Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Cryptobot
Quatro SMA Strategy [4h]Hello, I would like to present to you The "Quatro SMA" strategy
Strategy is based on four simple moving averages of different lengths and monitoring trading volume. The key idea is to identify strong market trends by comparing short-term moving averages with the long-term SMA. The strategy generates buy signals when all short-term SMAs are above the SMA(200) and the volume confirms the strength of the move. Similarly, sell signals are generated when all short-term SMAs are below the SMA(200), and the volume is sufficiently high.
The strategy manages risk by applying a stop loss and three different Take Profit levels (TP1, TP2, TP3), with varying percentages of the position closed at each level.
Each Take Profit level is triggered at a specific percentage gain, with the position being closed gradually depending on the achieved targets. The percentage of the position closed at each TP level is also defined by the user.
Indicators and Parameters:
Simple Moving Averages (SMA):
The script utilizes four simple moving averages with different lengths (4, 16, 32, 200). The first three SMAs (SMA1, SMA2, SMA3) are used to determine the trend direction, while the fourth SMA (with a length of 200) serves as a support/resistance line.
Volume:
The script monitors trading volume and checks if the current volume exceeds 2.5 times the average volume of the last 40 candles. High volume is considered as confirmation of trend strength.
Entry Conditions:
- Long Position: Triggered when SMA1 > SMA2 > SMA3, the closing price is above SMA(200), and the volume condition is met.
- Short Position: Triggered when SMA1 < SMA2 < SMA3, the closing price is below SMA(200), and the volume condition is met.
Exit Conditions:
- Long Position: Closed when SMA1 < SMA2 < SMA3 and the closing price is above SMA(200).
- Short Position: Closed when SMA1 > SMA2 > SMA3 and the closing price is below SMA(200).
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Crypto Punk [Bot] (Zeiierman)█ Overview
The Crypto Punk (Zeiierman) is a trading strategy designed for the dynamic and volatile cryptocurrency market. It utilizes algorithms that incorporate price action analysis and principles inspired by Geometric Brownian Motion (GBM). The bot's core functionality revolves around analyzing differences in high and low prices over various timeframes, estimating drift (trend) and volatility, and applying this information to generate trading signals.
█ How to use the Crypto Punk Bot
Utilize the Crypto Punk Bot as a technical analysis tool to enhance your trading strategy. The signals generated by the bot can serve as a confirmation of your existing approach to entering and exiting the market. Additionally, the backtest report provided by the bot is a valuable resource for identifying the optimal settings for the specific market and timeframe you are trading in.
One method is to use the bot's signals to confirm entry points around key support and resistance levels.
█ Key Features
Let's explain how the core features work in the strategy.
⚪ Strategy Filter
The strategy filter plays a vital role in the entries and exits. By setting this filter, the bot can identify higher or lower price points at which to execute trades. Opting for higher values will make the bot target more long-term extreme points, resulting in fewer but potentially more significant signals. Conversely, lower values focus on short-term extreme points, offering more frequent signals focusing on immediate market movements.
How is it calculated?
This filter identifies significant price points within a specified dynamic range by applying linear regression to the absolute deviation of the range, smoothing out fluctuations, and determining the trend direction. The algorithm then normalizes the data and searches for extreme points.
⚪ External AI filter
The external AI filter allows traders to incorporate two external sources as signal filters. This feature is particularly useful for refining their signal accuracy with additional data inputs.
External sources can include any indicator applied to your TradingView chart that produces a plot as an output, such as a moving average, RSI, supertrend, MACD, etc. Traders can use these indicators of their choice to set filters for screening signals within the strategy.
This approach offers traders increased flexibility to select filters that align with their trading style. For instance, one trader might prefer to take trades when the price is above a moving average, while another might opt for trades when the MACD is below the MACD signal line. These external filters enable traders to choose options that best fit their trading strategies. See the example below. Note that the input sources for the External AI filter can be any indicator applied to the chart, and the input source per se does not make this strategy unique. The AI filter takes the selected input source and applies our function to it. So, if a trader selects RSI as an input filter, RSI is not unique, but how the source is computed within the AI functions is.
How is it calculated?
Once the external filters are selected and enabled within the settings panel, our AI function is applied to enhance the filter's ability to execute trades, even when the set conditions of the filter are not met. For instance, if a trader wants to take trades only when the price is above a moving average, the AI filter can actually execute trades even if the price is below the moving average.
The filter works by combining k-nearest Neighbors (KNN) with Geometric Brownian Motion (GBM) involves first using GBM to model the historical price trends of an asset, identifying patterns of drift and volatility. KNN is then applied to compare the current market conditions with historical instances, identifying the closest matches based on similar market behaviors. By examining the drift values of these nearest historical neighbors, KNN predicts the current trend's direction.
The AI adaptability value is a setting that determines how flexible the AI algorithm is when applying the external AI filter. Setting the adaptability to 10 indicates minimal adaptability, suggesting that the bot will strictly adhere to the set filter criteria. On the other hand, a higher adaptability value grants the algorithm more leeway to "think outside the box," allowing it to consider signals that may not strictly meet the filter criteria but are deemed viable trading opportunities by the AI.
█ Examples
In this example, the RSI is used to filter out signals when the RSI is below the smoothing line, indicating that prices are declining.
Note that the external filter is specifically designed to work with either 'LONG ONLY' or 'SHORT ONLY' modes; it does not apply when the bot is set to trade on 'BOTH' modes. For 'LONG ONLY' positions, the filter criteria are met when source 1 is greater than source 2 (source 1 >= source 2). Conversely, for 'SHORT ONLY' positions, the filter criteria require source 1 to be less than source 2 (source 1 <= source 2).
Examples of Filter Usage:
Long Signals: To receive long signals when the closing price is higher than a moving average, set Source 1 to the 'close' price and Source 2 to a moving average value. This setup ensures that signals are generated only when the closing price exceeds the moving average, indicating a potential upward trend.
█ Settings
⚪ Set Timeframe
Choosing the correct entry and exit timeframes is crucial for the bot's performance. The general guideline is to select a timeframe that is higher than the one currently displayed on the trading chart but still relatively close in duration. For instance, if trading on a 1-minute chart, setting the bot's Timeframe to 5 minutes is advisable.
⚪ Entry
Traders have the flexibility to configure the bot according to their trading strategy, allowing them to choose whether the bot should engage in long positions only, short positions only or both. This customization ensures that the bot aligns with the trader's market outlook and risk tolerance.
⚪ Pyramiding
Pyramiding functionality is available to enhance the bot's trading strategy. If the current position experiences a drawdown by a specified number of points, the bot is programmed to add new positions to the existing one, potentially capitalizing on lower prices to average down the entry cost. To utilize this feature, access the settings panel, navigate to 'Properties,' and look for 'Pyramiding' to specify the number of times the bot can re-enter the market (e.g., setting it to 2 allows for two additional entries).
⚪ Risk Management
The bot incorporates several risk management methods, including a regular stop loss, trailing stop, and risk-reward-based stop loss and exit strategies. These features assist traders in managing their risk.
Stop Loss
Trailing Stop
⚪ Trading on specific days
This feature allows trading on specific days by setting which days of the week the bot can execute trades on. It enables traders to tailor their strategies according to market behavior on particular days.
⚪ Alerts
Alerts can be set for entry, exit, and risk management. This feature allows traders to automate their trading strategy, ensuring timely actions are taken according to predefined criteria.
█ How is Crypto Punk calculated?
The Crypto Punk Bot is a trading bot that utilizes a combination of price action analysis and elements inspired by Geometric Brownian Motion (GBM) to generate buy and sell signals for cryptocurrencies. The bot focuses on analyzing the difference between high and low prices over various timeframes, alongside estimates of drift (trend) and volatility derived from GBM principles.
Timeframe Analysis for Price Action
The bot examines multiple timeframes (e.g., daily, weekly) to identify the range between the highest and lowest prices within each period. This range analysis helps in understanding market volatility and the potential for significant price movements. The algorithm calculates the trading range by applying maximum and minimum functions to the set of prices over your selected timeframe. It then subtracts these values to determine the range's width. This method offers a quantitative measure of the asset's price volatility for the specified period.
Estimating Drift (Trend)
The bot estimates the drift component, which reflects the underlying trend or expected return of the cryptocurrency. The algorithm does this by estimating the drift (trend) using Geometric Brownian Motion (GBM), which involves determining an asset's average rate of return over time, reflecting the asset's expected direction of movement.
Estimating Volatility
Volatility is estimated by calculating the standard deviation of the logarithmic returns of the cryptocurrency's price over the same timeframe used for the drift calculation. Geometric Brownian Motion (GBM) involves measuring the extent of variation or dispersion in the returns of an asset over time. In the context of GBM, volatility quantifies the degree to which the price of an asset is expected to fluctuate around its drift.
Combining Drift and Volatility for Signal Generation
The bot uses the calculated drift and volatility to understand the current market conditions. A higher drift coupled with manageable volatility may indicate a strong upward trend, suggesting a potential buy signal. Conversely, a low or negative drift with increasing volatility might suggest a weakening market, triggering a sell signal.
█ Strategy Properties
This script backtest is done on the 1 hour chart Bitcoin, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Commission: 0.05 %
Slippage: 500 ticks
Stop Loss: Risk Reward set to 1
These parameters are set to provide an accurate representation of the backtesting environment. It's important to recognize that default settings may vary for several reasons outlined below:
Order Size: The standard is set at one contract to facilitate compatibility with a wide range of instruments, including futures.
Commission: This fee is subject to fluctuation based on the specific market and financial instrument, and as such, there isn't a standard rate that will consistently yield accurate outcomes.
We advise users to customize the Script Properties in the strategy settings to match their personal trading accounts and preferred platforms. This adjustment is crucial for obtaining practical insights from the deployed strategies.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Wunder Volume botWunder Volume Bot
1. Wunder Volume bot is a non-indicator strategy that is based on the Volume analysis.
2. For the entry we will use the volume multiplier to detect the abnormal volume activity. For example, the volume should be 2 times the average. You can set your own preferences for each asset. It is recommended to use a higher multiplier and multiple assets to run multiple different bots in order to diversify your approach.
3. A function for calculating risk on the portfolio (your deposit) has been added to the Wunder Volume bot script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example, if your deposit is $1000 and you set the risk to 1%, with a Stop Loss of 5%, the entry volume will be $200. The loss at SL will be $10.10, which is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
Wunder Trend Reversal botWunder Trend Reversal bot
1. Wunder Trend Reversal Bot - this has only one goal to find a reversal of the trend.
2. The strategy determines, based on the specified value for the filter, a market reversal based on the price actions of the previous bars.
3. A short EMA is used to filter false signals after the reversal signal was received. Crossing the EMA and changing its direction confirms the trend change.
4. There are 2 ways to calculate stop loss and take profit. You can choose one of them:
- Classic stop loss and take profit in a fixed percentage
- ATR stop loss and take pro
5. ATR uses risk reward (R:R) to calculate take profit. The script calculates the risk-reward based on a certain stop loss level and uses it to calculate the take profit
6. A function for calculating risk on the portfolio (your deposit) has been added to the script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example. Deposit - $1000, you set the risk to 1%. SL 5%. Entry volume will be $200. The loss at SL will be $10.10$ this is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contracts” option.
Wunder Keltner botWunder Keltner bot
1. Wunder Keltner bot is based on the breakout of the Keltner channel. For calculation, 2 channels are used, one for long trades, and the other for short trades. The division into 2 channels is used for more accurate entry calculations depending on trend directions.
2. The ADX indicator is used to filter signals and determine the trend strength. ADX determines the strength of the trend and confirms the entry into the strategy if the value is greater than the level indicated in the settings.
3. There are 3 ways to calculate Stop Loss and Take Profit. You can choose one of them:
Classic Stop Loss and Take Profit in a fixed percentage
ATR Stop Loss
Keltner. Stop Loss, which is set on the opposite Keltner’s Channel Band from Keltner breakout.
4. ATR and Keltner use Risk Reward (R:R) to calculate Take Profit. The script calculates Risk Reward based on the determined Stop loss level and uses the ration to calculate Take Profit.
5. A function for calculating risk on the portfolio (your deposit) has been added to the script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example. Deposit - $1000, you set the risk to 1%. SL 5%. Entry volume will be $200. The loss at SL will be $10.10$ this is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
Wunder DCA BotThe bot is based on the DCA system.
1. DCA is the investment method in which you buy a certain portion of the asset after the determined price deviation.
2. For entry, we evaluate the maximum and minimum levels for a given period that you can adjust in the script. The bot enters when price rebound from the specified levels.
3. For the exit, the bot will use the take profit percentage that you will specify in settings.
It is also possible to choose how the take profit is calculated either from the average entry price or from the entry order (first order).
4. DCA uses the following settings:
- Base order Volume: Volume of your first order on entry signal
- Subsequent orders volume: The volume of all subsequent orders except the first
- DCA orders count: This parameter will determine how many entries your overall strategy will have. For example: If you will put 3, that will mean that including your initial position you will have 2 additional orders.
- DCA order price deviation:
This is the value in % which determines the deviation of the additional entries from the entry price. Example: If you go long and the price of the asset is 100$ and you put an order price deviation of 1% that will mean that the first additional entry will occur when the price will drop by 1%, and the second entry will be triggered when the overall price will drop by 2% (as the interval between the first and the second additional entry will be 1%).
- DCA Order Volume Multiplier:
This parameter will determine the amount that you put into each additional position. If this parameter is equal to 1 that means that each additional entry will be equal to the initial amount. The extra volume will be added to your position from the second DCA entry. Example: Your initial position was 10$ and your Volume Multiplier is set to 2. When you reach your 1st DCA target your additional order will have the same volume of 10$. When you reach your 2nd DCA target your additional order will be 20$ (previous position volume * multiplier). Your 3rd DCA target will place the order of 40$.
- DCA order price Deviation Multiplier:
This value will increase the price deviation between each additional entry. It is calculated as the price deviation multiplied by the deviation multiplier. For example: if you enter long at the price 100$ and have a price deviation of 1% with the price deviation multiplier of 2 that will mean that the first additional entry will occur when the price will drop to 99$ however the second will occur when the price will go to 97$. The third additional position will be entered at 94$
5. For full automation of the bot, you should set your comments to the input in the bot settings in the "LONG" and "SHORT" fields. You also need to create an alert signal and set a Webhook to send signals.
IMPORTANT!!!
1. Position calculation should take into account several factors: your deposit, leverage, the number of DCA orders, the distance to the last DCA order;
2. When choosing leverage, it is important to correctly calculate the possible drawdown. If you set a high leverage value, then liquidation awaits and the bot will not be able to take profits and will exit the position ahead of time;
3. The size of the position must be determined in accordance with all risks and take into account the size of your deposit;
4. This DCA Bot is able to earn consistently with the correct calculated money management.
OnePunch Algo Momentum Indicator V1This is another Plugin from One Punch Algo Team. We call it OnePunch Algo Momentum Indicator V1.
Basic Use:
One Punch Algo Momentum Indicator plugin is used for momentum stocks and high volatility crypto. It provide signals based on Simple Moving Average, Volume, Support & Resistance Lines.
SIGNALS/ALERTS
Buy Signal: Purple Color uptrend icon gives you a signal of an up-trending movement or we call it momentum movement. This signal basically happen when a stock land in a high volatility zone. We use in-build systems such as SMA, Support and Resistance and Trends to come up with the Buy Signal.
Sell Signal: Gray Color downtrend icon gives you a signal of a downtrend movement.
Other Lines Shown in the Diagram:
Red Line is the 200 Day Simple Moving Average (SMA)
Green Line is the 50 Day Simple Moving Average (SMA)
Strategy Tester
Always make sure to use the strategy tester to test how historically our Algo has performed in different time frames. One Punch Algo Momentum Indicator provide the ability to backtest based on certain time periods. This allows you to backtest our Algo vs some other Algo to find which performed well for the given time period, you if you want to see buy and hold performance better than the use of an Algo. This is a strong tool to use for your analysis of a stock or crypto.
What are the timeframes where it is most effective?
Different Stocks or Crypto perform differently with One Punch Algo Momentum Indicator. Please make sure to backtest a stock or crypto before you use the strategy.
Short Term/Day Trading Setup
For Short Term or Day Trade: 1min, 5min, 15min & 30min candlesticks works really well.
Also 3min, 5min, 7min and 15min works as well
Mid Term Trading Setup
For Mid-term traders: 30min, 1hr,2hr, and 4hr setup works really well.
For Long Term Trading Setup
For long term traders: 4hr, 1D, 1Week and 1Month Setup works well.
Best used with Heikin Ashi or Candlestick charts.
DISCLAIMER: Stocks and options trading involves substantial RISK of LOSS and is NOT suitable for every investor. The valuation of stocks and options may fluctuate, and, as a result, clients may lose more than their original investment. If the market moves against you, you may sustain a total loss greater than the amount you deposited into your account. You are responsible for all the risks and financial resources you use and for the chosen trading system. You should not engage in trading unless you fully understand the nature of the transactions you are entering into and the extent of your exposure to loss. If you do not fully understand these risks, you must seek independent advice from your financial advisor.
All trading strategies are used at your own risk. And OnePunch ALGO Developer, Youtuber or the channel does NOT take any responsibility for your losses using any of the advice or suggestions or strategies are shown/said in any of OnePunch ALGO Youtuber or the channel videos.
ETH/USD 15m [iTradebot]1. General
2. Additional information
3. Access
1. This is a script for crypto trading strategies, based on following trends with moving averages.
A fast moving average and a slower getting crosschecked with MACD for buying/selling signals, those signals get crosschecked by 5 different factors, like the MACD or controlling average.
Only if all requirements will be met, the script expects the trend to change and sends an according signal.
This strategy is not made for multiple entries and keeps a position open until an opposite signal gets triggered.
It was built with ETH/USD 15min chart in mind, but can be used on any other chart, though you will have to find a different combination in inputs, to make it work with other pairs or timeframes.
Fast average: The faster of the two signal moving averages.
Slow average: The slower of the two signal moving averages.
Trend strength: Determines the crosscheck with the MACD.
Control length: Sets the period length for the control average (1=1bar, 300=300bars)
Inputs used here are:
Fast average: 5
Slow average: 19
Trend strength: 4
Control length: 306
Start capital: 1000
Trade equity: 100%
Commission: 0.036% (Binance)
Result 2020-06-11 until 2021-01-07
Net Profit: 717.56%
Percent Profitable: 54.17%
Max Drawdown: 8.79%
Profit Factor: 6.523
2. There are many combinations with good net profit outcomes, but make sure to also keep a low "Max Drawdown", to lower the risk substantially.
The combination we used, gives slightly less profit than other combinations, but also lowers the max drawdown from 20% to 9%.
In general in trading with crypto we advice to only use this strategy with Bitcoin or Ethereum , due to their high value and "stable" movements, compared to other cryptocurrencies.
The strategy is using 100% equity each trade, so make sure to have your capital management in place on the account.
To be specific, DONT put all your capital into this one strategy, but only part of it, according to your capital management.
Control lengths around 150 or 300 tend to give good combinations with the other 3 inputs. (on the 15min chart)
3. You can test this strategy 14 days for free and get access for up to 1 year on our website.
14 day free trial only requires Tradingview user name and e-mail.
Click on the link in our signature below.
Keltner Channel [LINKUSDT] 1HThis is a long-only strategy tested on LINK/USDT, 1 hour bar, from Feb 2019. The entry is determined by the breakout of upper Keltnel Channel and when the +DI is higher than 32. Instead of a fixed stop-loss from the original script , I change the exit to the middle band of the Keltnel Channel. 1st profit target will close 20% of the position. 2nd profit target will close 30% of the position. While the remaining 50% position will be closed when the price closes below the middle band of the Keltnel Channel, to take advantage of big trend. All parameters are adjustable. I added another option to enable or disable the ribbon trend filter.
My thoughts: For the same period, LINK appreciated 3000%. So I guess most in and out strategies couldn’t beat a buy and hold strategy during this period. But this doesn’t mean that this strategy is not feasible as each strategy is designed to only take advantage of a certain pattern or behavior of the market. Also, short term strategies allow you to use leverage and hence enable you to use you capital efficiently. Commission is set to 0.1%, taking account of the slippage.
Suggestion: Please perform walk forward analysis before you use real money for trading. Parameters need to be adjusted from time to time depends on your analysis. Can try using ATR for profit targets as over a longer term, the volatility might drop hence a high fixed % profit targets might not be realistic.
Any suggestions are welcome!
