Range BreakerStrategy Description: Range Breaker
The Range Breaker strategy is a breakout trading strategy that aims to capture profits when the price of a financial instrument moves out of a defined range. The strategy identifies swing highs and swing lows over a specified lookback period and enters long or short positions when the price breaks above the swing high or below the swing low, respectively. It also employs stop targets based on a percentage to manage risk and protect profits.
Beginner's Guide:
Understand the concepts:
a. Swing High: A swing high is a local peak in price where the price is higher than the surrounding prices.
b. Swing Low: A swing low is a local trough in price where the price is lower than the surrounding prices.
c. Lookback Period: The number of bars or periods the strategy analyzes to determine swing highs and swing lows.
d. Stop Target: A predetermined price level at which the strategy will exit the position to manage risk and protect profits.
Configure the strategy:
a. Set the initial capital, order size, commission, and pyramiding as needed for your specific trading account.
b. Choose the desired lookback period to identify the swing highs and lows.
c. Set the stop target multiplier and stop target percentage as desired to manage risk and protect profits.
Backtest the strategy:
a. Set the backtest start date to analyze the strategy's historical performance.
b. Observe the backtesting results to evaluate the strategy's effectiveness and adjust the parameters if necessary.
Implement the strategy:
a. Apply the strategy to your preferred financial instrument on the TradingView platform.
b. Monitor the strategy's performance and adjust the parameters as needed to optimize its effectiveness.
Risk management:
a. Always use a stop target to protect your trading capital and manage risk.
b. Don't risk more than a small percentage of your trading capital on a single trade.
c. Be prepared to adjust the strategy or stop trading it if the market conditions change significantly.
Adjusting the Lookback Period and Timeframes for Optimal Strategy Performance
The Range Breaker strategy uses a lookback period to identify swing highs and lows, which serve as the basis for determining entry and exit points for long and short positions. By adjusting the lookback period and analyzing different timeframes, you can potentially find the best strategy configuration for each specific asset.
Adjusting the lookback period:
The lookback period is a critical parameter that affects the sensitivity of the strategy to price movements. A shorter lookback period will make the strategy more sensitive to smaller price fluctuations, resulting in more frequent trading signals. On the other hand, a longer lookback period will make the strategy less sensitive, generating fewer signals but potentially capturing larger price movements.
To optimize the lookback period for a specific asset, you can test different lookback values and compare their performance in terms of risk-adjusted returns, win rate, and other relevant metrics. Keep in mind that using an overly short lookback period may lead to overtrading and increased transaction costs, while an overly long lookback period may cause the strategy to miss profitable trading opportunities.
Analyzing different timeframes:
Timeframes refer to the duration of each bar or candlestick on the chart. Shorter timeframes (e.g., 5-minute, 15-minute, or 30-minute) focus on intraday price movements, while longer timeframes (e.g., daily, weekly, or monthly) capture longer-term trends. The choice of timeframe affects the number of trading signals generated by the strategy and the length of time each position is held.
To find the best strategy for each asset, you can test the Range Breaker strategy on different timeframes and analyze its performance. Keep in mind that shorter timeframes may require more active monitoring and management due to the increased frequency of trading signals. Longer timeframes, on the other hand, may require more patience as positions are held for extended periods.
Finding the best strategy for each asset:
Every asset has unique price characteristics that may affect the performance of a trading strategy. To find the best strategy for each asset, you should:
a. Test various lookback periods and timeframes, observing the strategy's performance in terms of profitability, risk-adjusted returns, and win rate.
b. Consider the asset's historical price behavior, such as its volatility, liquidity, and trend-following or mean-reverting tendencies.
c. Evaluate the strategy's performance during different market conditions, such as bullish, bearish, or sideways markets, to ensure its robustness.
d. Keep in mind that each asset may require a unique set of strategy parameters for optimal performance, and there may be no one-size-fits-all solution.
By experimenting with different lookback periods and timeframes, you can fine-tune the Range Breaker strategy for each specific asset, potentially improving its overall performance and adaptability to changing market conditions. Always practice proper risk management and be prepared to make adjustments as needed.
Remember that trading strategies carry inherent risk, and past performance is not indicative of future results. Always practice proper risk management and consider your own risk tolerance before trading with real money.
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3Commas Bot DCA Backtester & Signals FREEThis is a DCA Strategy backtester + signals, built to emulate the 3Commas DCA bots. It uses your choice of 4 different buy signals, 2 of which can be adjusted in the settings. Everything is customizable so you can backtest specific settings with different buy signals and find the best performing strategy for your risk tolerance and capital. It can be used to backtest strategies on stocks as well, but just make sure your base order is larger than the share price for the entire backtesting range or it will not calculate properly.
You can use this template to code your own buy signals and then backtest them as a DCA strategy if you know some basic pine script.
The indicator shows all of your backtesting orders on the chart. The red line is your take profit level, the blue line is your average price level, the white line is your first order and the green lines are your average down orders. If you enable a stop loss in the settings your stop loss will be shown as an orange line once all of your average down orders have been hit, it will not be set until price has dipped below your covered trading range.
These levels update when things change during backtesting so you can visualize your strategy and how it would perform as well as see if your percentage deviation is large enough to cover dips. When backtesting trades are taken, the chart will show where they were taken(in backtesting) along with info on those trades such as the number each order is, the size of that order and the percentage deviation that order is from the initial buy.
SENDING SIGNALS TO 3COMMAS
Tradingview cannot sync this backtester to 3Commas and with the way alerts are setup for strategies on Tradingview, the best option for you to give signals to your bot would be to use this backtester to figure out what trigger you want to use and then setup that indicator separately to send alerts to your bot. All of the indicators used for signals in this backtester are available for free and can be configured to match this backtester and send alerts to 3Commas for you. Just make sure you set your alerts to once per bar close and don’t use less than a 15 second timeframe because then you could trigger the Tradingview threshold for alerts and get your alerts shut off.
You can also use this backtester with your own buy triggers if you know a little pine script. Just make copy of the script and code in your own buy signals and see how it backtests.
INFO PANEL FOR ANALYZING YOUR STRATEGY
The right hand side of the screen will show an info panel that shows a lot of different information so you can quickly see your bot settings and how it performed right on the screen.
In the top right corner you will see in purple your bot settings. These include your stoploss % if turned on, take profit %, average down order %, average down order % multiplier, volume multiplier, max number of orders allowed and size of your base order.
The top section of the first column “Current Trade” shows these stats: the open trade’s average price, the open trade’s take profit price, the open trade’s PNL, how far price is from your open tarde’s take profit level in percentage, your open position size and number of open orders.
The bottom section of the first column “Overall Performance” shows these stats: total number of trades taken during backtesting range, the largest amount of trades that were open at one time during backtesting, the max drawdown, the average number of bars per trade, gross profit, net profit, percent profit from your initial capital, current portfolio value and your initial capital.
CUSTOMIZABLE OPTIONS TO FIND THE PERFECT STRATEGY
Stoploss On/Off
This will turn your stoploss on or off. By default it is set to off and will not affect anything unless turned on.
Stoploss Percentage
This is the percentage below your final average down order price that will be set as a stoploss to keep your account from going too far in the red on big dips.
Take Profit Percentage - This is the percentage of profit you want the trade to hit before taking profit on your entire DCA trade. This level updates everytime you average down.
Average Down Percentage - This is the percentage that price has to drop from your initial order to initiate your first safety order. If the Average Down Percent Multiplier is set to 1 then this percentage will be the same for every average down order.
Average Down Percentage Multiplier - This multiplies your Average Down Percentage so each safety order needs a larger percentage deviation than the previous one. This keeps your buys closer together at the beginning and further apart when you hit more orders so you can extend your trading range but still be aggressive when price is going sideways.
Volume Multiplier Per New Order - This multiplies the size of each trade based on your base order. If you set it to a 2x multiplier then each average down order will be 2 times the size of the last one. So for example, a $100 base order with a 2x multiplier would have these values for the first 3 average down orders: 200, 400, 800.
Size Of Base Order - This is the size of your first position entry and will be used as a starting point for the volume multiplier. If your base order is $100 then it will buy $100 worth of whatever crypto you are backtesting this on. If you are looking at stock charts, you need to make sure your base order is higher than the share price across the entire backtesting range or it will not perform correctly.
Max Number Of Orders - This is the maximum number of orders the bot can take, including your base order. Adjust this to suit the amount of capital you are willing to allocate to your bot based on how much money it will require to run according to your bot settings.
TIPS ON HOW TO USE FOR BEST RESULTS
If you don’t have a lot of capital to work with, then use longer timeframes with a reasonable take profit percentage so that you don’t need a lot of average down orders. You can also try keeping the volume multiplier close to 1.
You can use the 3Commas dca bot settings page to see how much capital you will need for your strategy if you match it to the settings you have on this indicator. You can also check to see how much of a percentage deviation your bot is covering to make sure you have a reasonable range to trade in and orders to cover big dips. You can also check your coverage by seeing how far down the chart the green lines cover, which are your average down orders.
Make sure the initial capital in the properties tab of the settings has enough to cover all of your orders otherwise you will get unrealistic backtesting results. Also, make sure you leave the order size in the properties tab on contracts so it calculates your trades correctly. The only settings you need to touch in the properties tab is the initial capital. Unless you are trading somewhere that has lower commission fees, then you can change that to match, but leave all the other settings as is for it to function properly.
Increasing the volume multiplier will make your average price and take profit target follow the price action a lot closer as price falls, but it can also lead to having very large orders very quickly once you get into the 1.5-3x multiple range. Try using a high volume multiplier with less safety orders and you will get better results, however you need to have money on the sidelines to add on major dips to keep your bot turning a profit. Be very careful with this as greed and impatience will hurt your overall performance. This bot is meant to make money with lots of small wins so don’t get greedy and make sure you have enough money to cover large dips. If you are being aggressive with your bot, then I recommend only using 25% or less of your portfolio to trade aggressively and then use the smart trade feature on 3commas to add chunks of funds to your trades when price dips below your last safety order. Or if you want it to run without any supervision, then use lower volume multipliers and have lots of safety orders that can cover entire bear markets and still keep buying lower.
It’s a good idea to have some capital on the sidelines that you can add in when price dips quickly. This will help lower your average price and allow your bot to get out in profit quicker. 3Commas bot has a smart trade feature that will allow you to track your average price when adding extra funds and it will automatically update your other orders which is very convenient. Look at the longer timeframes when price dips and only add chunks at major areas where price is very likely to bounce. Or you can be aggressive when trading and add to your position when price dips and is at a likely bounce zone to maximize profits.
Only trade coins that have a good amount of liquidity as the larger your orders get, the harder it will be to sell if there isn’t much liquidity. Also, beware of how large your first order is as it will usually be a market order and can move the market if there is not much liquidity.
Since this bot takes a lot of trades and performs best when taking small profits consistently, you will need to factor in exchange fees. The bot is set to .5% commission(you can change this) on the buy and sell orders as most exchanges charge that amount. Some exchanges offer no fee trading on certain coins so be sure to look around for those so you can keep the commissions and maximize profits.
I strongly encourage you to try out a lot of different setting combinations across multiple different coins and do it across a few months to see how it would have performed under various market conditions. This will help you get a better idea of how much of a percentage deviation you’ll need to be able to cover to keep your bot running and making constant profits. You can also use the deep backtesting feature of the strategy panel to see how it would have done, but just beware that the info panel of the indicator will not reflect deep backtesting results, only the normal backtesting range.
MARKETS
This backtester can be used on any market including crypto, stocks, forex & futures. You just need to make sure your base order is larger than the share price when using this on things besides crypto.
TIMEFRAMES
This backtester can be used on all timeframes.
[MT] Strategy Backtest Template| Initial Release | | EN |
An update of my old script, this script is designed so that it can be used as a template for all those traders who want to save time when programming their strategy and backtesting it, having functions already programmed that in normal development would take you more time to program, with this template you can simply add your favorite indicator and thus be able to take advantage of all the functions that this template has.
🔴Stop Loss and 🟢Take Profit:
No need to mention that it is a Stop Loss and a Take Profit, within these functions we find the options of: fixed percentage (%), fixed price ($), ATR, especially for Stop Loss we find the Pivot Points, in addition to this, the price range between the entry and the Stop Loss can be converted into a trailing stop loss, instead, especially for the Take Profit we have an option to choose a 1:X ratio that complements very well with the Pivot Points.
📈Heikin Ashi Based Entries:
Heikin Ashi entries are trades that are calculated based on Heikin Ashi candles but their price is executed to Japanese candles, thus avoiding false results that occur in Heikin candlestick charts, this making in certain cases better results in strategies that are executed with this option compared to Japanese candlesticks.
📊Dashboard:
A more visual and organized way to see the results and necessary data produced by our strategy, among them we can see the dates between which our operations are made regardless if you have activated some time filter, usual data such as Profit, Win Rate, Profit factor are also displayed in this panel, additionally data such as the total number of operations, how many were gains and how many losses, the average profit and loss for each operation and finally the maximum profits and losses followed, which are data that will be very useful to us when we elaborate our strategies.
Feel free to use this template to program your own strategies, if you find errors or want to request a new feature let me know in the comments or through my social networks found in my tradingview profile.
| Update 1.1 | | EN |
➕Additions: '
Time sessions filter and days of the week filter added to the time filter section.
Option to add leverage to the strategy.
5 Moving Averages, RSI, Stochastic RSI, ADX, and Parabolic Sar have been added as indicators for the strategy.
You can choose from the 6 available indicators the way to trade, entry alert or entry filter.
Added the option of ATR for Take Profit.
Ticker information and timeframe are now displayed on the dashboard.
Added display customization and color customization of indicator plots.
Added customization of display and color plots of trades displayed on chart.
📝Changes:
Now when activating the time filter it is optional to add a start or end date and time, being able to only add a start date or only an end date.
Operation plots have been changed from plot() to line creation with line.new().
Indicator plots can now be controlled from the "plots" section.
Acceptable and deniable range of profit, winrate and profit factor can now be chosen from the "plots" section to be displayed on the dashboard.
Aesthetic changes in the section separations within the settings section and within the code itself.
The function that made the indicators give inputs based on heikin ashi candles has been changed, see the code for more information.
⚙️Fixes:
Dashboard label now projects correctly on all timeframes including custom timeframes.
Removed unnecessary lines and variables to take up less code space.
All code in general has been optimized to avoid the use of variables, unnecessary lines and avoid unnecessary calculations, freeing up space to declare more variables and be able to use fewer lines of code.
| Lanzamiento Inicial | | ES |
Una actualización de mi antiguo script, este script está diseñado para que pueda ser usado como una plantilla para todos aquellos traders que quieran ahorrar tiempo al programar su estrategia y hacer un backtesting de ella, teniendo funciones ya programadas que en el desarrollo normal te tomaría más tiempo programar, con esta plantilla puedes simplemente agregar tu indicador favorito y así poder aprovechar todas las funciones que tiene esta plantilla.
🔴Stop Loss y 🟢Take Profit:
No hace falta mencionar que es un Stop Loss y un Take Profit, dentro de estas funciones encontramos las opciones de: porcentaje fijo (%), precio fijo ($), ATR, en especial para Stop Loss encontramos los Pivot Points, adicionalmente a esto, el rango de precio entre la entrada y el Stop Loss se puede convertir en un trailing stop loss, en cambio, especialmente para el Take Profit tenemos una opción para elegir un ratio 1:X que se complementa muy bien con los Pivot Points.
📈Entradas Basadas en Heikin Ashi:
Las entradas Heikin Ashi son operaciones que son calculados en base a las velas Heikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así́ los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas.
📊Panel de Control:
Una manera más visual y organizada de ver los resultados y datos necesarios producidos por nuestra estrategia, entre ellos podemos ver las fechas entre las que se hacen nuestras operaciones independientemente si se tiene activado algún filtro de tiempo, datos usuales como el Profit, Win Rate, Profit factor también son mostrados en este panel, adicionalmente se agregaron datos como el número total de operaciones, cuantos fueron ganancias y cuantos perdidas, el promedio de ganancias y pérdidas por cada operación y por ultimo las máximas ganancias y pérdidas seguidas, que son datos que nos serán muy útiles al elaborar nuestras estrategias.
Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mis redes sociales que se encuentran en mi perfil de tradingview.
| Actualización 1.1 | | ES |
➕Añadidos:
Filtro de sesiones de tiempo y filtro de días de la semana agregados al apartado de filtro de tiempo.
Opción para agregar apalancamiento a la estrategia.
5 Moving Averages, RSI, Stochastic RSI, ADX, y Parabolic Sar se han agregado como indicadores para la estrategia.
Puedes escoger entre los 6 indicadores disponibles la forma de operar, alerta de entrada o filtro de entrada.
Añadido la opción de ATR para Take Profit.
La información del ticker y la temporalidad ahora se muestran en el dashboard.
Añadido personalización de visualización y color de los plots de indicadores.
Añadido personalización de visualización y color de los plots de operaciones mostradas en grafica.
📝Cambios:
Ahora al activar el filtro de tiempo es opcional añadir una fecha y hora de inicio o fin, pudiendo únicamente agregar una fecha de inicio o solamente una fecha de fin.
Los plots de operaciones han cambiados de plot() a creación de líneas con line.new().
Los plots de indicadores ahora se pueden controlar desde el apartado "plots".
Ahora se puede elegir el rango aceptable y negable de profit, winrate y profit factor desde el apartado "plots" para mostrarse en el dashboard.
Cambios estéticos en las separaciones de secciones dentro del apartado de configuraciones y dentro del propio código.
Se ha cambiado la función que hacía que los indicadores dieran entradas en base a velas heikin ashi, mire el código para más información.
⚙️Arreglos:
El dashboard label ahora se proyecta correctamente en todas las temporalidades incluyendo las temporalidades personalizadas.
Se han eliminado líneas y variables innecesarias para ocupar menos espacio en el código.
Se ha optimizado todo el código en general para evitar el uso de variables, líneas innecesarias y evitar los cálculos innecesarios, liberando espacio para declarar más variables y poder utilizar menos líneas de código.
Moon Phases Strategy [LuxAlgo]Trading moon phases has become quite popular among traders, believing that there exists a relationship between moon phases and market movements. This strategy is based on an estimate of moon phases with the possibility to use different methods to determine long/short positions based on moon phases.
Note that we assume moon phases are perfectly periodic with a cycle of 29.530588853 days (which is not realistically the case), as such there exists a difference between the detected moon phases by the strategy and the ones you would see. This difference becomes less important when using higher timeframes.
Settings
New Moon Reference Date: Date of a new moon to be used as starting point for the cycle calculation. Buy: Determine the condition to be used to open a long position Sell: Determine the condition to be used to open a short position
Description
The strategy can use different buy/sell conditions, these are determined in the Buy/Sell settings drop-down menu.
By default, the strategy goes long on a new moon and short on a full moon. This setup is common since full moons are said to be related to depressed mood. However, it is possible to use inverse conditions.
Users can also go long on higher moons (new moons or full moons occurring at a price that is higher than the previous one when a new/full moon occurred) and short on lower moons, this would return a trend following strategy, using the inverse conditions (buy lower moons/sell higher moons) would return a contrarian strategy.
The above chart displays the strategy using default conditions.
The above chart displays the strategy of going long on a higher moon and selling on a lower moon.
Quick Summary
We provide a quick summary of the strategy using default conditions (buy on a new moon, sell on a full moon) on various tickers using the 4h timeframe (note that using a lower timeframe would return a backtest executing a lower number of trades).
Constant position sizing is used and no frictional costs are considered.
BTCUSD
The moon phases strategy has been regularly tested with BTCUSD, with traders highlighting how moon phases tend to occur during tops/bottoms. We test the strategy from 2019-01-06 00:00.
Net Profit: $68544.86 Closed Trades : 67 % Profitability : 50.75 Max Drawdown : $18541.24 Max
TSLA
The strategy is tested from 2011-01-04 14:30
Net profit: $349.17 Closed Trades : 265 % Profitability : 54.34 Max Drawdown : $262.72
EURUSD
The strategy is tested from 2018-01-16 14:00.
Net profit: $-0.18 Closed Trades : 91 % Profitability : 50.55 Max Drawdown : 0.36
Portfolio Backtester Engine█ OVERVIEW
Portfolio Backtester Engine (PBTE). This tool will allow you to backtest strategies across multiple securities at once. Allowing you to easier understand if your strategy is robust. If you are familiar with the PineCoders backtesting engine , then you will find this indicator pleasant to work with as it is an adaptation based on that work. Much of the functionality has been kept the same, or enhanced, with some minor adjustments I made on the account of creating a more subjectively intuitive tool.
█ HISTORY
The original purpose of the backtesting engine (`BTE`) was to bridge the gap between strategies and studies . Previously, strategies did not contain the ability to send alerts, but were necessary for backtesting. Studies on the other hand were necessary for sending alerts, but could not provide backtesting results . Often, traders would have to manage two separate Pine scripts to take advantage of each feature, this was less than ideal.
The `BTE` published by PineCoders offered a solution to this issue by generating backtesting results under the context of a study(). This allowed traders to backtest their strategy and simultaneously generate alerts for automated trading, thus eliminating the need for a separate strategy() script (though, even converting the engine to a strategy was made simple by the PineCoders!).
Fast forward a couple years and PineScript evolved beyond these issues and alerts were introduced into strategies. The BTE was not quite as necessary anymore, but is still extremely useful as it contains extra features and data not found under the strategy() context. Below is an excerpt of features contained by the BTE:
"""
More than `40` built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
"""
Before I go any further, I want to be clear that the BTE is STILL a good tool and it is STILL very useful. The Portfolio Backtesting Engine I am introducing is only a tangental advancement and not to be confused as a replacement, this tool would not have been possible without the `BTE`.
█ THE PROBLEM
Most strategies built in Pine are limited by one thing. Data. Backtesting should be a rigorous process and researchers should examine the performance of their strategy across all market regimes; that includes, bullish and bearish markets, ranging markets, low volatility and high volatility. Depending on your TV subscription The Pine Engine is limited to 5k-20k historical bars available for backtesting, which can often leave the strategy results wanting. As a general rule of thumb, strategies should be tested across a quantity of historical bars which will allow for at least 100 trades. In many cases, the lack of historical bars available for backtesting and frequency of the strategy signals produces less than 100 trades, rendering your strategy results inconclusive.
█ THE SOLUTION
In order to be confident that we have a robust strategy we must test it across all market regimes and we must have over 100 trades. To do this effectively, researchers can use the Portfolio Backtesting Engine (PBTE).
By testing a strategy across a carefully selected portfolio of securities, researchers can now gather 5k-20k historical bars per security! Currently, the PTBE allows up to 5 securities, which amounts to 25k-100k historical bars.
█ HOW TO USE
1 — Add the indicator to your chart.
• Confirm inputs. These will be the most important initial values which you can change later by clicking the gear icon ⚙ and opening up the settings of the indicator.
2 — Select a portfolio.
• You will want to spend some time carefully selecting a portfolio of securities.
• Each security should be uncorrelated.
• The entire portfolio should contain a mix of different market regimes.
You should understand that strategies generally take advantage of one particular type of market regime. (trending, ranging, low/high volatility)
For example, the default RSI strategy is typically advantageous during ranging markets, whereas a typical moving average crossover strategy is advantageous in trending markets.
If you were to use the standard RSI strategy during a trending market, you might be selling when you should be buying.
Similarily, if you use an SMA crossover during a ranging market, you will find that the MA's may produce many false signals.
Even if you build a strategy that is designed to be used only in a trending market, it is still best to select a portfolio of all market regimes
as you will be able to test how your strategy will perform when the market does something unexpected.
3 — Test a built-in strategy or add your own.
• Navigate to gear icon ⚙ (settings) of strategy.
• Choose your options.
• Select a Main Entry Strat and Alternate Entry Strat .
• If you want to add your own strategy, you will need to modify the source code and follow the built-in example.
• You will only need to generate (buy 1 / sell -1/ neutral 0) signals.
• Select a Filter , by default these are all off.
• Select an Entry Stop - This will be your stop loss placed at the trade entry.
• Select Pyamiding - This will allow you to stack positions. By default this is off.
• Select Hard Exits - You can also think of these as Take Profits.
• Let the strategy run and take note of the display tables results.
• Portfolio - Shows each security.
• The strategy runs on each asset in your portfolio.
• The initial capital is equally distributed across each security.
So if you have 5 securities and a starting capital of 100,000$ then each security will run the strategy starting with 20,000$
The total row will aggregate the results on a bar by bar basis showing the total results of your initial capital.
• Net Profit (NP) - Shows profitability.
• Number of Trades (#T) - Shows # of trades taken during backtesting period.
• Typically will want to see this number greater than 100 on the "Total" row.
• Average Trade Length (ATL) - Shows average # of days in a trade.
• Maximum Drawdown (MD ) - Max peak-to-valley equity drawdown during backtesting period.
• This number defines the minimum amount of capital required to trade the system.
• Typically, this shouldn’t be lower than 34% and we will want to allow for at least 50% beyond this number.
• Maximum Loss (ML) - Shows largest loss experienced on a per-trade basis.
• Normally, don’t want to exceed more than 1-2 % of equity.
• Maximum Drawdown Duration (MDD) - The longest duration of a drawdown in equity prior to a new equity peak.
• This number is important to help us psychologically understand how long we can expect to wait for a new peak in account equity.
• Maximum Consecutive Losses (MCL) - The max consecutive losses endured throughout the backtesting period.
• Another important metric for trader psychology, this will help you understand how many losses you should be prepared to handle.
• Profit to Maximum Drawdown (P:MD) - A ratio for the average profit to the maximum drawdown.
• The higher the ratio is, the better. Large profits and small losses contribute to a good PMD.
• This metric allows us to examine the profit with respect to risk.
• Profit Loss Ratio (P:L) - Average profit over the average loss.
• Typically this number should be higher in trend following systems.
• Mean reversion systems show lower values, but compensate with a better win %.
• Percent Winners (% W) - The percentage of winning trades.
• Trend systems will usually have lower win percentages, since statistically the market is only trending roughly 30% of the time.
• Mean reversion systems typically should have a high % W.
• Time Percentage (Time %) - The amount of time that the system has an open position.
• The more time you are in the market, the more you are exposed to market risk, not to mention you could be using that money for something else right?
• Return on Investment (ROI) - Your Net Profit over your initial investment, represented as a percentage.
• You want this number to be positive and high.
• Open Profit (OP) - If the strategy has any open positions, the floating value will be represented here.
• Trading Days (TD) - An important metric showing how many days the strategy was active.
• This is good to know and will be valuable in understanding how long you will need to run this strategy in order to achieve results.
█ FEATURES
These are additional features that extend the original `BTE` features.
- Portfolio backtesting.
- Color coded performance results.
- Circuit Breakers that will stop trading.
- Position reversals on exit. (Simulating the function of always in the market. Similar to strategy.entry functionality)
- Whipsaw Filter
- Moving Average Filter
- Minimum Change Filter
- % Gain Equity Exit
- Popular strategies, (MACD, MA cross, supertrend)
Below are features that were excluded from the original `BTE`
- 2 stage in-trade stops with kick-in rules (This was a subjective decision to remove. I found it to be complex and thwarted my use of the `BTE` for some time.)
- Simple conversion from Study to Strategy modes. (Not possible with multiple securities)
- Coupling with your own external indicator (Not really practical to use with multiple securities, but could be used if signals were generated based on some indicator which was not based on the current chart)
- Use of the Data Window to show detailed bar by bar trade information and global statistics.
- Post Exit Analysis.
- Plotting of reminders and generation of alerts on in-trade events.
- Alerts (These may be added in the future by request when I find the time.)
█ THANKS
The whole PineCoders team for all their shared knowledge and original publication of the BTE and Richard Weismann for his ideas on building robust strategies.
═════════════════════════════════════════════════════════════════════════
STRATEGY TESTER ENGINE - ON CHART DISPLAY - PLUG & PLAYSo i had this idea while ago when @alexgrover published a script and dropped a nugget in between which replicates the result of strategy tester on chart as an indicator.
So it seemed fair to use one of his strategy to display the results.
This strategy tester can now be used in replay mode like an indicator and you can see what happen at a particular section of the chart which was is not possible in default strategy tester results of TV.
Please read how each result is calculated so you will know what you are using.
This engine shows most common results of strategy tester in a single screen, which are as follows:
1. Starting Capital
2. Current Profit Percentage
3. Max Profit Percentage
4. Gross Profit
5. Gross Loss
6. Total Closed Trades
7. Total Trades Won
8. Total Trades Lost
9. Percentage Profitable
10. Profit Factor
11. Current Drawdown
12. Max Drawdown
13. Liquidation
So elaborating on what is what:
1. Starting Capital - This stays 0, which signifies your starting balance as 0%. It is set to 0 so we can compare all other results without any change in variables. If set to 100, then all the results will be increased by 100. Some users might find it useful to set it to 100, then they can change code on line 41 from to and it should show starting balance as 100%.
2. Current Profit Percentage - This shows your current profit adjusted to current price of the candle, not like TV which shows after candle is close. There is a comment on the line 38 which can be removed and your can see unrealized profit as well in this section. Please note that this will affect Draw-down calculations later in this section.
3. Max Profit Percentage - This will show you your max profit achieved during your strategy run, which was not possible yet to see via strategy tester. So, now you can see how much profit was achieved by your strategy during the run and you can compare it with chart to see what happens during bull-run or bear-run, so you can further optimize your strategy to best suit your desired results.
4. Gross Profit - This is total percentage of profit your strategy achieved during entire run as if you never had any losses.
5. Gross Loss - This is total percentage of loss your strategy achieved during entire run as if you never had any profits.
6. Total Closed Trades - This is total number of trades that your strategy has executed so far.
7. Total Trades Won - This is the total number of trades that your strategy has executed that resulted in positive increase in equity.
8. Totals Trades Lost - This is the total number of trades that your strategy has executed that resulted in decrease in equity.
9. Percentage Profitable - This is the ratio between your current total winning trades divided by total closed trades, and finally multiplied by 100 to get percentage results.
10. Profit Factor - This is the ratio between Gross Profit and Gross Loss, so if profit factor is 2, then it indicates that you are set to gain 2 times per your risk per trade on average when total trades are executed.
11. Current Drawdown - This is important section and i want you to read this carefully. Here draw-down is calculated very differently than what TV shows. TV has access to candle data and calculates draw-down accordingly as per number of trades closed, but here DD is calculated as difference between max profit achieved and current profit. This way you can see how much percentage you are down from max peak of equity at current point in time. You can do back-test of the data and see when peak was achieved and how much your strategy did a draw-down candle by candle.
12. Max Drawdown - This is also calculated differently same as above, current draw-down. Here you can see how much max DD your strategy did from a peak profit of equity. This is not set as max profit percentage is set because you will see single number on display, while idea is to keep it custom. I will explain.
So lets say, your max DD on TV is 30%. Here this is of no use to see Max DD , as some people might want to see what was there max DD 1000 candles back or 10 candle back. So this will show you your max DD from the data you select. TV shows 25000 candle data in a chart if you go back, you can set the counter to 24999 and it will show you max DD as shown on TV, but if you want custom section to show max DD , it is now possible which was not possible before.
Also, now let's say you put DD as 24999 and open a chart of an asset that was listed 1 week ago, now on 1H chart max DD will never show up until you reach 24999 candle in data history, but with this you can now enter a manual number and see the data.
13. Liquidation - This is an interesting feature, so now when your equity balance is less than 0 and your draw-down goes to -100, it will show you where and at what point in time you got liquidated by adding a red background color in the entire section. This is the most fun part of this script, while you can only see max DD on TV.
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How to Use -
1 word, plug and play. Yes. Actual codes start from line 33.
select overlay=false or remove it from the title in your strategy on first line,
Just copy the codes from line 33 to 103,
then go to end section of your strategy and paste the entire code from line 33 to line 103,
see if you have any duplicate variable, edit it,
Add to chart.
What you see above is very contracted view. Here is how it looks when zoomed in.
imgur.com
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Feel free to edit and share and use. If you use it in your scripts, drop me tag. Cheers.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
S4_IBS_Mean_Rev_3candleExitOverview:
This is a rules-based, mean reversion strategy designed to trade pullbacks using the Internal Bar Strength (IBS) indicator. The system looks for oversold conditions based on IBS, then enters long trades , holding for a maximum of 3 bars or until the trade becomes profitable.
The strategy includes:
✅ Strict entry rules based on IBS
✅ Hardcoded exit conditions for risk management
✅ A clean visual table summarizing key performance metrics
How It Works:
1. Internal Bar Strength (IBS) Setup:
The IBS is calculated using the previous bar’s price range:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
IBS values closer to 0 indicate price is near the bottom of the previous range, suggesting oversold conditions.
2. Entry Conditions:
IBS must be ≤ 0.25, signaling an oversold setup.
Trade entries are only allowed within a user-defined backtest window (default: 2024).
Only one trade at a time is permitted (long-only strategy).
3. Exit Conditions:
If the price closes higher than the entry price, the trade exits with a profit.
If the trade has been open for 3 bars without showing profit, the trade is forcefully exited.
All trades are closed automatically at the end of the backtest window if still open.
Additional Features:
📊 A real-time performance metrics table is displayed on the chart, showing:
- Total trades
- % of profitable trades
- Total P&L
- Profit Factor
- Max Drawdown
- Best/Worst trade performance
📈 Visual markers indicate trade entries (green triangle) and exits (red triangle) for easy chart interpretation.
Who Is This For?
This strategy is designed for:
✅ Traders exploring systematic mean reversion approaches
✅ Those who prefer strict, rules-based setups with no subjective decision-making
✅ Traders who want built-in performance tracking directly on the chart
Note: This strategy is provided for educational and research purposes. It is a backtested model and past performance does not guarantee future results. Users should paper trade and validate performance before considering real capital.
Canuck Trading Trader StrategyCanuck Trading Trader Strategy
Overview
The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns.
Key Features
Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals.
Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward.
High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission.
Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance.
Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding).
Performance Highlights
Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital:
Net Profit: $2,279,888.08 (227.99%)
Win Rate: 52.94% (3,039 winning trades out of 5,741)
Profit Factor: 3.495
Max Drawdown: 2.20%
Average Winning Trade: $1,050.91 (0.55%)
Average Losing Trade: $338.20 (0.18%)
Sharpe Ratio: 2.468
Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing.
Usage Instructions
Setup:
Apply the strategy to a NASDAQ:TSLA 15-minute chart.
Ensure your TradingView account supports bar magnification for accurate results.
Configuration:
Lookback Candles: Default is 2 (recommended).
Min Trend Strength: Set to 0.2% for optimal trade frequency.
Stop Loss: Default 3.0% to cap losses.
Take Profit: Default 2.0% to secure gains.
Order Size: 10% of equity per trade.
Pyramiding: Allows up to 2 orders.
Commission: Set to 0.1.
Slippage: Set to 1 tick.
Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings.
Backtesting:
Run backtests over March 1, 2024, to June 20, 2025, to verify performance.
Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance.
Live Trading:
Use with a compatible broker or TradingView alerts for automated execution.
Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades).
Validate in a demo account before deploying with real capital.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
Stochastic RSI with MTF TableShort Description of the Script
The provided Pine Script indicator, titled "Stochastic RSI with MTF Table," calculates and displays the Stochastic RSI for the current timeframe and multiple other timeframes (5m, 15m, 30m, 60m, 240m, and daily). The Stochastic RSI is a momentum indicator that blends the Relative Strength Index (RSI) and Stochastic Oscillator to identify overbought and oversold conditions, as well as potential trend reversals via K and D line crossovers.
Key features of the script include:
Inputs: Customizable parameters such as K smoothing (default 3), D smoothing (default 3), RSI length (default 14), Stochastic length (default 14), source price (default close), and overbought/oversold levels (default 80/20).
MTF Table: A table displays the Stochastic RSI status for each timeframe:
"OB" (overbought) if K > 80, "OS" (oversold) if K < 20, or "N" (neutral) otherwise.
Crossovers: "K↑D" for bullish (K crosses above D) and "K↓D" for bearish (K crosses below D).
Visualization: Plots the K and D lines for the current timeframe, with horizontal lines at 80 (overbought), 50 (middle), and 20 (oversold), plus a background fill for clarity.
Table Position: Configurable to appear in one of four chart corners (default: top-right).
This indicator helps traders assess momentum across multiple timeframes simultaneously, aiding in the identification of trend strength and potential entry/exit points.
Trading Strategy with 50EMA and 200EMA for Highest Winning Rate
To create a strategy with the best probability of a high winning rate using the Stochastic RSI MTF indicator alongside the 50-period Exponential Moving Average (50EMA) and 200-period Exponential Moving Average (200EMA), we can combine trend identification with momentum-based entry timing. The 50EMA and 200EMA are widely used to determine medium- and long-term trends, while the Stochastic RSI MTF table provides multi-timeframe momentum signals. Here’s the strategy:
1. Determine the Overall Trend
Bullish Trend: The 50EMA is above the 200EMA on the current timeframe (e.g., daily or 60m chart). This suggests an uptrend, often associated with a "Golden Cross."
Bearish Trend: The 50EMA is below the 200EMA on the current timeframe. This indicates a downtrend, often linked to a "Death Cross."
Implementation: Plot the 50EMA and 200EMA on your chart and visually confirm their relative positions.
2. Identify Entry Signals Using the Stochastic RSI MTF Table
In a Bullish Trend (50EMA > 200EMA):
Look for timeframes in the MTF table showing:
Oversold (OS): K < 20, indicating a potential pullback in the uptrend where price may rebound.
Bullish Crossover (K↑D): K crosses above D, signaling rising momentum and a potential entry point.
Example: If the 60m and 240m timeframes show "OS" or "K↑D," this could be a buy signal.
In a Bearish Trend (50EMA < 200EMA):
Look for timeframes in the MTF table showing:
Overbought (OB): K > 80, suggesting a rally in the downtrend where price may reverse downward.
Bearish Crossover (K↓D): K crosses below D, indicating declining momentum and a potential short entry.
Example: If the 30m and daily timeframes show "OB" or "K↓D," this could be a sell/short signal.
Current Timeframe Check: Use the plotted K and D lines on your trading timeframe for precise entry timing (e.g., confirm a K↑D crossover on a 60m chart for a long trade).
3. Confirm Signals Across Multiple Timeframes
Strengthen the Signal: A higher winning rate is more likely when multiple timeframes align with the trend and signal. For instance:
Bullish trend + "OS" or "K↑D" on 60m, 240m, and daily = strong buy signal.
Bearish trend + "OB" or "K↓D" on 15m, 60m, and 240m = strong sell signal.
Prioritize Higher Timeframes: Signals from the 240m or daily timeframe carry more weight due to their indication of broader trends, increasing reliability.
4. Set Stop-Loss and Take-Profit Levels
Long Trades (Bullish):
Stop-Loss: Place below the most recent swing low or below the 50EMA, whichever is closer, to protect against trend reversals.
Take-Profit: Target a key resistance level or use a risk-reward ratio (e.g., 2:1 or 3:1) based on the stop-loss distance.
Short Trades (Bearish):
Stop-Loss: Place above the most recent swing high or above the 50EMA, whichever is closer.
Take-Profit: Target a key support level or apply a similar risk-reward ratio.
Trailing Stop Option: As the trend progresses, trail the stop below the 50EMA (for longs) or above it (for shorts) to lock in profits.
5. Risk Management
Position Sizing: Risk no more than 1-2% of your trading capital per trade to minimize losses from false signals.
Volatility Consideration: Adjust stop-loss distances and position sizes based on the asset’s volatility (e.g., wider stops for volatile stocks or crypto).
Avoid Overtrading: Wait for clear alignment between the EMA trend and MTF signals to avoid low-probability setups.
Example Scenario
Chart: 60-minute timeframe.
Trend: 50EMA > 200EMA (bullish).
MTF Table: 60m shows "OS," 240m shows "K↑D," and daily is "N."
Action: Enter a long position when the 60m K line crosses above D, confirming the table signal.
Stop-Loss: Below the recent 60m swing low (e.g., 2% below entry).
Take-Profit: At the next resistance level or a 3:1 reward-to-risk ratio.
Outcome: High probability of success due to trend alignment and multi-timeframe confirmation.
Why This Strategy Works
Trend Following: Trading in the direction of the 50EMA/200EMA trend reduces the risk of fighting the market’s momentum.
Momentum Timing: The Stochastic RSI MTF table pinpoints pullbacks or reversals within the trend, improving entry timing.
Multi-Timeframe Confirmation: Alignment across timeframes filters out noise, increasing the win rate.
Risk Control: Defined stop-loss and position sizing protect against inevitable losses.
Caveats
No strategy guarantees a 100% win rate; false signals can occur, especially in choppy markets.
Test this strategy on historical data or a demo account to verify its effectiveness for your asset and timeframe.
This approach leverages the strengths of both trend-following (EMA) and momentum (Stochastic RSI) tools, aiming for a high-probability, disciplined trading system.
Step-Based Trailing Stop-Loss IndicatorThis indicator is built for momentum traders who want to maximize winning trades and minimize losses through a smart, step-based trailing stop-loss system. Instead of using a fixed Take Profit, this tool dynamically protects profits once the trade reaches a favorable RR (Risk-to-Reward) level.
How It Works:
Manual Entry Input
You enter your Entry Price and select Buy/Sell in the settings.
This flexibility allows backtesting or live trade tracking.
Initial Setup
Default SL: 50 ticks(Tested on us30,but works on any pair you just need to adjust SL)
TP for reference: 4R — can be used for benchmarking, but we don't limit profits with a hard TP.
Trailing Logic
Once price reaches 3R in profit:
The SL begins trailing.
It starts at 2R, keeping a 1R cushion behind the max profit.
For every 0.5R gain, SL also moves up by 0.5R:
Example: At 3.5R → SL is at 2.5R
At 5.0R → SL is at 4.0R
This trailing continues until the SL is hit or the trend exhausts.
Chart Features
🟧 Entry Line
🔴 Initial SL
🟢 Reference TP (4R, optional)
🟣 Dynamic Trailing SL
🏷️ Labels for Entry & SL levels
EMA 34 Crossover with Break Even Stop LossEMA 34 Crossover with Break Even Stop Loss Strategy
This trading strategy is based on the 34-period Exponential Moving Average (EMA) and aims to enter long positions when the price crosses above the EMA 34. The strategy is designed to manage risk effectively with a dynamic stop loss and take-profit mechanism.
Key Features:
EMA 34 Crossover:
The strategy generates a long entry signal when the closing price of the current bar crosses above the 34-period EMA, with the condition that the previous closing price was below the EMA. This crossover indicates a potential upward trend.
Risk Management:
Upon entering a trade, the strategy sets a stop loss at the low of the previous bar. This helps in controlling the downside risk.
A take profit level is set at a 10:1 risk-to-reward ratio, meaning the potential profit is ten times the amount risked on the trade.
Break-even Stop Loss:
As the price moves in favor of the trade and reaches a 3:1 risk-to-reward ratio, the strategy moves the stop loss to the entry price (break-even). This ensures that no loss will be incurred if the market reverses, effectively protecting profits.
Exit Conditions:
The strategy exits the trade when either the stop loss is hit (if the price drops below the stop loss level) or the take profit target is reached (if the price rises to the take profit level).
If the price reaches the break-even level (entry price), the stop loss is adjusted to lock in profits and prevent any loss.
Visualization:
The stop loss and take profit levels are plotted on the chart for easy visualization, helping traders track the status of their trade.
Trade Management Summary:
Long Entry: When price crosses above the 34-period EMA.
Stop Loss: Set to the low of the previous candle.
Take Profit: Set to a 10:1 risk-to-reward ratio.
Break-even: Stop loss is moved to entry price when a 3:1 risk-to-reward ratio is reached.
Exit: The trade is closed either when the stop loss or take profit levels are hit.
This strategy is designed to minimize losses by employing a dynamic stop loss and to maximize gains by setting a favorable risk-to-reward ratio, making it suitable for traders who prefer a structured, automated approach to risk management and trend-following.
Momentum Volume Divergence (MVD) EnhancedMomentum Volume Divergence (MVD) Enhanced is a powerful indicator that detects price-momentum divergences and momentum suppression for reversal trading. Optimized for XRP on 1D charts, it features dynamic lookbacks, ATR-adjusted thresholds, and SMA confirmation. Signals include strong divergences (triangles) and suppression warnings (crosses). Includes a detailed user guide—try it out and share your feedback!
Setup: Add to XRP 1D chart with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA crossovers. See full guide for details!
Disclaimer: This indicator is for educational purposes only, not financial advice. Trading involves risk—use at your discretion.
Momentum Volume Divergence (MVD) Enhanced Indicator User Guide
Version: Pine Script v6
Designed for: TradingView
Recommended Use: XRP on 1-day (1D) chart
Date: March 18, 2025
Author: Herschel with assistance from Grok 3 (xAI)
Overview
The Momentum Volume Divergence (MVD) Enhanced indicator is a powerful tool for identifying price-momentum divergences and momentum suppression patterns on XRP’s 1-day (1D) chart. Plotted below the price chart, it provides clear visual signals to help traders spot potential reversals and trend shifts.
Purpose
Detect divergences between price and momentum for buy/sell opportunities.
Highlight momentum suppression as warnings of fading trends.
Offer actionable trading signals with intuitive markers.
Indicator Components
Main Plot
Volume-Weighted Momentum (vw_mom): Blue line showing momentum adjusted by volume.
Above 0 = bullish momentum.
Below 0 = bearish momentum.
Zero Line: Gray dashed line at 0, separating bullish/bearish zones.
Key Signals
Strong Bearish Divergence:
Marker: Red triangle at the top.
Meaning: Price makes a higher high, but momentum weakens, confirmed by a drop below the 5-day SMA.
Action: Potential sell/short signal.
Strong Bullish Divergence:
Marker: Green triangle at the bottom.
Meaning: Price makes a lower low, but momentum strengthens, confirmed by a rise above the 5-day SMA.
Action: Potential buy/long signal.
Bearish Suppression:
Marker: Orange cross at the top + red background.
Meaning: Strong bullish momentum with low volume in a volume downtrend, suggesting fading strength.
Action: Warning to avoid longs or exit early.
Bullish Suppression:
Marker: Yellow cross at the bottom + green background.
Meaning: Strong bearish momentum with low volume in a volume uptrend, suggesting fading weakness.
Action: Warning to avoid shorts or exit early.
Debug Plots (Optional)
Volume Ratio: Gray line (volume vs. its MA) vs. yellow line (threshold).
Momentum Threshold: Purple lines (positive/negative momentum cutoffs).
Smoothed Momentum: Orange line (raw momentum).
Confirmation SMA: Purple line (price trend confirmation).
Labels
Text labels (e.g., "Bear Div," "Bull Supp") mark detected patterns.
How to Use the Indicator
Step-by-Step Trading Process
1. Monitor the Chart
Load your XRP 1D chart with the indicator applied.
Observe the blue vw_mom line and signal markers.
2. Spot a Signal
Primary Signals: Look for red triangles (strong_bear) or green triangles (strong_bull).
Warnings: Note orange crosses (suppression_bear) or yellow crosses (suppression_bull).
3. Confirm the Signal
For Strong Bullish Divergence (Buy):
Green triangle appears.
Price closes above the 5-day SMA (purple line) and a recent swing high.
Optional: Volume ratio (gray line) exceeds the threshold (yellow line).
For Strong Bearish Divergence (Sell):
Red triangle appears.
Price closes below the 5-day SMA and a recent swing low.
Optional: Volume ratio (gray line) falls below the threshold (yellow line).
4. Enter the Trade
Long:
Buy at the close of the signal bar.
Stop loss: Below the recent swing low or 2 × ATR(14) below entry.
Short:
Sell/short at the close of the signal bar.
Stop loss: Above the recent swing high or 2 × ATR(14) above entry.
5. Manage the Trade
Take Profit:
Aim for a 2:1 or 3:1 risk-reward ratio (e.g., risk $0.05, target $0.10-$0.15).
Or exit when an opposite suppression signal appears (e.g., orange cross for longs).
Trailing Stop:
Move stop to breakeven after a 1:1 RR move.
Trail using the 5-day SMA or 2 × ATR(14).
Early Exit:
Exit if a suppression signal appears against your position (e.g., suppression_bull while short).
6. Filter Out Noise
Avoid trades if a suppression signal precedes a divergence within 2-3 days.
Optional: Add a 50-day SMA on the price chart:
Longs only if price > 50-SMA.
Shorts only if price < 50-SMA.
Example Trades (XRP 1D)
Bullish Trade
Signal: Green triangle (strong_bull) at $0.55.
Confirmation: Price closes above 5-SMA and $0.57 high.
Entry: Buy at $0.58.
Stop Loss: $0.53 (recent low).
Take Profit: $0.63 (2:1 RR) or exit on suppression_bear.
Outcome: Price hits $0.64, exit at $0.63 for profit.
Bearish Trade
Signal: Red triangle (strong_bear) at $0.70.
Confirmation: Price closes below 5-SMA and $0.68 low.
Entry: Short at $0.67.
Stop Loss: $0.71 (recent high).
Take Profit: $0.62 (2:1 RR) or exit on suppression_bull.
Outcome: Price drops to $0.61, exit at $0.62 for profit.
Tips for Success
Combine with Price Levels:
Use support/resistance zones (e.g., weekly pivots) to confirm entries.
Monitor Volume:
Rising volume (gray line above yellow) strengthens signals.
Adjust Sensitivity:
Too many signals? Increase div_strength_threshold to 0.7.
Too few signals? Decrease to 0.3.
Backtest:
Review 20-30 past signals on XRP 1D to assess performance.
Avoid Choppy Markets:
Skip signals during low volatility (tight price ranges).
Troubleshooting
No Signals:
Lower div_strength_threshold to 0.3 or mom_threshold_base to 0.2.
Check if XRP’s volatility is unusually low.
False Signals:
Increase sma_confirm_length to 7 or add a 50-SMA filter.
Indicator Not Loading:
Ensure the script compiles without errors.
Customization (Optional)
Change Colors: Edit color.* values (e.g., color.red to color.purple).
Add Alerts: Use TradingView’s alert menu for "Strong Bearish Divergence Confirmed," etc.
Test Other Assets: Experiment with BTC or ETH, adjusting inputs as needed.
Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion.
Setup: Use on XRP 1D with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA cross. Stop: 2x ATR(14). Profit: 2:1 RR or suppression exit. Full guide available separately!
AO Smart Scalper – 5M Dynamic SL Edition📈 AO Signals with Fixed and Dynamic SL – Optimized for 5-Minute Charts 📉
This indicator is built for 5-minute timeframe trading, combining powerful momentum signals from the Awesome Oscillator (AO) with both Fixed and Dynamic Stop Loss (SL) levels to enhance trade management and risk control.
✅ Buy/Sell Signals:
The indicator generates clear BUY and SELL signals based on the AO crossing above or below the zero line, helping traders capture momentum shifts early.
🛑 Fixed Stop Loss:
Each trade signal comes with a Fixed SL, calculated based on the high (for shorts) or low (for longs) of the previous candle, with a customizable percentage offset. This SL is plotted with a red line, providing a clear initial risk level.
⚡ Dynamic Stop Loss: Continuous Presence, Strategic Use:
A secondary Dynamic SL line is plotted, which is continuously present on the chart. This dynamic level responds to market conditions and can serve as a trailing stop or key decision point.
💡 Recommended Use: It is recommended to actively start using the Dynamic SL once the trade has moved into profit. This allows protecting obtained profits and minimizing the risk of losses in case of a market reversal.
🛡️ Enhanced Dynamic Stop-Loss Strategy:
🔒 Initial Protection: Utilize the Fixed SL as the initial stop-loss, placed below relevant lows (for longs) or above relevant highs (for shorts), or as provided by the fixed SL indicator.
🛤️ Dynamic Tracking:
🟢 Long Trades: Once in profit, the Dynamic SL will dynamically adjust, moving upwards as higher lows are formed, effectively trailing the price and securing profits.
🔴 Short Trades: Conversely, in short trades, once in profit, the Dynamic SL will move downwards as lower highs are formed, protecting gains.
🔄 Alternatively the dynamic stop loss will follow the dynamic SL line provided by the indicator.
🚪 Exiting Trades: When the price crosses below the Dynamic SL line in a LONG trade, or above it in a SHORT trade, the recommended action is to exit the trade.
↩️ Re-entry Consideration: You may consider re-entering only if the price clearly returns above the Dynamic SL (for longs) or below it (for shorts).
⚠️ IMPORTANT - 5-Minute Strategy Guidance ⏱️
This tool is specifically optimized for the 5-minute timeframe. This approach helps filter out weak setups and maintain discipline in volatile market conditions.
✨ Additional Features:
👁️ Visual and editable SL levels
📊 200-period SMA for trend context
💻 Simple and effective interface for intraday trading setups
🎯 Ideal for traders seeking a clean, rule-based system that combines momentum entry signals with layered stop loss protection.
🔑 Key Changes:
It was emphasized that the Dynamic SL is always present, but its active use is recommended once the trade is in profit.
It was clarified the use of the Fixed SL, giving the option to use the one provided by the indicator, or to place it according to the price action.
Mile Runner - Swing Trade LONGMile Runner - Swing Trade LONG Indicator - By @jerolourenco
Overview
The Mile Runner - Swing Trade LONG indicator is designed for swing traders who focus on LONG positions in stocks, BDRs (Brazilian Depositary Receipts), and ETFs. It provides clear entry signals, stop loss, and take profit levels, helping traders identify optimal buying opportunities with a robust set of technical filters. The indicator is optimized for daily candlestick charts and combines multiple technical analysis tools to ensure high-probability trades.
Key Features
Entry Signals: Visualized as green triangles below the price bars, indicating a potential LONG entry.
Stop Loss and Take Profit Levels: Automatically plotted on the chart for easy reference.
Stop Loss: Based on the most recent pivot low (support level).
Take Profit: Calculated using a Fibonacci-based projection from the entry price to the stop loss.
Trend and Momentum Filters: Ensures trades align with the prevailing trend and have sufficient momentum.
Volume and Volatility Confirmation: Verifies market interest and price movement potential.
How It Works
The indicator uses a combination of technical tools to filter and confirm trade setups:
Exponential Moving Averages (EMAs):
A short EMA (default: 9 periods) and a long EMA (default: 21 periods) identify the trend.
A bullish crossover (EMA9 crosses above EMA21) signals a potential upward trend.
Money Flow Index (MFI):
Confirms buying pressure when MFI > 50.
Average True Range (ATR):
Ensures sufficient volatility by checking if ATR exceeds its 20-period moving average.
Volume:
Confirms market interest when volume exceeds its 20-period moving average.
Pivot Lows:
Identifies recent support levels (pivot lows) to set the stop loss.
Ensures the pivot low is recent (within the last 10 bars by default).
Additional Trend Filter:
Confirms the long EMA is rising, reinforcing the bullish trend.
Inputs and Customization
The indicator is highly customizable, allowing traders to tailor it to their strategies:
EMA Periods: Adjust the short and long EMA lengths.
ATR and MFI Periods: Modify lookback periods for volatility and momentum.
Pivot Lookback: Control the sensitivity of pivot low detection.
Fibonacci Level: Adjust the Fibonacci retracement level for take profit.
Take Profit Multiplier: Fine-tune the aggressiveness of the take profit target.
Max Pivot Age: Set the maximum bars since the last pivot low for relevance.
Usage Instructions
Apply the Indicator:
Add the "Mile Runner - Swing Trade LONG" indicator to your TradingView chart.
Best used on daily charts for swing trading.
Look for Entry Signals:
A green triangle below the price bar signals a potential LONG entry.
Set Stop Loss and Take Profit:
Stop Loss: Red dashed line indicating the stop loss level.
Take Profit: Purple dashed line showing the take profit level.
Monitor the Trade:
The entry price is marked with a green dashed line for reference.
Adjust trade management based on the plotted levels.
Set Alerts:
Use the built-in alert condition to get notified of new LONG entry signals.
Important Notes
For LONG Positions Only : Designed exclusively for swing trading LONG positions.
Timeframe: Optimized for daily charts but can be tested on other timeframes.
Asset Types: Works best with stocks, BDRs, and ETFs.
Risk Management: Always align stop loss and take profit levels with your risk tolerance.
Why Use Mile Runner?
The Mile Runner indicator simplifies swing trading by integrating trend, momentum, volume, and volatility filters into one user-friendly tool. It helps traders:
Identify high-probability entry points.
Establish clear stop loss and take profit levels.
Avoid low-volatility or low-volume markets.
Focus on assets with strong buying pressure and recent support.
By following its signals and levels, traders can make informed decisions and enhance their swing trading performance. Customize the inputs and test it on your favorite assets—happy trading!
Cash And Carry Arbitrage BTC Compare Month 6 by SeoNo1Detailed Explanation of the BTC Cash and Carry Arbitrage Script
Script Title: BTC Cash And Carry Arbitrage Month 6 by SeoNo1
Short Title: BTC C&C ABT Month 6
Version: Pine Script v5
Overlay: True (The indicators are plotted directly on the price chart)
Purpose of the Script
This script is designed to help traders analyze and track arbitrage opportunities between the spot market and futures market for Bitcoin (BTC). Specifically, it calculates the spread and Annual Percentage Yield (APY) from a cash-and-carry arbitrage strategy until a specific expiry date (in this case, June 27, 2025).
The strategy helps identify profitable opportunities when the futures price of BTC is higher than the spot price. Traders can then buy BTC in the spot market and short BTC futures contracts to lock in a risk-free profit.
1. Input Settings
Spot Symbol: The real-time BTC spot price from Binance (BTCUSDT).
Futures Symbol: The BTC futures contract that expires in June 2025 (BTCUSDM2025).
Expiry Date: The expiration date of the futures contract, set to June 27, 2025.
These inputs allow users to adjust the symbols or expiry date according to their trading needs.
2. Price Data Retrieval
Spot Price: Fetches the latest closing price of BTC from the spot market.
Futures Price: Fetches the latest closing price of BTC futures.
Spread: The difference between the futures price and the spot price (futures_price - spot_price).
The spread indicates how much higher (or lower) the futures price is compared to the spot market.
3. Time to Maturity (TTM) and Annual Percentage Yield (APY) Calculation
Current Date: Gets the current timestamp.
Time to Maturity (TTM): The number of days left until the futures contract expires.
APY Calculation:
Formula:
APY = ( Spread / Spot Price ) x ( 365 / TTM Days ) x 100
This represents the annualized return from holding a cash-and-carry arbitrage position if the trader buys BTC at the spot price and sells BTC futures.
4. Display Information Table on the Chart
A table is created on the chart's top-right corner showing the following data:
Metric: Labels such as Spread and APY
Value: Displays the calculated spread and APY
The table automatically updates at the latest bar to display the most recent data.
5. Alert Condition
This sets an alert condition that triggers every time the script runs.
In practice, users can modify this alert to trigger based on specific conditions (e.g., APY exceeds a threshold).
6. Plotting the APY and Spread
APY Plot: Displays the annualized yield as a blue line on the chart.
Spread Plot: Visualizes the futures-spot spread as a red line.
This helps traders quickly identify arbitrage opportunities when the spread or APY reaches desirable levels.
How to Use the Script
Monitor Arbitrage Opportunities:
A positive spread indicates a potential cash-and-carry arbitrage opportunity.
The larger the APY, the more profitable the arbitrage opportunity could be.
Timing Trades:
Execute a buy on the BTC spot market and simultaneously sell BTC futures when the APY is attractive.
Close both positions upon futures contract expiry to realize profits.
Risk Management:
Ensure you have sufficient margin to hold both positions until expiry.
Monitor funding rates and volatility, which could affect returns.
Conclusion
This script is an essential tool for traders looking to exploit price discrepancies between the BTC spot market and futures market through a cash-and-carry arbitrage strategy. It provides real-time data on spreads, annualized returns (APY), and visual alerts, helping traders make informed decisions and maximize their profit potential.
Forex Hammer and Hanging Man StrategyThe strategy is based on two key candlestick chart patterns: Hammer and Hanging Man. These chart patterns are widely used in technical analysis to identify potential reversal points in the market. Their relevance in the Forex market, known for its high liquidity and volatile price movements, is particularly pronounced. Both patterns provide insights into market sentiment and trader psychology, which are critical in currency trading, where short-term volatility plays a significant role.
1. Hammer:
• Typically occurs after a downtrend.
• Signals a potential trend reversal to the upside.
• A Hammer has:
• A small body (close and open are close to each other).
• A long lower shadow, at least twice as long as the body.
• No or a very short upper shadow.
2. Hanging Man:
• Typically occurs after an uptrend.
• Signals a potential reversal to the downside.
• A Hanging Man has:
• A small body, similar to the Hammer.
• A long lower shadow, at least twice as long as the body.
• A small or no upper shadow.
These patterns are a manifestation of market psychology, specifically the tug-of-war between buyers and sellers. The Hammer reflects a situation where sellers tried to push the price down but were overpowered by buyers, while the Hanging Man shows that buyers failed to maintain the upward movement, and sellers could take control.
Relevance of Chart Patterns in Forex
In the Forex market, chart patterns are vital tools because they offer insights into price action and market sentiment. Since Forex trading often involves large volumes of trades, chart patterns like the Hammer and Hanging Man are important for recognizing potential shifts in market momentum. These patterns are a part of technical analysis, which aims to forecast future price movements based on historical data, relying on the psychology of market participants.
Scientific Literature on the Relevance of Candlestick Patterns
1. Behavioral Finance and Candlestick Patterns:
Research on behavioral finance supports the idea that candlestick patterns, such as the Hammer and Hanging Man, are relevant because they reflect shifts in trader psychology and sentiment. According to Lo, Mamaysky, and Wang (2000), patterns like these could be seen as representations of collective investor behavior, influenced by overreaction, optimism, or pessimism, and can often signal reversals in market trends.
2. Statistical Validation of Chart Patterns:
Studies by Brock, Lakonishok, and LeBaron (1992) explored the profitability of technical analysis strategies, including candlestick patterns, and found evidence that certain patterns, such as the Hammer, can have predictive value in financial markets. While their study primarily focused on stock markets, their findings are generally applicable to the Forex market as well.
3. Market Efficiency and Candlestick Patterns:
The efficient market hypothesis (EMH) posits that all available information is reflected in asset prices, but some studies suggest that markets may not always be perfectly efficient, allowing for profitable exploitation of certain chart patterns. For instance, Jegadeesh and Titman (1993) found that momentum strategies, which often rely on price patterns and trends, could generate significant returns, suggesting that patterns like the Hammer or Hanging Man may provide a slight edge, particularly in short-term Forex trading.
Testing the Strategy in Forex Using the Provided Script
The provided script allows traders to test and evaluate the Hammer and Hanging Man patterns in Forex trading by entering positions when these patterns appear and holding the position for a specified number of periods. This strategy can be tested to assess its performance across different currency pairs and timeframes.
1. Testing on Different Timeframes:
• The effectiveness of candlestick patterns can vary across different timeframes, as market dynamics change with the level of detail in each timeframe. Shorter timeframes may provide more frequent signals, but with higher noise, while longer timeframes may produce more reliable signals, but with fewer opportunities. This multi-timeframe analysis could be an area to explore to enhance the strategy’s robustness.
2. Exit Strategies:
• The script incorporates an exit strategy where positions are closed after holding them for a specified number of periods. This is useful for testing how long the reversal patterns typically take to play out and when the optimal exit occurs for maximum profitability. It can also help to adjust the exit logic based on real-time market behavior.
Conclusion
The Hammer and Hanging Man patterns are widely recognized in technical analysis as potential reversal signals, and their application in Forex trading is valuable due to the market’s high volatility and liquidity. This strategy leverages these candlestick patterns to enter and exit trades based on shifts in market sentiment and psychology. Testing and optimization, as offered by the script, can help refine the strategy and improve its effectiveness.
For further refinement, it could be valuable to consider combining candlestick patterns with other technical indicators or using multi-timeframe analysis to confirm patterns and increase the probability of successful trades.
References:
• Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
• Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
This provides a theoretical basis for the use of candlestick patterns in trading, supported by academic literature and research on market psychology and efficiency.
Dynamic Support and Resistance Pivot Strategy The Dynamic Support and Resistance Pivot Strategy is a flexible and adaptive tool designed to identify short-term support and resistance levels using the concept of price pivots.
### Key Elements of the Strategy
1. Pivot points as support and resistance levels
Pivots are significant turning points on the price chart, often marking local highs and lows where the price has reversed direction. A pivot high occurs when the price forms a local peak, while a pivot low occurs when the price forms a local trough. When a new pivot high is formed, it creates a resistance level. Conversely, when a new pivot low is formed, it creates a support level.
The strategy continuously updates these levels as new pivots are detected, ensuring they remain relevant to the current market conditions. By identifying these price levels, the strategy dynamically adjusts to market conditions, allowing it to adapt to both trending and ranging markets, since it has a long target and can perform reversal operations.
2. Entry Criteria
- Buy (Long): A long position is triggered when the price is near the support level and then crosses it from below to above. This suggests that the price has found support and may start moving upwards.
- Sell (Short): A short position is triggered when the price is near the resistance level and then crosses it from above to below. This indicates that the price may be reversing and moving downward.
3. Support/Resistance distance (%)
- This parameter establishes a percentage range around the identified support and resistance level. For example, if the Support Resistance Distance is 0.4% (default), the closing price must be within a range of 0.4% above support or below the resistance to be considered "close" and trigger a trade.
4. Exit criteria
- Take profit = 27 %
- Stop loss = 10 %
- Reversal if a new entry point is identified in the opposite direction
5. No Repainting
- The Dynamic Support and Resistance Pivot Strategy is not subject to repainting.
6. Position Sizing by Equity and risk management
- This strategy has a default configuration to operate with 35% of the equity. The stop loss is set to 10% from the entry price. This way, the strategy is putting at risk about 10% of 35% of equity, that is, around 3.5% of equity for each trade. The percentage of equity and stop loss can be adjusted by the user according to their risk management.
7. Backtest results
- This strategy was subjected to backtest and operations in replay mode on **1000000MOGUSDT.P**, with the inclusion of transaction fees at 0.12% and slipagge of 5 ticks, and the past results have shown consistent profitability. Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
8. Chart Visualization
- Support and resistance levels are displayed as green (support) and red (resistance) lines.
- Pivot prices are displayed as green (pivot low) and red (pivot high) labels.
In this image above, the Support/Resistance distance (%) parameter was set to 0.8.
9. Default Configuration
Chart Timeframe: 1h
Pivot Lengh: 2
Support/Resistance distance (%): 0.4*
Stop Loss: 10 %
Take Profit: 27 %
* This parameter can alternatively be set to 0.8.
10. Alternative Configuration
Chart Timeframe: 20 min
Pivot Lengh: 4
Support/Resistance distance (%): 0.1
Stop Loss: 10 %
Take Profit: 25 %
BYBIT:1000000MOGUSDT.P
BullBear with Volume-Percentile TP - Strategy [presentTrading] Happy New Year, everyone! I hope we have a fantastic year ahead.
It's been a while since I published an open script, but it's time to return.
This strategy introduces an indicator called Bull Bear Power, combined with an advanced take-profit system, which is the main innovative and educational aspect of this script. I hope all of you find some useful insights here. Welcome to engage in meaningful exchanges. This is a versatile tool suitable for both novice and experienced traders.
█ Introduction and How it is Different
Unlike traditional strategies that rely solely on price or volume indicators, this approach combines Bull Bear Power (BBP) with volume percentile analysis to identify optimal entry and exit points. It features a dynamic take-profit mechanism based on ATR (Average True Range) multipliers adjusted by volume and percentile factors, ensuring adaptability to diverse market conditions. This multifaceted strategy not only improves signal accuracy but also optimizes risk management, distinguishing it from conventional trading methods.
BTCUSD 6hr performance
Disable the visualization of Bull Bear Power (BBP) to clearly view the Z-Score.
█ Strategy, How it Works: Detailed Explanation
The BBP Strategy with Volume-Percentile TP utilizes several interconnected components to analyze market data and generate trading signals. Here's an overview with essential equations:
🔶 Core Indicators and Calculations
1. Exponential Moving Average (EMA):
- **Purpose:** Smoothens price data to identify trends.
- **Formula:**
EMA_t = (Close_t * (2 / (lengthInput + 1))) + (EMA_(t-1) * (1 - (2 / (lengthInput + 1))))
- Usage: Baseline for Bull and Bear Power.
2. Bull and Bear Power:
- Bull Power: `BullPower = High_t - EMA_t`
- Bear Power: `BearPower = Low_t - EMA_t`
- BBP:** `BBP = BullPower + BearPower`
- Interpretation: Positive BBP indicates bullish strength, negative indicates bearish.
3. Z-Score Calculation:
- Purpose: Normalizes BBP to assess deviation from the mean.
- Formula:
Z-Score = (BBP_t - bbp_mean) / bbp_std
- Components:
- `bbp_mean` = SMA of BBP over `zLength` periods.
- `bbp_std` = Standard deviation of BBP over `zLength` periods.
- Usage: Identifies overbought or oversold conditions based on thresholds.
🔶 Volume Analysis
1. Volume Moving Average (`vol_sma`):
vol_sma = (Volume_1 + Volume_2 + ... + Volume_vol_period) / vol_period
2. Volume Multiplier (`vol_mult`):
vol_mult = Current Volume / vol_sma
- Thresholds:
- High Volume: `vol_mult > 2.0`
- Medium Volume: `1.5 < vol_mult ≤ 2.0`
- Low Volume: `1.0 < vol_mult ≤ 1.5`
🔶 Percentile Analysis
1. Percentile Calculation (`calcPercentile`):
Percentile = (Number of values ≤ Current Value / perc_period) * 100
2. Thresholds:
- High Percentile: >90%
- Medium Percentile: >80%
- Low Percentile: >70%
🔶 Dynamic Take-Profit Mechanism
1. ATR-Based Targets:
TP1 Price = Entry Price ± (ATR * atrMult1 * TP_Factor)
TP2 Price = Entry Price ± (ATR * atrMult2 * TP_Factor)
TP3 Price = Entry Price ± (ATR * atrMult3 * TP_Factor)
- ATR Calculation:
ATR_t = (True Range_1 + True Range_2 + ... + True Range_baseAtrLength) / baseAtrLength
2. Adjustment Factors:
TP_Factor = (vol_score + price_score) / 2
- **vol_score** and **price_score** are based on current volume and price percentiles.
Local performance
🔶 Entry and Exit Logic
1. Long Entry: If Z-Score crosses above 1.618, then Enter Long.
2. Short Entry: If Z-Score crosses below -1.618, then Enter Short.
3. Exiting Positions:
If Long and Z-Score crosses below 0:
Exit Long
If Short and Z-Score crosses above 0:
Exit Short
4. Take-Profit Execution:
- Set multiple exit orders at dynamically calculated TP levels based on ATR and adjusted by `TP_Factor`.
█ Trade Direction
The strategy determines trade direction using the Z-Score from the BBP indicator:
- Long Positions:
- Condition: Z-Score crosses above 1.618.
- Short Positions:
- Condition: Z-Score crosses below -1.618.
- Exiting Trades:
- Long Exit: Z-Score drops below 0.
- Short Exit: Z-Score rises above 0.
This approach aligns trades with prevailing market trends, increasing the likelihood of successful outcomes.
█ Usage
Implementing the BBP Strategy with Volume-Percentile TP in TradingView involves:
1. Adding the Strategy:
- Copy the Pine Script code.
- Paste it into TradingView's Pine Editor.
- Save and apply the strategy to your chart.
2. Configuring Settings:
- Adjust parameters like EMA length, Z-Score thresholds, ATR multipliers, volume periods, and percentile settings to match your trading preferences and asset behavior.
3. Backtesting:
- Use TradingView’s backtesting tools to evaluate historical performance.
- Analyze metrics such as profit factor, drawdown, and win rate.
4. Optimization:
- Fine-tune parameters based on backtesting results.
- Test across different assets and timeframes to enhance adaptability.
5. Deployment:
- Apply the strategy in a live trading environment.
- Continuously monitor and adjust settings as market conditions change.
█ Default Settings
The BBP Strategy with Volume-Percentile TP includes default parameters designed for balanced performance across various markets. Understanding these settings and their impact is essential for optimizing strategy performance:
Bull Bear Power Settings:
- EMA Length (`lengthInput`): 21
- **Effect:** Balances sensitivity and trend identification; shorter lengths respond quicker but may generate false signals.
- Z-Score Length (`zLength`): 252
- **Effect:** Long period for stable mean and standard deviation, reducing false signals but less responsive to recent changes.
- Z-Score Threshold (`zThreshold`): 1.618
- **Effect:** Higher threshold filters out weaker signals, focusing on significant market moves.
Take Profit Settings:
- Use Take Profit (`useTP`): Enabled (`true`)
- **Effect:** Activates dynamic profit-taking, enhancing profitability and risk management.
- ATR Period (`baseAtrLength`): 20
- **Effect:** Shorter period for sensitive volatility measurement, allowing tighter profit targets.
- ATR Multipliers:
- **Effect:** Define conservative to aggressive profit targets based on volatility.
- Position Sizes:
- **Effect:** Diversifies profit-taking across multiple levels, balancing risk and reward.
Volume Analysis Settings:
- Volume MA Period (`vol_period`): 100
- **Effect:** Longer period for stable volume average, reducing the impact of short-term spikes.
- Volume Multipliers:
- **Effect:** Determines volume conditions affecting take-profit adjustments.
- Volume Factors:
- **Effect:** Adjusts ATR multipliers based on volume strength.
Percentile Analysis Settings:
- Percentile Period (`perc_period`): 100
- **Effect:** Balances historical context with responsiveness to recent data.
- Percentile Thresholds:
- **Effect:** Defines price and volume percentile levels influencing take-profit adjustments.
- Percentile Factors:
- **Effect:** Modulates ATR multipliers based on price percentile strength.
Impact on Performance:
- EMA Length: Shorter EMAs increase sensitivity but may cause more false signals; longer EMAs provide stability but react slower to market changes.
- Z-Score Parameters:*Longer Z-Score periods create more stable signals, while higher thresholds reduce trade frequency but increase signal reliability.
- ATR Multipliers and Position Sizes: Higher multipliers allow for larger profit targets with increased risk, while diversified position sizes help in securing profits at multiple levels.
- Volume and Percentile Settings: These adjustments ensure that take-profit targets adapt to current market conditions, enhancing flexibility and performance across different volatility environments.
- Commission and Slippage: Accurate settings prevent overestimation of profitability and ensure the strategy remains viable after accounting for trading costs.
Conclusion
The BBP Strategy with Volume-Percentile TP offers a robust framework by combining BBP indicators with volume and percentile analyses. Its dynamic take-profit mechanism, tailored through ATR adjustments, ensures that traders can effectively capture profits while managing risks in varying market conditions.
MACD Aggressive Scalp SimpleComment on the Script
Purpose and Structure:
The script is a scalping strategy based on the MACD indicator combined with EMA (50) as a trend filter.
It uses the MACD histogram's crossover/crossunder of zero to trigger entries and exits, allowing the trader to capitalize on short-term momentum shifts.
The use of strategy.close ensures that positions are closed when specified conditions are met, although adjustments were made to align with Pine Script version 6.
Strengths:
Simplicity and Clarity: The logic is straightforward and focuses on essential scalping principles (momentum-based entries and exits).
Visual Indicators: The plotted MACD line, signal line, and histogram columns provide clear visual feedback for the strategy's operation.
Trend Confirmation: Incorporating the EMA(50) as a trend filter helps avoid trades that go against the prevailing trend, reducing the likelihood of false signals.
Dynamic Exit Conditions: The conditional logic for closing positions based on weakening momentum (via MACD histogram change) is a good way to protect profits or minimize losses.
Potential Improvements:
Parameter Inputs:
Make the MACD (12, 26, 9) and EMA(50) values adjustable by the user through input statements for better customization during backtesting.
Example:
pine
Copy code
macdFast = input(12, title="MACD Fast Length")
macdSlow = input(26, title="MACD Slow Length")
macdSignal = input(9, title="MACD Signal Line Length")
emaLength = input(50, title="EMA Length")
Stop Loss and Take Profit:
The strategy currently lacks explicit stop-loss or take-profit levels, which are critical in a scalping strategy to manage risk and lock in profits.
ATR-based or fixed-percentage exits could be added for better control.
Position Size and Risk Management:
While the script uses 50% of equity per trade, additional options (e.g., fixed position sizes or risk-adjusted sizes) would be beneficial for flexibility.
Avoid Overlapping Signals:
Add logic to prevent overlapping signals (e.g., opening a new position immediately after closing one on the same bar).
Backtesting Optimization:
Consider adding labels or markers (label.new or plotshape) to visualize entry and exit points on the chart for better debugging and analysis.
The inclusion of performance metrics like max drawdown, Sharpe ratio, or profit factor would help assess the strategy's robustness during backtesting.
Compatibility with Live Trading:
The strategy could be further enhanced with alert conditions using alertcondition to notify the trader of buy/sell signals in real-time.
XAUUSD Trend Strategy### Description of the XAUUSD Trading Strategy with Pine Script
This strategy is designed to trade gold (**XAUUSD**) using proven technical analysis principles. It combines key indicators such as **Exponential Moving Averages (EMA)**, the **Relative Strength Index (RSI)**, and **Bollinger Bands** to identify trading opportunities in trending market conditions.
---
#### Objective:
To maximize profits by identifying trend-aligned entry points while minimizing risks through well-defined Stop Loss and Take Profit levels.
---
### How It Works
1. **Indicators Used:**
- **Exponential Moving Averages (EMA):** Tracks short-term and long-term trends to confirm market direction.
- **Relative Strength Index (RSI):** Detects overbought or oversold conditions for potential reversals or trend continuation.
- **Bollinger Bands:** Measures volatility to identify breakout or reversion points.
2. **Entry Rules:**
- **Long (Buy):** Triggered when:
- The short-term EMA crosses above the long-term EMA (bullish trend confirmation).
- RSI exits oversold territory (<30), signaling buying momentum.
- The price breaks above the upper Bollinger Band, indicating a strong trend.
- **Short (Sell):** Triggered when:
- The short-term EMA crosses below the long-term EMA (bearish trend confirmation).
- RSI exits overbought territory (>70), signaling selling momentum.
- The price breaks below the lower Bollinger Band, indicating a strong downtrend.
3. **Risk Management:**
- **Stop Loss:** Automatically calculated based on a percentage of equity risk (customizable via inputs).
- **Take Profit:** Defined using a risk-to-reward ratio, ensuring consistent profitability when trades succeed.
4. **Visualization:**
- The chart displays the EMAs, Bollinger Bands, and entry/exit points for clear analysis.
---
### Key Features:
- **Customizable Parameters:** You can adjust EMAs, RSI thresholds, Bollinger Band settings, and risk levels to suit your trading style.
- **Alerts:** Automatic alerts for potential trade setups.
- **Backtesting-Ready:** Easily test historical performance on TradingView.
---
This strategy is ideal for gold traders looking for a systematic, rule-based approach to trading trends with minimal emotional interference.
Multi Fibonacci Supertrend with Signals【FIbonacciFlux】Multi Fibonacci Supertrend with Signals (MFSS)
Overview
The Multi Fibonacci Supertrend with Signals (MFSS) is an advanced technical analysis tool that combines multiple Supertrend indicators using Fibonacci ratios to identify trend directions and potential trading opportunities.
Key Features
1. Fibonacci-Based Supertrend Levels
* Factor 1 (Weak) : 0.618 - The golden ratio
* Factor 2 (Medium) : 1.618 - The Fibonacci ratio
* Factor 3 (Strong) : 2.618 - The extension ratio
2. Visual Components
* Multi-layered Trend Lines
* Different line weights for easy identification
* Progressive transparency from Factor 1 to Factor 3
* Color-coded trend directions (Green for bullish, Red for bearish)
* Dynamic Fill Areas
* Gradient fills between price and trend lines
* Visual representation of trend strength
* Automatic color adjustment based on trend direction
* Signal Indicators
* Clear BUY/SELL labels on chart
* Position-adaptive signal placement
* High-visibility color scheme
3. Signal Generation Logic
The system generates signals based on two key conditions:
* Primary Condition :
* BUY : Price crossunder Supertrend2 (Factor 1.618)
* SELL : Price crossover Supertrend2 (Factor 1.618)
* Confirmation Filter :
* Signals only trigger when Supertrend3 confirms the trend direction
* Reduces false signals in volatile markets
Technical Details
Input Parameters
* ATR Period : 10 (default)
* Customizable for different market conditions
* Affects sensitivity of all Supertrend levels
* Factor Settings :
* All factors are customizable
* Default values based on Fibonacci sequence
* Minimum value: 0.01
* Step size: 0.01
Alert System
* Built-in alert conditions
* Customizable alert messages
* Real-time notification support
Use Cases
* Trend Trading
* Identify strong trend directions
* Filter out weak signals
* Confirm trend continuations
* Risk Management
* Multiple trend levels for stop-loss placement
* Clear entry and exit signals
* Trend strength visualization
* Market Analysis
* Multi-timeframe analysis capability
* Trend strength assessment
* Market structure identification
Benefits
* Reliability
* Based on proven Supertrend algorithm
* Enhanced with Fibonacci mathematics
* Multiple confirmation levels
* Clarity
* Clear visual signals
* Easy-to-interpret interface
* Reduced noise in signal generation
* Flexibility
* Customizable parameters
* Adaptable to different markets
* Suitable for various trading styles
Performance Considerations
* Optimized code structure
* Efficient calculation methods
* Minimal resource usage
Installation and Usage
Setup
* Add indicator to chart
* Adjust parameters if needed
* Enable alerts as required
Best Practices
* Use with other confirmation tools
* Adjust factors based on market volatility
* Consider timeframe appropriateness
Backtesting Results and Strategy Performance
This indicator is specifically designed for pullback trading with optimized risk-reward ratios in trend-following strategies. Below are the detailed backtesting results from our proprietary strategy implementation:
BTCUSDT Performance (Binance)
* Test Period: Approximately 7 years
* Risk-Reward Ratio: 2:1
* Take Profit: 8%
* Stop Loss: 4%
Key Metrics (BTCUSDT):
* Net Profit: +2,579%
* Total Trades: 551
* Win Rate: 44.8%
* Profit Factor: 1.278
* Maximum Drawdown: 42.86%
ETHUSD Performance (Binance)
* Risk-Reward Ratio: 4.33:1
* Take Profit: 13%
* Stop Loss: 3%
Key Metrics (ETHUSD):
* Net Profit: +8,563%
* Total Trades: 581
* Win Rate: 32%
* Profit Factor: 1.32
* Maximum Drawdown: 55%
Strategy Highlights:
* Optimized for pullback trading in strong trends
* Focus on high risk-reward ratios
* Proven effectiveness in major cryptocurrency pairs
* Consistent performance across different market conditions
* Robust profit factor despite moderate win rates
Note: These results are from our proprietary strategy implementation and should be used as reference only. Individual results may vary based on market conditions and implementation.
Important Considerations:
* The strategy demonstrates strong profitability despite lower win rates, emphasizing the importance of proper risk-reward ratios
* Higher drawdowns are compensated by significant overall returns
* The system shows adaptability across different cryptocurrencies with consistent profit factors
* Results suggest optimal performance in volatile crypto markets
Real Trading Examples
BTCUSDT 4-Hour Chart Analysis
Example of pullback strategy implementation on Bitcoin, showing clear trend definition and entry points
ETHUSDT 4-Hour Chart Analysis
Ethereum chart demonstrating effective signal generation during strong trends
BTCUSDT Detailed Signal Example (15-Minute Scalping)
Close-up view of signal generation and trend confirmation process on 15-minute timeframe, demonstrating the indicator's effectiveness for scalping operations
Chart Analysis Notes:
* Green and red zones clearly indicate trend direction
* Multiple timeframe confirmation visible through different Supertrend levels
* Clear entry signals during pullbacks in established trends
* Precise stop-loss placement opportunities below support levels
Implementation Guidelines:
* Wait for main trend confirmation from Factor 3 (2.618)
* Enter trades on pullbacks to Factor 2 (1.618)
* Use Factor 1 (0.618) for fine-tuning entry points
* Place stops below the relevant Supertrend level
Footnotes:
* Charts provided are from Binance exchange, using both 4-hour and 15-minute timeframes
* Trading view screenshots captured during actual market conditions
* Indicators shown: Multi Fibonacci Supertrend with all three factors
* Time period: Recent market activity showing various market conditions
Important Notice:
These charts are for educational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management.
Disclaimer
This indicator is for informational purposes only. Past performance is not indicative of future results. Always conduct proper risk management and due diligence.
License
Open source under MIT License
Author's Note
Contributions and suggestions for improvement are welcome. Please feel free to fork and enhance.
Unlock the Power of Seasonality: Monthly Performance StrategyThe Monthly Performance Strategy leverages the power of seasonality—those cyclical patterns that emerge in financial markets at specific times of the year. From tax deadlines to industry-specific events and global holidays, historical data shows that certain months can offer strong opportunities for trading. This strategy was designed to help traders capture those opportunities and take advantage of recurring market patterns through an automated and highly customizable approach.
The Inspiration Behind the Strategy:
This strategy began with the idea that market performance is often influenced by seasonal factors. Historically, certain months outperform others due to a variety of reasons, like earnings reports, holiday shopping, or fiscal year-end events. By identifying these periods, traders can better time their market entries and exits, giving them an advantage over those who solely rely on technical indicators or news events.
The Monthly Performance Strategy was built to take this concept and automate it. Instead of manually analyzing market data for each month, this strategy enables you to select which months you want to focus on and then executes trades based on predefined rules, saving you time and optimizing the performance of your trades.
Key Features:
Customizable Month Selection: The strategy allows traders to choose specific months to test or trade on. You can select any combination of months—for example, January, July, and December—to focus on based on historical trends. Whether you’re targeting the historically strong months like December (often driven by the 'Santa Rally') or analyzing quieter months for low volatility trades, this strategy gives you full control.
Automated Monthly Entries and Exits: The strategy automatically enters a long position on the first day of your selected month(s) and exits the trade at the beginning of the next month. This makes it perfect for traders who want to benefit from seasonal patterns without manually monitoring the market. It ensures precision in entering and exiting trades based on pre-set timeframes.
Re-entry on Stop Loss or Take Profit: One of the standout features of this strategy is its ability to re-enter a trade if a position hits the stop loss (SL) or take profit (TP) level during the selected month. If your trade reaches either a SL or TP before the month ends, the strategy will automatically re-enter a new trade the next trading day. This feature ensures that you capture multiple trading opportunities within the same month, instead of exiting entirely after a successful or unsuccessful trade. Essentially, it keeps your capital working for you throughout the entire month, not just when conditions align perfectly at the beginning.
Built-in Risk Management: Risk management is a vital part of this strategy. It incorporates an Average True Range (ATR)-based stop loss and take profit system. The ATR helps set dynamic levels based on the market’s volatility, ensuring that your stops and targets adjust to changing market conditions. This not only helps limit potential losses but also maximizes profit potential by adapting to market behavior.
Historical Performance Testing: You can backtest this strategy on any period by setting the start year. This allows traders to analyze past market data and optimize their strategy based on historical performance. You can fine-tune which months to trade based on years of data, helping you identify trends and patterns that provide the best trading results.
Versatility Across Asset Classes: While this strategy can be particularly effective for stock market indices and sector rotation, it’s versatile enough to apply to other asset classes like forex, commodities, and even cryptocurrencies. Each asset class may exhibit different seasonal behaviors, allowing you to explore opportunities across various markets with this strategy.
How It Works:
The trader selects which months to test or trade, for example, January, April, and October.
The strategy will automatically open a long position on the first trading day of each selected month.
If the trade hits either the take profit or stop loss within the month, the strategy will close the current position and re-enter a new trade on the next trading day, provided the month has not yet ended. This ensures that the strategy continues to capture any potential gains throughout the month, rather than stopping after one successful trade.
At the start of the next month, the position is closed, and if the next month is also selected, a new trade is initiated following the same process.
Risk Management and Dynamic Adjustments:
Incorporating risk management with this strategy is as easy as turning on the ATR-based system. The strategy will automatically calculate stop loss and take profit levels based on the market’s current volatility, adjusting dynamically to the conditions. This ensures that the risk is controlled while allowing for flexibility in capturing profits during both high and low volatility periods.
Maximizing the Seasonal Edge:
By automating entries and exits based on specific months and combining that with dynamic risk management, the Ultimate Monthly Performance Strategy takes advantage of seasonal patterns without requiring constant monitoring. The added re-entry feature after hitting a stop loss or take profit ensures that you are always in the game, maximizing your chances to capture profitable trades during favorable seasonal periods.
Who Can Benefit from This Strategy?
This strategy is perfect for traders who:
Want to exploit the predictable, recurring patterns that occur during specific months of the year.
Prefer a hands-off, automated trading approach that allows them to focus on other aspects of their portfolio or life.
Seek to manage risk effectively with ATR-based stop losses and take profits that adjust to market conditions.
Appreciate the ability to re-enter trades when a take profit or stop loss is hit within the month, ensuring that they don't miss out on multiple opportunities during a favorable period.
In summary, the Ultimate Monthly Performance Strategy provides traders with a comprehensive tool to capitalize on seasonal trends, optimize their trading opportunities throughout the year, and manage risk effectively. The built-in re-entry system ensures you continue to benefit from the market even after hitting targets within the same month, making it a robust strategy for traders looking to maximize their edge in any market.
Risk Disclaimer:
Trading financial markets involves significant risk and may not be suitable for all investors. The Monthly Performance Strategy is designed to help traders identify seasonal trends, but past performance does not guarantee future results. It is important to carefully consider your risk tolerance, financial situation, and trading goals before using any strategy. Always use appropriate risk management and consult with a professional financial advisor if necessary. The use of this strategy does not eliminate the risk of losses, and traders should be prepared for the possibility of losing their entire investment. Be sure to test the strategy on a demo account before applying it in live markets.
