure no overnight risk.
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
SUPPORT RESISTANCE STRATEGY [5MIN TF]A SUPPORT RESISTANCE BREAKOUT STRATEGY for 5 minute Time-Frame , that has the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above Resistance Level ,indicated by Red Line, is a Long condition.
2) Price crosses below Support Level ,indicated by Green Line , is a Short condition.
3) Candle high crosses above ema1, is a part of the Long condition .
4) Candle low crosses below ema1, is a part of the Short condition .
5) Volume Threshold is an added confirmation for long/short positions.
6) Maximum Risk per trade for the intraday trade can be changed .
7) Default qty size is set to 50 contracts , which can be changed under settings → properties → order size.
8) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
→ L_Bars ———————————> Length of Resistance / Support Levels.
→ R_Bars ———————————> Length of Resistance / Support Levels.
→ Volume Break ———————> Volume Breakout from range to confirm Long/Short position.
→ Price Cross Ema —————> Added condition as explained above (3) and (4).
→ ATR LONG —————————> ATR stoploss trail for Long positions.
→ ATR SHORT ————————> ATR stoploss trail for Short positions.
→ RISK ————————————> Maximum Risk per trade intraday.
The strategy was back-tested on TCS ,the input values and the results are mentioned under "BACKTEST RESULTS" below.
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 50 contracts , which can be changed under
Settings
↓
Properties
↓
Order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 27.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm , at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 92 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 100 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:TCS ( 5 min Time-Frame and contract size 50) gives us 60% profitability , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.8 ,net Profit of 30,000 Rs profit .
Sharpe Ratio : 0.49
Sortino Ratio : 1.4
The graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) L_Bars —————————> 4
2) R_Bars —————————> 4
3) Volume Break ————> 5
4) Price Cross Ema ——> 100
5) ATR LONG ——————> 2.4
6) ATR SHORT —————> 2.6
7) RISK —————————> 2000
8) Default qty size ——> 50
NSE:TCS
Save it to favorites.
Apply it to your charts Now !!
Thank You ☺ NSE:TCS
Cava Signals Backtesting/VisualizerPLEASE READ THE DESCRIPTION CAREFULLY
Trying this again, as it seems I keep violating the rules unintentionally. Moderator, please forgive me as I try to make this right.
This backtesting/visualizer script was created for me to get a visual idea of the Cava Signals indicator throughout its development time and continuous optimization.
This script is to be used on the 30-minute timeframe on supported markets, and whether I can only publish strategies on regular candles, the indicator is meant to trigger on heikin ashi candles.I understand backtesting on non-regular candles produces unrealistic results, but I emphasize that this script is more for visualization purposes rather than accurate $ amounts from the trades. The signals are used along with a dedicated bot configuration, so part of the strategy is not managed by the script, but by the bot's config.
Some behind the scenes on what we are looking at:
a combination of ema and sma crosses on different time frames (5m, 15m, 30m, 60m and 90m) - we call this the wave trend
a combination of stochastic rsi on different time frames (10m, 30m)
a combination of schaff trend cycles on different time frames (5m, 20m and 30m)
a combination of money flow index on different time frames (10m and 30m)
volume information for each supported market/pair
and a couple of other info particular to each pair
With the above combination of data points, we try to optimize our strategy for an entry, for dca'ing down in case the coin goes down as well as dca'ing up to maximize profit when a coin is going up, take profit levels when we recognize a good time to do so, and of course, a closing level. I would like to emphasize the *visualization* purpose of this script in recognizing lows, highs, and market structure to identify the important levels to signal - this script is NOT to be used for accurate backtesting, but for an idea of the overall performance of when signals are triggered.
Let me try to explain the workflow and icons you see on the chart:
The colored circles on the bottom of the chart are all buy signals; each color corresponds to a particular buy signal, we have a combination of 9 possible situations that would trigger a buy signal. Some would trigger a buy signal only in combination with other buy signals or other indicators within the script. we also display a green upwards arrow below bars when a buy signal is triggered.
The colored arrows pointing down on the top of the chart are close signals. We have a combination of 5 closing criteria each color corresponds to one, just like the buy signals do. We only close a trade in profit. If not in profit, we will look to DCA down.
DCA signals are shown by the green flag above bars. they are signals to DCA up or down depending on the trade being negative or positive. DCA'ing up or down is also managed by the bot's configuration for limits on when to accept the signal.
Take Profit levels are shown by the green diamond above bars and work in conjunction with the bot's config on when to take the signal if at all and other take profit levels. Usually, when we hit the first take profit level we move our stop loss to entry via the bot's take profit safety feature. You can see this call with the close entry named TPS .
The black bars you may see on the chart is to illustrate when the market is extended based on a particular strategy. During this period we will not trigger a buy signal unless there is a huge spike in positive volume .
The green number below the bars is the total positive delta volume on the buy candles.
On the table on the right upper corner, we show some information on the market and performance of the backtesting - for visualization purposes only!
Currently, the script is tailored to work with the following markets/pairs:
Binance Spot: ADA, ALGO, ATOM, AVAX, BNB, BTC , DOT, ETH, LINK, LUNA, MATIC, SOL, VET, XRP, XTZ
Binance Futures: BTC , ETH, ADA, ALGO, ATOM, BNB, COMP, DOT, ENJ , LINK, OCEAN, OMG, SOL, VET, XMR, XRP, XTZ, AVAX, AAVE, DOGE, LTC, LUNA, MKR , NEAR, ONT, RUNE, SUSHI, LTC, XLM , COMP, ONT, THETA, FTM , EGLD , WAVES, ONE, HTN , CHZ , HOT, MANA, CRV , RVN, BAT, ANKR, 1INCH, ALICE, ATA , AXS , CHR , COTI, NKN , RAY, REN, SRM , SXP , TLM
ByBit Inverse Perpetual: BTCUSD , ETHUSD
ByBit Futures: AAVE, ADA, ALGO, AVAX, AXS , BNB, BTC , DOT, ETH, LINK, LTC, MATIC, SOL, SUSHI, UNI , XEM, XRP, XTZ
The chosen pairs are subject to change based on the best-performing assets we are constantly analyzing.
I hope this helps to understand the script, its purpose and ideas. I hope this satisfies the community rules - it was not my intention to break them - if there's anything on the above or the script that still violates the guidelines, please let me know and accept my apologies in advance.
If anyone would like to know more, let me know in the comment section.
Thank you!
Swing trade - Libertus - STRATEGYHello all.
Month of hard work, testing and fine tunning went into making of this strategy.
I wanted to be able to leave trading to bot and spend more time away from charts and this strategy finally enabled me to do just that!
It's a swing trade strategy which will always keep you in trade (if used on exchange which allows you to short).
If you use 4H time frame you'll get about 2-3 trades a week.
As you should be able to see bellow, strategy has very good profitability of 60+% in last 6 months with small drag-down and nice profits.
It's optimized for ETH on 4H time, but settings can be adapted for different assets and time frames.
Best settings for ETH 4H time frame are default 0/0 with both Filter 1 and Filter 2 enabled.
Settings can be changed in positive +1, +2, +3 etc., and negative -1, -2, -3...
Strategy profitability is based on buying and selling 10 ETH (not more, not less) in every trade. You can see +20 or -20 on every trade which means 10 ETH for closing current position and 10 ETH for opening new position. If you are trading more or less then this, you can easily calculate your profitability via this.
Indicator which could be used manually or via bot is in production, will be finished soon!
Good luck trading!
VIDYA ProTrend Multi-Tier ProfitHello! This time is about a trend-following system.
VIDYA is quite an interesting indicator that adjusts dynamically to market volatility, making it more responsive to price changes compared to traditional moving averages. Balancing adaptability and precision, especially with the more aggressive short trade settings, challenged me to fine-tune the strategy for a variety of market conditions.
█ Introduction and How it is Different
The "VIDYA ProTrend Multi-Tier Profit" strategy is a trend-following system that combines the VIDYA (Variable Index Dynamic Average) indicator with Bollinger Bands and a multi-step take-profit mechanism.
Unlike traditional trend strategies, this system allows for more adaptive profit-taking, adjusting for long and short positions through distinct ATR-based and percentage-based targets. The innovation lies in its dynamic multi-tier approach to profit-taking, especially for short trades, where more aggressive percentages are applied using a multiplier. This flexibility helps adapt to various market conditions by optimizing trade management and profit allocation based on market volatility and trend strength.
BTCUSD 6hr performance
█ Strategy, How it Works: Detailed Explanation
The core of the "VIDYA ProTrend Multi-Tier Profit" strategy lies in the dual VIDYA indicators (fast and slow) that analyze price trends while accounting for market volatility. These indicators work alongside Bollinger Bands to filter trade entries and exits.
🔶 VIDYA Calculation
The VIDYA indicator is calculated using the following formula:
Smoothing factor (𝛼):
alpha = 2 / (Length + 1)
VIDYA formula:
VIDYA(t) = alpha * k * Price(t) + (1 - alpha * k) * VIDYA(t-1)
Where:
k = |Chande Momentum Oscillator (MO)| / 100
🔶 Bollinger Bands as a Volatility Filter
Bollinger Bands are calculated using a rolling mean and standard deviation of price over a specified period:
Upper Band:
BB_upper = MA + (K * stddev)
Lower Band:
BB_lower = MA - (K * stddev)
Where:
MA is the moving average,
K is the multiplier (typically 2), and
stddev is the standard deviation of price over the Bollinger Bands length.
These bands serve as volatility filters to identify potential overbought or oversold conditions, aiding in the entry and exit logic.
🔶 Slope Calculation for VIDYA
The slopes of both fast and slow VIDYAs are computed to assess the momentum and direction of the trend. The slope for a given VIDYA over its length is:
Slope = (VIDYA(t) - VIDYA(t-n)) / n
Where:
n is the length of the lookback period. Positive slope indicates bullish momentum, while negative slope signals bearish momentum.
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🔶 Entry and Exit Conditions
- Long Entry: Occurs when the price moves above the slow VIDYA and the fast VIDYA is trending upward. Bollinger Bands confirm the signal when the price crosses the upper band, indicating bullish strength.
- Short Entry: Happens when the price drops below the slow VIDYA and the fast VIDYA trends downward. The signal is confirmed when the price crosses the lower Bollinger Band, showing bearish momentum.
- Exit: Based on VIDYA slopes flattening or reversing, or when the price hits specific ATR or percentage-based profit targets.
🔶 Multi-Step Take Profit Mechanism
The strategy incorporates three levels of take profit for both long and short trades:
- ATR-based Take Profit: Each step applies a multiple of the ATR (Average True Range) to the entry price to define the exit point.
The first level of take profit (long):
TP_ATR1_long = Entry Price + (2.618 * ATR)
etc.
█ Trade Direction
The strategy offers flexibility in defining the trading direction:
- Long: Only long trades are considered based on the criteria for upward trends.
- Short: Only short trades are initiated in bearish trends.
- Both: The strategy can take both long and short trades depending on the market conditions.
█ Usage
To use the strategy effectively:
- Adjust the VIDYA lengths (fast and slow) based on your preference for trend sensitivity.
- Use Bollinger Bands as a filter for identifying potential breakout or reversal scenarios.
- Enable the multi-step take profit feature to manage positions dynamically, allowing for partial exits as the price reaches specified ATR or percentage levels.
- Leverage the short trade multiplier for more aggressive take profit levels in bearish markets.
This strategy can be applied to different asset classes, including equities, forex, and cryptocurrencies. Adjust the input parameters to suit the volatility and characteristics of the asset being traded.
█ Default Settings
The default settings for this strategy have been designed for moderate to trending markets:
- Fast VIDYA Length (10): A shorter length for quick responsiveness to price changes. Increasing this length will reduce noise but may delay signals.
- Slow VIDYA Length (30): The slow VIDYA is set longer to capture broader market trends. Shortening this value will make the system more reactive to smaller price swings.
- Minimum Slope Threshold (0.05): This threshold helps filter out weak trends. Lowering the threshold will result in more trades, while raising it will restrict trades to stronger trends.
Multi-Step Take Profit Settings
- ATR Multipliers (2.618, 5.0, 10.0): These values define how far the price should move before taking profit. Larger multipliers widen the profit-taking levels, aiming for larger trend moves. In higher volatility markets, these values might be adjusted downwards.
- Percentage Levels (3%, 8%, 17%): These percentage levels define how much the price must move before taking profit. Increasing the percentages will capture larger moves, while smaller percentages offer quicker exits.
- Short TP Multiplier (1.5): This multiplier applies more aggressive take profit levels for short trades. Adjust this value based on the aggressiveness of your short trade management.
Each of these settings directly impacts the performance and risk profile of the strategy. Shorter VIDYA lengths and lower slope thresholds will generate more trades but may result in more whipsaws. Higher ATR multipliers or percentage levels can delay profit-taking, aiming for larger trends but risking partial gains if the trend reverses too early.
