Volume ValueWhen VelocityTitle: Volume ValueWhen Velocity Trading Strategy
▶ Introduction:
The " Volume ValueWhen Velocity " trading strategy is designed to generate long position signals based on various technical conditions, including volume thresholds, RSI (Relative Strength Index), and price action relative to the Simple Moving Average (SMA). The strategy aims to identify potential buy opportunities when specific criteria are met, helping traders capitalize on potential bullish movements.
▶ How to use and conditions
★ Important : Only on Spot Binance BINANCE:BTCUSDT
Name: Volume ValueWhen Velocity
Operating mode: Long on Spot BINANCE BINANCE:BTCUSDT
Timeframe: Only one hour
Market: Crypto
currency: Bitcoin only
Signal type: Medium or short term
Entry: All sections in the Technical Indicators and Conditions section must be saved to enter (This is explained below)
Exit: Based on loss limit and profit limit It is removed in the settings section
Backtesting:
⁃ Exchange: BINANCE BINANCE:BTCUSDT
⁃ Pair: BTCUSDT
⁃ Timeframe:1h
⁃ Fee: 0.1%
- Initial Capital: 1,000 USDT
- Position sizing: 500 usdt
-Trading Range: 2022-07-01 11:30 ___ 2023-07-21 14:30
▶ Strategy Settings and Parameters:
1. `strategy(title='Volume ValueWhen Velocity', ...`: Sets the strategy title, initial capital, default quantity type, default quantity value, commission value, and trading currency.
↬ Stop-Loss and Take-Profit Settings:
1. long_stoploss_value and long_stoploss_percentage : Define the stop-loss percentage for long positions.
2. long_takeprofit_value and long_takeprofit_percentage : Define the take-profit percentage for long positions.
↬ ValueWhen Occurrence Parameters:
1. occurrence_ValueWhen_1 and occurrence_ValueWhen_2 : Control the occurrences of value events.
2. `distance_value`: Specifies the minimum distance between occurrences of ValueWhen 1 and ValueWhen 2.
↬ RSI Settings:
1. rsi_over_sold and rsi_length : Define the oversold level and RSI length for RSI calculations.
↬ Volume Thresholds:
1. volume_threshold1 , volume_threshold2 , and volume_threshold3 : Set the volume thresholds for multiple volume conditions.
↬ ATR (Average True Range) Settings:
1. atr_small and atr_big : Specify the periods used to calculate the Average True Range.
▶ Date Range for Back-Testing:
1. start_date, end_date, start_month, end_month, start_year, and end_year : Define the date range for back-testing the strategy.
▶ Technical Indicators and Conditions:
1. rsi: Calculates the Relative Strength Index (RSI) based on the defined RSI length and the closing prices.
2. was_over_sold: Checks if the RSI was oversold in the last 10 bars.
3. getVolume and getVolume2 : Custom functions to retrieve volume data for specific bars.
4. firstCandleColor : Evaluates the color of the first candle based on different timeframes.
5. sma : Calculates the Simple Moving Average (SMA) of the closing price over 13 periods.
6. numCandles : Counts the number of candles since the close price crossed above the SMA.
7. atr1 : Checks if the ATR_small is less than ATR_big for the specified security and timeframe.
8. prevClose, prevCloseBarsAgo, and prevCloseChange : ValueWhen functions to calculate the change in the close price between specific occurrences.
9. atrval: A condition based on the ATR_value3.
▶ Buy Signal Condition:
Condition: A combination of multiple volume conditions.
buy_signal: The final buy signal condition that considers various technical conditions and their interactions.
▶ Long Strategy Execution:
1. The strategy will enter a long position (buy) when the buy_signal condition is met and within the specified date range.
2. A stop-loss and take-profit will be set for the long position to manage risk and potential profits.
▶ Conclusion:
The " Volume ValueWhen Velocity " trading strategy is designed to identify long position opportunities based on a combination of volume conditions, RSI, and price action. The strategy aims to capitalize on potential bullish movements and utilizes a stop-loss and take-profit mechanism to manage risk and optimize potential returns. Traders can use this strategy as a starting point for their own trading systems or further customize it to suit their preferences and risk appetite. It is crucial to thoroughly back-test and validate any trading strategy before deploying it in live markets.
↯ Disclaimer:
Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Pesquisar nos scripts por "backtest"
Yesterday's High v.17.07Yesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of INJ, a 12% Take-Profit and a 1.5% Stop-Loss were set, with an activated trailing-stop percentage, TRL 1 and OFF 0.5.
To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name: Yesterday's High Breakout - Trend Follower Strategy
Author: @tumiza999
Category: Trend Follower, Breakout of Yesterday's High.
Operating mode: Spot or Futures (only long).
Trade duration: Intraday.
Timeframe: 30M, 1H, 2H, 4H
Market: Crypto
Suggested usage: Short-term trading, when the market is in trend and it is showing high volatility.
Entry: When there is a breakout of Yesterday's High.
Exit: Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration:
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting:
⁃ Exchange: BINANCE
⁃ Pair: INJUSDT
⁃ Timeframe: 4H
- Treshold: 1
- Gap%: 1
- SL: 1.5
- TP:12
- TRL: 1
- OFF-TRL: 0.5
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits: LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer: Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Probability Envelopes (PBE)Introduction
In the world of trading, technical analysis is vital for making informed decisions about the future direction of an asset's price. One such tool is the use of indicators, mathematical calculations that can help traders predict market trends. This article delves into an innovative indicator called the Probability Envelopes Indicator, which offers valuable insights into the potential price levels an asset may reach based on historical data. This in-depth look explores the statistical foundations of the indicator, highlighting its key components and benefits.
Section 1: Calculating Price Movements with Log Returns and Percentages
The Probability Envelopes Indicator provides the option to use either log returns or percentage changes when calculating price movements. Each method has its advantages:
Log Returns: These are calculated as the natural logarithm of the ratio of the current price to the previous price. Log returns are considered more stable and less sensitive to extreme price fluctuations.
Percentage Changes: These are calculated as the percentage difference between the current price and the previous price. They are simpler to interpret and easier to understand for most traders.
Section 2: Understanding Mean, Variance, and Standard Deviation
The Probability Envelopes Indicator utilizes various statistical measures to analyze historical price movements:
Mean: This is the average of a set of numbers. In the context of this indicator, it represents the average price movement for bullish (green) and bearish (red) scenarios.
Variance: This measure represents the dispersion of data points in a dataset. A higher variance indicates a greater spread of data points from the mean. Variance is calculated as the average of the squared differences from the mean.
Standard Deviation: This is the square root of the variance. It is a measure of the amount of variation or dispersion in a dataset. In the context of this indicator, standard deviations are used to calculate the width of the bands around the expected mean.
Section 3: Analyzing Historical Price Movements and Probabilities
The Probability Envelopes Indicator examines historical price movements and calculates probabilities based on their frequency:
The indicator first identifies and categorizes price movements into bullish (green) and bearish (red) scenarios.
It then calculates the probability of each price movement occurring by dividing the frequency of the movement by the total number of occurrences in each category (bullish or bearish).
The expected green and red movements are calculated by multiplying the probabilities by their respective price movements and summing the results.
The total expected movement, or weighted average, is calculated by combining the expected green and red movements and dividing by the total number of occurrences.
Section 4: Constructing the Probability Envelopes
The Probability Envelopes Indicator utilizes the calculated statistics to construct its bands:
The expected mean is calculated using the total expected movement and applied to the current open price.
An exponential moving average (EMA) is used to smooth the expected mean, with the smoothing length determining the degree of responsiveness.
The upper and lower bands are calculated by adding and subtracting the mean green and red movements, respectively, along with their standard deviations multiplied by a user-defined multiplier.
Section 5: Benefits of the Probability Envelopes Indicator
The Probability Envelopes Indicator offers numerous advantages to traders:
Enhanced Decision-Making: By providing probability-based estimations of future price levels, the indicator can help traders make more informed decisions and potentially improve their trading strategies.
Versatility: The indicator is applicable to various financial instruments, such as stocks, forex, commodities, and cryptocurrencies, making it a valuable tool for traders in different markets.
Customization: The indicator's parameters, including the use of log returns, multiplier values, and smoothing length, can be adjusted according to the user's preferences and trading style. This flexibility allows traders to fine-tune the Probability Envelopes Indicator to better suit their needs and goals.
Risk Management: The Probability Envelopes Indicator can be used as a component of a risk management strategy by providing insight into potential price movements. By identifying potential areas of support and resistance, traders can set stop-loss and take-profit levels more effectively.
Visualization: The graphical representation of the indicator, with its clear upper and lower bands, makes it easy for traders to quickly assess the market and potential price levels.
Section 6: Integrating the Probability Envelopes Indicator into Your Trading Strategy
When incorporating the Probability Envelopes Indicator into your trading strategy, consider the following tips:
Confirmation Signals: Use the indicator in conjunction with other technical analysis tools, such as trend lines, moving averages, or oscillators, to confirm the strength and direction of the market trend.
Timeframes: Experiment with different timeframes to find the optimal settings for your trading strategy. Keep in mind that shorter timeframes may generate more frequent signals but may also increase the likelihood of false signals.
Risk Management: Always establish a proper risk management strategy that includes setting stop-loss and take-profit levels, as well as managing your position sizes.
Backtesting: Test the Probability Envelopes Indicator on historical data to evaluate its effectiveness and fine-tune its parameters to optimize your trading strategy.
Section 7: Cons and Limitations of the Probability Envelopes Indicator
While the Probability Envelopes Indicator offers several advantages to traders, it is essential to be aware of its potential cons and limitations. Understanding these can help you make better-informed decisions when incorporating the indicator into your trading strategy.
Lagging Nature: The Probability Envelopes Indicator is primarily based on historical data and price movements. As a result, it may be less responsive to real-time changes in market conditions, and the predicted price levels may not always accurately reflect the market's current state. This lagging nature can lead to late entry and exit signals.
False Signals: As with any technical analysis tool, the Probability Envelopes Indicator can generate false signals. These occur when the indicator suggests a potential price movement, but the market does not follow through. It is crucial to use other technical analysis tools to confirm the signals and minimize the impact of false signals on your trading decisions.
Complex Statistical Concepts: The Probability Envelopes Indicator relies on complex statistical concepts and calculations, which may be challenging to grasp for some traders, particularly beginners. This complexity can lead to misunderstandings and misuse of the indicator if not adequately understood.
Overemphasis on Past Data: While historical data can be informative, relying too heavily on past performance to predict future movements can be limiting. Market conditions can change rapidly, and relying solely on past data may not provide an accurate representation of the current market environment.
No Guarantees: The Probability Envelopes Indicator, like all technical analysis tools, cannot guarantee success. It is essential to approach trading with realistic expectations and understand that no indicator or strategy can provide foolproof results.
To overcome these limitations, it is crucial to combine the Probability Envelopes Indicator with other technical analysis tools and utilize a comprehensive risk management strategy. By doing so, you can better understand the market and increase your chances of success in the ever-changing financial markets.
Section 8: Probability Envelopes Indicator vs. Bollinger Bands
Bollinger Bands and the Probability Envelopes Indicator are both technical analysis tools designed to identify potential support and resistance levels, as well as potential trend reversals. However, they differ in their underlying concepts, calculations, and applications. This section will provide a deep dive into the differences between these two indicators and how they can complement each other in a trading strategy.
Underlying Concepts and Calculations:
Bollinger Bands:
Bollinger Bands are based on a simple moving average (SMA) of the price data, with upper and lower bands plotted at a specified number of standard deviations away from the SMA.
The distance between the bands widens during periods of increased price volatility and narrows during periods of low volatility, indicating potential trend reversals or breakouts.
The standard settings for Bollinger Bands typically involve a 20-period SMA and a 2 standard deviation distance for the upper and lower bands.
Probability Envelopes Indicator:
The Probability Envelopes Indicator calculates the expected price movements based on historical data and probabilities, utilizing mean and standard deviation calculations for both upward and downward price movements.
It generates upper and lower bands based on the calculated expected mean movement and the standard deviation of historical price changes, multiplied by a user-defined multiplier.
The Probability Envelopes Indicator also allows users to choose between using log returns or percentage changes for the calculations, adding flexibility to the indicator.
Key Differences:
Calculation Method: Bollinger Bands are based on a simple moving average and standard deviations, while the Probability Envelopes Indicator uses statistical probability calculations derived from historical price changes.
Flexibility: The Probability Envelopes Indicator allows users to choose between log returns or percentage changes and adjust the multiplier, offering more customization options compared to Bollinger Bands.
Risk Management: Bollinger Bands primarily focus on volatility, while the Probability Envelopes Indicator incorporates probability calculations to provide additional insights into potential price movements, which can be helpful for risk management purposes.
Complementary Use:
Using both Bollinger Bands and the Probability Envelopes Indicator in your trading strategy can offer valuable insights into market conditions and potential price levels.
Bollinger Bands can provide insights into market volatility and potential breakouts or trend reversals based on the widening or narrowing of the bands.
The Probability Envelopes Indicator can offer additional information on the expected price movements based on historical data and probabilities, which can be helpful in anticipating potential support and resistance levels.
Combining these two indicators can help traders to better understand market dynamics and increase their chances of identifying profitable trading opportunities.
In conclusion, while both Bollinger Bands and the Probability Envelopes Indicator aim to identify potential support and resistance levels, they differ significantly in their underlying concepts, calculations, and applications. By understanding these differences and incorporating both tools into your trading strategy, you can gain a more comprehensive understanding of the market and make more informed trading decisions.
In conclusion, the Probability Envelopes Indicator is a powerful and versatile technical analysis tool that offers unique insights into expected price movements based on historical data and probability calculations. It provides traders with the ability to identify potential support and resistance levels, as well as potential trend reversals. When compared to Bollinger Bands, the Probability Envelopes Indicator offers more customization options and incorporates probability-based calculations for a different perspective on market dynamics.
Although the Probability Envelopes Indicator has its limitations and potential cons, such as the reliance on historical data and the assumption that past performance is indicative of future results, it remains a valuable addition to any trader's toolkit. By using the Probability Envelopes Indicator in conjunction with other technical analysis tools, such as Bollinger Bands, traders can gain a more comprehensive understanding of the market and make more informed trading decisions.
Ultimately, the success of any trading strategy relies on the ability to interpret and apply multiple indicators effectively. The Probability Envelopes Indicator serves as a unique and valuable tool in this regard, providing traders with a deeper understanding of the market and its potential price movements. By utilizing this indicator in combination with other tools and techniques, traders can increase their chances of success and optimize their trading strategies.
30MIN CYCLE█ HOW DOES IT WORK?
The known 90 min cycle is used as one killzone. But actually all 18 min are relevant to search for a trade. All 18 min when a new box starts only then is the placement of an order valid. If the entry candle isn't in a box then it will probably fail. The boxes should only be used in the M1 or M5 timeframe. The best hitrate is in the M1 timeframe. Included are the last 48 "Mini-Killzones" für intraday trading and backtesting. These "Mini-Killzones" can be used with the "Liquidity Inducement Strategy".
█ WHAT MAKES IT UNIQUE?
This is the first indicator on tradingview that shows all mini-killzones for trading and backtesting a whole tradingday. The well-known killzones of ICT are from 08:00-11:00 and 14:00 - 17:00 (UTC+1) but with this indicator there is finally a refinement of the ICT Smart Money Concept killzones.
█ HOW TO USE IT?
For a proper use of this indicator we suggest to know already at least SMC or better Liquidity Indcuement Trading. This indicator is a further confluence before placing an order. After you made your setup you will have these mini-killzones as a confluence. We don't suggest to open a trade only according to this indicator.
█ ADDITIONAL INFO
This indicator is free to use for all tradingview users.
█ DISCLAIMER
This is not financial advice.
DRM StrategyOne of the ways I go when I develop strategies is by reducing the number of parameters and removing fixed parameters and levels.
In this strategy, I'm trying to create an RSI indicator with a dynamic length.
Length is computed based on the correlation between Price and its momentum.
You can set min and max values for the RSI, and if the correlation is close to 1, we'll be at a min RSI value. When it's -1, we'll be at the max level.
I got this idea from Sofien Kaabar's book.
The strategy is super simple, and there might be much room for improvement.
Performance on the deep backtesting is not excellent, so I think the strategy needs some filters for regimes, etc.
Thanks to @MUQWISHI for helping me code it.
Disclaimer
Please remember that past performance may not indicate future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
I11L - Meanreverter 4h---Overview---
The system buys fear and sells greed.
Its relies on a Relative Strength Index (RSI) and moving averages (MA) to find oversold and overbought states.
It seems to work best in market conditions where the Bond market has a negative Beta to Stocks.
Backtests in a longer Timeframe will clearly show this.
---Parameter---
Frequency: Smothens the RSI curve, helps to "remember" recent highs better.
RsiFrequency: A Frequency of 40 implies a RSI over the last 40 Bars.
BuyZoneDistance: Spacing between the different zones. A wider spacing reduces the amount of signals and icnreases the holding duration. Should be finetuned with tradingcosts in mind.
AvgDownATRSum: The multiple of the Average ATR over 20 Bars * amount of opentrades for your average down. I choose the ATR over a fixed percent loss to find more signals in low volatility environments and less in high volatility environments.
---Some of my thoughts---
Be very careful about the good backtesting performance in many US-Stocks because the System had a favourable environment since 1970.
Be careful about the survivorship bias as well.
52% of stocks from the S&P500 were removed since 2000.
I discount my Annual Results by 5% because of this fact.
You will find yourself quite often with very few signals because of the high market correlation.
My testing suggests that there is no expected total performance difference between a signal from a bad and a signal from a good market condition but a higher volatility.
I am sharing this strategy because i am currently not able to implement it as i want to and i think that meanreversion is starting to be taken more serious by traders.
The challange in implementing this strategy is that you need to be invested 100% of the time to retrieve the expected annual performance and to reduce the fat tail risk by market crashes.
Price Divergence IndicatorThis Price Divergence Indicator indicator modifies the standard Divergence Indicator to look for price divergences between the current chart and any other selected TradingView chart.
The thesis that this indicator is built upon:
Prices on assets or indices that are normally correlated move in lock step. Where there are deviations between the confirmed highs or lows of two assets or indices it is likely that they will "catch up" in the near future.
By default it will load the price data for the SPX and look for price divergences on the current chart timeframe. Any TradingView Symbol can be selected as the 'Comparison Source' and any timeframe. Some of the options I've been trying out include:
SPX vs NDQ
XAO vs SPX
UK100 vs NDQM
MSFT vs NDQM
GOOG vs NDQM
AMZN vs MSFT
BTC vs ETH
BTC vs NDQ
BTC vs DXY
I've found looking for divergences on a longer timeframe can be useful and don't expect any meaningful results if you set it to shorter than chart timeframes.
Alerts can be created based on any of the divergences and the 'Backtest Buy Signal' can be used to send notification to a backtester (bull = 2, hidden bull = 1, neutral = 0, hidden bear = -1, bear = -2), this is plotted to display.none, so enable it in Settings - Style and disable all other plots to see it.
Divergences are measured between the CONFIRMED peaks of the two charts. The confirmation timeframe is set using 'Pivot Lookback Right'. The lower the lookback the quicker the signal and the more likely it is to not have hit an actual peak, a higher lookback will give a much more dependable signal but the move may be finished by the time the alert actually fires. The "Plot When Alerts Fire" option should give you an idea (top and bottom triangles) of what to expect, but you should watch bar replays to understand how your setting will impact when alerts are created and potential false positives.
BT-Bollinger Bands - Trend FollowingEsse script foi criado para estudo de Backtest.
O script usa as Bandas de Bollinger para indicar o início de uma tendência, a entrada é configurada quando o preço abre abaixo e fecha acima da banda superior ou para venda quando o preço abre acima e fecha abaixo da banda inferior.
Não há um stop fixo e nem alvo fixo a saída se dá quando o preço toca a média da banda.
Você pode usar uma média móvel como filtro combinado com a estratégia.
O Script também pode ser usado com algum serviço de bot como 3commas.io , basta colocar as mensagens de entrada e saída para o bot.
Autor : Credsonb - Nick: M4TR1X_BR
Neste gráfico estou usando as seguintes configurações:
Bandas Bollinger: 7
Desvio Padrão: 1.5
Time Frame: 12hs
Ticker: ETH
This script was created for Backtest study.
script uses Bollinger Bands to indicate the start of a trend, entry is set when price opens below and closes above the upper band or for short when price opens above and closes below the lower band.
There is no fixed stop and no fixed target, the exit occurs when the price touches the average of the band.
You can use a moving average as a filter combined with the strategy.
The Script can also be used with some bot service like 3commas. io , just put the input and output messages to the bot.
Author : Credsonb - Nick: M4TR1X_BR
BT-SAR Ema, Squeeze, Volatility
Esse script foi criado para estudo de Backtest.
Ele usa o SAR PARABÓLICO como indicador de sinal de entrada, você também pode combinar 3 indicadores para filtrar as entradas: Média Móvel, Squeeze Momentum e Volatility Oscilator .
Existe duas entradas, quando o SAR Parabólico vira ou pelo Breakout (usando o último preço) do SAR Parabólico antes dele virar.
As Os filtros podem ser usados de forma combinada ou individual.
O Script também pode ser usado com algum serviço de bot como 3commas.io, basta colocar as mensagens de entrada e saída para o bot.
This script was created for Backtest study.
It uses PARABOLIC SAR as input signal indicator, you can also combine 3 indicators to filter inputs: Moving Average, Squeeze Momentum and Volatility Oscillator .
There are two entries, when the Parabolic SAR turns or by Breakout (using the last price) of the Parabolic SAR before it turns.
The Filters can be used in combination or individually.
The Script can also be used with some bot service like 3commas.io, just put the input and output messages to the bot.
Chanu Delta RSI StrategyThis strategy is built on the Chanu Delta RSI , which indicates the strength of the Bitcoin market. The problem with the previous Chanu Delta Strategy was that it was simply based on the price difference between the two Bitcoin markets, so there was no universality. However, this new Chanu Delta RSI strategy solves the problem by introducing an RSI that compares the price difference trend.
When the Chanu Delta RSI hits “Bull Level” and “Bear Level” and closes the candle, long and short signals are triggered respectively. The example shown on the screen is a default setting optimized for a 4-hour candlestick strategy based on the Bybit BTCUSDT futures market. You can use it by adjusting the setting value and modifying it to suit you.
This strategy is selectable from both reference and large amplitude BTCUSD markets in order to enable fine backtesting. I recommend using BYBIT:BTCUSDT for the reference market and COINBASE:BTCUSD for the large amplitude market.
(Note) Using the "Chanu Delta RSI" to know the current indicator value in real time, it is convenient to predict the signal of the strategy.
(Note) Because the Chanu Delta RSI represents the price difference based on the Bybit BTCUSDT futures market, backtesting is possible from March 2020.
_____________________________________________________________
이 전략은 비트코인 시장의 강점을 나타내는 Chanu Delta RSI를 기반으로 합니다. 기존 Chanu Delta 전략의 문제점은 단순히 두 비트코인 시장의 가격차를 기준으로 하여 보편성이 없었다는 점이다. 하지만 이번 새로운 Chanu Delta RSI 전략은 가격차이 추세를 비교하는 RSI를 도입해 문제를 해결했습니다.
Chanu Delta RSI가 "Bull Level"과 "Bear Level"에 도달하고 봉마감하면 롱, 숏 신호가 각각 트리거됩니다. 화면에 보이는 예시는 Bybit BTCUSDT 선물 시장을 기반으로 한 4시간 캔들스틱 전략에 최적화된 기본 설정입니다. 설정값을 조정하여 자신에게 맞게 수정하여 사용하시면 됩니다.
이 전략은 정밀한 백테스팅을 가능하게 하기 위해 참조 및 큰 진폭 BTCUSD 시장에서 모두 선택할 수 있습니다. 참조 시장에는 BYBIT:BTCUSDT를 사용하고 큰 진폭 시장에는 COINBASE:BTCUSD를 사용하는 것이 좋습니다.
(주) "Chanu Delta RSI"를 이용하여 현재 지표 값을 실시간으로 알 수 있어 전략의 시그널을 예측하는데 편리합니다.
(주) Chanu Delta RSI는 바이비트 BTCUSDT 선물시장을 기준으로 가격차이를 나타내므로 2020년 3월부터 백테스팅이 가능합니다.
Argo I (alerts for 3commas single bots)This script lets users create BUY/SELL alerts for 3commas single bots in a simple way, based on a built in set of indicators that can be tweaked to work together or separately through the study settings. Indicators include Bollinger Bands, Williams %R, RSI, EMA, SMA , Market Cipher, Inverse Fisher Transform.
If the user choses to create both BUY and SELL signals from the study settings, the alert created will send both BUY and SELL signals for the selected pair. Note the script will only send alerts for the pair selected in the study settings, not for the current chart (if different).
How to use:
- Add the script to the current chart
- Open the study settings , insert bot details. Pairs MUST be in capital letters or 3commas will not recognize them.
- Still in the study settings, tweak the deal start/close conditions from various indicators until happy. The study will plot the entry / exit points below the current chart (1 = buy, 2 = sell)
- Ideally, test the settings with a backtesting script. The present script is compatible with the Trading Parrot's backtester.
- When happy, right click on the "..." next to the study name, then "Add alert'".
- Under "Condition", on the second line, chose "Any alert () function call". Add the webhook from 3commas, give it a name, and "create".
Happy tweaking!
How to use Leverage and Margin in PineScriptEn route to being absolutely the best and most complete trading platform out there, TradingView has just closed 2 gaps in their PineScript language.
It is now possible to create and backtest a strategy for trading with leverage.
Backtester now produces Margin Calls - so recognizes mid-trade drawdown and if it is too big for the broker to maintain your trade, some part of if will be instantly closed.
New additions were announced in official blogpost , but it lacked code examples, so I have decided to publish this script. Having said that - this is purely educational stuff.
█ LEVERAGE
Let's start with the Leverage. I will discuss this assuming we are always entering trades with some percentage of our equity balance (default_qty_type = strategy.percent_of_equity), not fixed order quantity.
If you want to trade with 1:1 leverage (so no leverage) and enter a trade with all money in your trading account, then first line of your strategy script must include this parameter:
default_qty_value = 100 // which stands for 100%
Now, if you want to trade with 30:1 leverage, you need to multipy the quantity by 30x, so you'd get 30 x 100 = 3000:
default_qty_value = 3000 // which stands for 3000%
And you can play around with this value as you wish, so if you want to enter each trade with 10% equity on 15:1 leverage you'd get default_qty_value = 150.
That's easy. Of course you can modify this quantity value not only in the script, but also afterwards in Script Settings popup, "Properties" tab.
█ MARGIN
Second newly released feature is Margin calculation together with Margin Calls. If the market goes against your trades and your trading account cannot maintain mid-trade drawdown - those trades will be closed in full or partly. Also, if your trading account cannot afford to open more trades (pyramiding those trades), Margin mechanism will prevent them from being entered.
I will not go into details about how Margin calculation works, it was all explainged in above mentioned blogpost and documentation .
All you need to do is to add two parameters to the opening line of your script:
margin_long = 1./30*50, margin_short = 1./30*50
Whereas "30" is a leverage scale as in 30:1, and "50" stands for 50% of Margin required by your broker. Personally the Required Margin number I've met most often is 50%, so I'm using value 50 here, but there are literally 1000+ brokers in this world and this is individual decision by each of them, so you'd better ask yourself.
--------------------
Please note, that if you ever encounter a strategy which triggers Margin Call at least once, then it is probably a very bad strategy. Margin Call is a last resort, last security measure - all the risks should be calculated by the strategy algorithm before it is ever hit. So if you see a Margin Call being triggred, then something is wrong with risk management of the strategy. Therefore - don't use it!
Improved simple RSI Buy/Sell at a level (SL/TP)Improved Simple Strategy based on RSI, using overbought or oversold levels.
Backtest: ETHPERP (FTX) - 30m
Set STOP LOSS and GET PROFIT as a percentage (2% and 10% by default).
If strategy.position_size != 0 algorithm convert percentages into points and set stop loss and take profit limit orders.
Delta-RSI Strategy (with filters)Delta-RSI Strategy (with filters):
This is a version of the Delta-RSI Oscillator strategy with several criteria available to filter entry and exit signals. This script is also suitable for backtesting over a user-defined period and offers several risk management options (take profit and stop loss).
Since the publication of the Delta-RSI Oscillator script, I have been asked many times to make it compatible with the Strategy Tester and add filtering criteria to minimize "false" signals. This version covers many of these requests. Feel free to insert your favorite D-RSI parameters and play around!
ABOUT DELTA-RSI
Delta-RSI represents a smoothed time derivative of the RSI designed as a momentum indicator (see links below):
INPUT DESCTIPTION
MODEL PARAMETERS
Polynomial Order : The order of local polynomial used to interpolate the relative strength index (RSI).
Length : The length of the lookback frame where local regression is applied.
RSI Length : The timeframe of RSI used as input.
Signal Length : The signal line is a EMA of the D-RSI time series. This input parameter defines the EMA length.
ALLOWED ENTRIES
The strategy can include long entries, short entries or both.
ENTRY AND EXIT CONDITIONS
Zero-crossing : bullish trade signal triggered when D-RSI crosses zero from negative to positive values (bearish otherwise)
Signal Line Crossing : bullish trade signal triggered when D-RSI crosses from below to above the signal line (bearish otherwise)
Direction Change : bullish trade signal triggered when D-RSI was negative and starts ascending (bearish otherwise)
APPLY FILTERS TO
The filters (described below) can be applied to long entry, short entry and exit signals.
RELATIVE VOLUME FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the current volume is greater than N times the average over the last M bars.
VOLATILITY FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the N-period average true range, ATR, is greater than the M-period ATR. If N < M, this condition implies increasing volatility.
OVERBOUGHT/OVERSOLD FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the value of 14-period RSI is in the range between N and M.
STOP LOSS/TAKE PROFIT
Fixed and trailing stop loss as well as take profit options are available.
FIXED BACKTESTING START/END DATES
If the checkboxes are not checked, the strategy will backtest all available price bars.
The Strategy - Ichimoku Kinko Hyo and moreThe purpose of this strategy is to make the signals from my scripts available for verification by backtests. Different signal and filter combinations can be created and specific manual parameter optimization can be carried out.
In detail, this strategy includes:
23 entry signals
two entry filters with each 9 filters
two exit filters with each 9 filters
take profit and stop loss
time period for backtesting
Simple EMA_Hull_RSI StrategyAnother simple strategy. Crossing EMA & Hull MA and the level of RSI (overbought/oversold) defines long or short.
Can be improved by varying the parameters and adding take profit / stop loss.
Backtest: ETHUSD (Bitmex): 5m
Simple RSI Strategy Buy/Sell at a certain levelSimple Strategy based on RSI, using overbought or oversold levels, defined by us, sell or buy an asset.
Backtest: ETHUSD (Bitmex) - 3h
TradingView Alerts to MT4 MT5 + dynamic variables NON-REPAINTINGAccidentally, I’m sharing open-source profitable Forex strategy. Accidentally, because this was aimed to be purely educational material. A few days ago TradingView released a very powerful feature of dynamic values from PineScript now being allowed to be passed in Alerts. And thanks to TradingConnector, they could be instantly executed in MT4 or MT5 platform of any broker in the world. So yeah - TradingConnector works with indices and commodities, too.
The logic of this EURUSD 6h strategy is very simple - it is based on Stochastic crossovers with stop-loss set under most recent pivot point. Setting stop-loss with surgical precision is possible exactly thanks to allowance of dynamic values in alerts. TradingConnector has been also upgraded to take advantage of these dynamic values and it now enables executing trades with pre-calculated stop-loss, take-profit, as well as stop and limit orders.
Another fresh feature of TradingConnector, is closing positions only partly - provided that the broker allows it, of course. A position needs to have trade_id specified at entry, referred to in further alerts with partial closing. Detailed spec of alerts syntax and functionalities can be found at TradingConnector website. How to include dynamic variables in alert messages can be seen at the very end of the script in alertcondition() calls.
The strategy also takes commission into consideration.
Slippage is intentionally left at 0. Due to shorter than 1 second delivery time of TradingConnector, slippage is practically non-existing. This can be achieved especially if you’re using VPS server, hosted in the same datacenter as your brokers’ servers. I am using such setup, it is doable. Small slippage and spread is already included in commission value.
This strategy is NON-REPAINTING and uses NO TRAILING-STOP or any other feature known to be faulty in TradingView backtester. Does it make this strategy bulletproof and 100% success-guaranteed? Hell no! Remember the no.1 rule of backtesting - no matter how profitable and good looking a script is, it only tells about the past. There is zero guarantee the same strategy will get similar results in the future.
To turn this script into study so that alerts can be produced, do 2 things:
1. comment “strategy” line at the beginning and uncomment “study” line
2. comment lines 54-59 and uncomment lines 62-65.
Then add script to the chart and configure alerts.
This script was build for educational purposes only.
Certainly this is not financial advice. Anybody using this script or any of its parts in any way, must be aware of high risks connected with trading.
Thanks @LucF and @a.tesla2018 for helping me with code fixes :)
TRAILING STOP LOSS TO LONG AND SHORT##THIS SCRIPT IS ON GITHUB
This TradingView strategy it is designed to integrate with other strategies with indicators.
It performs a trailing stop loss from entry and exit conditions.
In this strategy you can add conditions for long and short positions.
The strategy will ride up your stop loss when price moviment 1%.
The strategy will close your operation when the market price crossed the stop loss.
Also is possible to select the period that strategy will execute the backtest.
The strategy has the following parameters:
+ **INITIAL STOP LOSS** - Where can isert the value to first stop.
+ **POSITION TYPE** - Where can to select trade position.
+ **BACKTEST PERIOD** - To select range.
## DISCLAIMER
1. I am not licensed financial advisors or broker dealers. I do not tell you when or what to buy or sell. I developed this software which enables you execute manual or automated trades multiple trades using TradingView. The software allows you to set the criteria you want for entering and exiting trades.
2. Do not trade with money you cannot afford to lose.
3. I do not guarantee consistent profits or that anyone can make money with no effort. And I am not selling the holy grail.
4. Every system can have winning and losing streaks.
5. Money management plays a large role in the results of your trading. For example: lot size, account size, broker leverage, and broker margin call rules all have an effect on results. Also, your Take Profit and Stop Loss settings for individual pair trades and for overall account equity have a major impact on results. If you are new to trading and do not understand these items, then I recommend you seek education materials to further your knowledge.
**YOU NEED TO FIND AND USE THE TRADING SYSTEM THAT WORKS BEST FOR YOU AND YOUR TRADING TOLERANCE.**
**I HAVE PROVIDED NOTHING MORE THAN A TOOL WITH OPTIONS FOR YOU TO TRADE WITH THIS PROGRAM ON TRADINGVIEW.**
## NOTE
I accept suggestions to improve the script.
If you encounter any problems I will be happy to share with me.
+ Authors: @exit490
+ Revision: v1.0.0
+ Date: 03-Aug-2019
+ Pinescript version: 4
## LICENSE
Copyright 2019 Mauricio Pimenta / exit490
Trailing Stop Loss script may be freely distributed under the MIT license .
Adding some essential components to a prebuilt RSI strategyThis is more to be used as a blank_slate for any strategy build adding more effective backtesting with a period selector and inputs like TS, TP, SL that can all be used as plots for alerts.
It has the BackTest Component created by Pbergden
It also includes the standard long/short with trailing stop, take profit, stop loss and margin call.
Here is a video using the blank_slate to add in the built-in RSI Strategy.
youtu.be
We hope this brings good results and helps speed things up for everyone.
CM RSI-2 Strategy Lower IndicatorRSI-2 Strategy
***At the bottom of the page is a link where you can download the PDF of the Backtesting Results.
This year I am focusing on learning from two of the best mentors in the Industry with outstanding track records for Creating Systems, and learning the what methods actually work as far as back testing.
I came across the RSI-2 system that Larry Connors developed. Larry has become famous for his technical indicators, but his RSI-2 system is what actually put him “On The Map” per se. At first glance I didn’t think it would work well, but I decided to code it and ran backtests on the S&P 100 In Down Trending Markets, Up Trending Markets, and both combined. I was shocked by the results. So I thought I would provide them for you. I also ran a test on the Major forex Pairs (12) for the last 5 years, and All Forex Pairs (80) from 11/28/2007 - 6/09/2014, impressive results also.
The RSI-2 Strategy is designed to use on Daily Bars, however it is a short term trading strategy. The average length of time in a trade is just over 2 days. But the results CRUSH the general market averages.
Detailed Description of Indicators, Rules Below:
Link For PDF of Detailed Trade Results
d.pr
Original Post
CM RSI-2 Strategy - Upper Indicators.RSI-2 Strategy
***At the bottom of the page is a link where you can download the PDF of the Backtesting Results.
This year I am focusing on learning from two of the best mentors in the Industry with outstanding track records for Creating Systems, and learning the what methods actually work as far as back testing.
I came across the RSI-2 system that Larry Connors developed. Larry has become famous for his technical indicators, but his RSI-2 system is what actually put him “On The Map” per se. At first glance I didn’t think it would work well, but I decided to code it and ran backtests on the S&P 100 In Down Trending Markets, Up Trending Markets, and both combined. I was shocked by the results. So I thought I would provide them for you. I also ran a test on the Major forex Pairs (12) for the last 5 years, and All Forex Pairs (80) from 11/28/2007 - 6/09/2014, impressive results also.
The RSI-2 Strategy is designed to use on Daily Bars, however it is a short term trading strategy. The average length of time in a trade is just over 2 days. But the results CRUSH the general market averages.
Detailed Description of Indicators, Rules Below:
Link For PDF of Detailed Trade Results
d.pr
Original Post
12M Return Strategy This strategy is based on the original Dual Momentum concept presented by Gary Antonacci in his book “Dual Momentum Investing.”
It implements the absolute momentum portion of the framework using a 12-month rate of change, combined with a moving-average filter for trend confirmation.
The script automatically adapts the lookback period depending on chart timeframe, ensuring the return calculation always represents approximately one year, whether you are on daily, weekly, or monthly charts.
How the Strategy Works
1. 12-Month Return Calculation
The core signal is the 12-month price return, computed as:
(Current Price ÷ Price from ~1 year ago) − 1
This return:
Plots as a histogram
Turns green when positive
Turns red when negative
The lookback adjusts automatically:
1D chart → 252 bars
1W chart → 52 bars
1M chart → 12 bars
Other timeframes → estimated to approximate 1 calendar year
2. Trend Filter (Moving Average of Return)
To smooth volatility and avoid noise, the strategy applies a moving average to the 12M return:
Default length: 12 periods
Plotted as a white line on the indicator panel
This becomes the benchmark used for crossovers.
3. Trade Signals (Long / Short / Cash)
Trades are generated using a simple crossover mechanism:
Bullish Signal (Go Long)
When:
12M Return crosses ABOVE its MA
Action:
Close short (if any)
Enter long
Bearish Signal (Go Short or Go Flat)
When:
12M Return crosses BELOW its MA
Action:
If shorting is enabled → Enter short
If shorting is disabled → Exit position and go to cash
Shorting can be enabled or disabled with a single input switch.
4. Position Sizing
The strategy uses:
Percent of Equity position sizing
You can specify the percentage of your portfolio to allocate (default 100%).
No leverage is required, but the strategy supports it if your account settings allow.
5. Visual Signals
To improve clarity, the strategy marks signals directly on the indicator panel:
Green Up Arrows: return > MA
Red Down Arrows: return < MA
A status label shows the current mode:
LONG
SHORT
CASH
6. Backtest-Ready
This script is built as a full TradingView strategy, not just an indicator.
This means you can:
Run complete backtests
View performance metrics
Compare long-only vs long/short behavior
Adjust inputs to tune the system
It provides a clean, rule-driven interpretation of the classic absolute momentum approach.
Inspired By: Gary Antonacci – Dual Momentum Investing
This script reflects the absolute momentum side of Antonacci’s original research:
Uses 12-month momentum (the most statistically validated lookback)
Applies a trend-following overlay to control downside risk
Recreates the classic signal structure used in academic studies
It is a simplified, transparent version intended for practical use and educational clarity.
Disclaimer
This script is for educational and research purposes only.
Historical performance does not guarantee future results.
Always use proper risk management.
