Shorting when Bollinger Band Above Price with RSI (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to reverse. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70.
EXIT
The trade is closed when the RSI is less than 70
The lower standard deviation of the Bollinger Band is less than the closing price.
This strategy was backtested from the beginning of 2022 to capture how this strategy would perform in a bear market.
The strategy assumes each order to trade 70% of the available capital to make the results more realistic. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume.
Oscillators
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Negroni MA & RSI Strategy, plus trade entry and SL/TP optionsI will start with the context, and some things to think about when using a strategy tool to back-test ideas.
CONTEXT
FIRST: This is derived from other people's work, but I honestly hadn't found a mixed indicator MA strategy tool that does what this now does. If it is out there, apologies!!
This tool can help back-test various MA trends (SMA, EMA, HMA, VWMA); as well as factoring in RSI levels (or not); and can factor in a fixed HTF MA (or not). You can apply a 'retest entry' or a 'breakout entry', and you can also apply various risk mgt for SL/TP orders: 1) No SL/TP; or 2) a fixed %, or 3) dynamic ATR multipliers.
Find below, some details explaining what this tool is attempting to do.
Thank you, tack, salute!
THINGS TO REVIEW (it is not just about 'profitability'!!)
Whilst discretion is always highly encouraged as a trader, and a 100% indicator-driven strategy is VERY unlikely to yield sustainable results going forward, at the very least back-testing your strategies can help provide some guidance, not just on win rate Vs profit factor, but other things including:
a) Trade frequency: if a strategy has an 75% win rate and profit factor of 4, with all your parameters and confluence checks, but only triggers 3 trades every 5 years, is that realistically implementable to your trading situation if you have a $10,000 account?
b) Trade entry type: is it consistently better to wait for a retest of an 'MA zone', or is it better to market buy/sell on breakout of the 'MA zone'?
c) Risk management (SL/TP): is it consistently better to have a fixed static % for SL/TP ("I always place my stops 2% away, whether it is EURUSD or BTCUSDT"), or would you be better placed to try using an ATR multiplier of the respective assets?
d) Moving average type: is your old faithful 100 EMA really serving you well, or is the classic SMA more reliable, or how about the HMA, or the VWMA? Is the 100/200 cross holding up, or do you need something more sensitive? Is there any significant difference between a 10 EMA/20 EMA trend zone compared to a 13 EMA /25 EMA zone?
e) Confluence: Do added confluence checks (RSI, higher timeframe MA) actually improve profitability? But even if they do, is at the cost of cutting too many trades?
INPUTS AND PARAMETERS
Choice 1) Entry Strategy: Retest or Breakout - You can select both!
[ ]:
a) RETEST entry strat: price crosses UNDER FastMA INTO the 'MA trend zone'.
b) BREAKOUT entry strat: price crosses OVER FastMA OUT the 'MA trend zone'.
Choice 2) Risk Management (SL and TP) - You can select more than 1 strategy!
a) No SL/TP: Long trades are closed when the LOW crosses back UNDER the fastMA again, and shorts are closed when the HIGH crosses back OVER the fastMA again.
b) Static % SL/TP: Your SL/TP will be a fixed % away from avg. position price... WARNING: You should change this for various asset classes; FX vol is not the same as crypto altcoin vol!
c) Dynamic ATR SL/TP: Your SL/TP is a multiple of your selected ATR range (default is 50, see 'info' when you select ATR range). ATR accounts for the change in vol of different asset classes somewhat, HOWEVER... you should probably still not have the same multiplier trading S&P500 as you would trading crypto altcoins!
Then select your preferred parameters: EMA, SMA, HMA, VWMA, etc. You can mix and match, and most options have a info/tooltip guide.
RSI note: If you don't care for RSI levels, then set buy signal at 1... i.e always buys! Similarly set sell signal at 99.
ATR note: standard ATR length is usually 14, however... your SL/TP will move POST entry, and can tighten or widen your initial SL/TP... for better AND usually for worse! Go find a trade (strat 3) on the chart, look at the SL/TP lines, now change the number to 5, you'll see.
Fixed HTF MA note: If you don't care for HTF MA confluence, just change the timeframe/options to match the 'Slow MA' options you've chosen.
Divergence for Many [Dimkud - v5]Strategy is based on "Divergence for Many Indicators v4 ST" strategy by CannyTolany01
which is based on "Divergence for Many Indicator" indicator by LonesomeTheBlue
This strategy is searching for divergences on 18 indicators which you can select and optimise one by one.
Additionally you can connect any other External Indicator value. (just add this indicator the the chart and select option in settings)
To the original indicator/strategy I have added 9 additional indicators:
( Money Flow Index, Williams_Vix, Stochastic RSI , SMI Ergodic Oscillator, Volume Weighted MACD , Bull Bear Power, Balance of Power , Relative Volatility Index , Logistic Settings).
Converted strategy to v5 of Pine Script.
Added Static SL/TP in percents (%).
Added filters to filter enters:
1. Volume Weighted MACD - Multi-TimeFrame Filter
(It checks for histogram to falling or rising for a set periods of bars)
2. Money Flow Index - Multi-TimeFrame Filter
(It checks if MFI Oscillator is in the set diapason.
Also It checks if MFI is falling or rising for a set periods of bars )
3. ATR filter
(check changes in fast ATR to slow ATR )
Strategy shows good backtest results on many crypto tokens on 45m - 1h periods. (with parameters optimisation for every indicator)
To find best parameters - you can enable indicators one-by one, and optimise best parameters for each of them.
Then enable all indicators with successful results.
Optimise SL/TP.
Then try to enable and optimise filters (channels etc.)
The better is to optimise parameters separately for Short and Long trading. And run two separate bots (in settings enable only Long or only Short.)
Updates:
- Added visualisation for open trades (SL/TP)
- Added Volatility filter by ATR with many options for tests.
- Fixed some small bugs.
- Added second RSI filter (you can use two RSIs with different TF or settings)
- Updated ATR volatility and MFI filter. Removed non-effective options
- Added CCI filter
- Added option to Enable/Disable visualisation of TP/SL on chart
- Fixed one small quick bug. ("ATR filter short" was not working)
- Added Super Trend filter
- Added Momentum filter
- Added Volume Filter
- All "request.security" MultiTimeFrame calls changed to 100% non-repait function "f_security()"
Rsi strategy for BTC with (Rsi SPX)
I hope this strategy is just an idea and a starting point, I use the correlation of the Sp500 with the Btc, this does not mean that this correlation will exist forever!. I love Trading view and I'm learning to program, I find correlations very interesting and here is a simple strategy.
This is a trading strategy script written in Pine Script language for use in TradingView. Here is a brief overview of the strategy:
The script uses the RSI (Relative Strength Index) technical indicator with a period of 14 on two securities: the S&P 500 (SPX) and the symbol corresponding to the current chart (presumably Bitcoin, based on the variable name "Btc_1h_fixed"). The RSI is plotted on the chart for both securities.
The script then sets up two trading conditions using the RSI values:
A long entry condition: when the RSI for the current symbol crosses above the RSI for the S&P 500, a long trade is opened using the "strategy.entry" function.
A short entry condition: when the RSI for the current symbol crosses below the RSI for the S&P 500, a short trade is opened using the "strategy.entry" function.
The script also includes a take profit input parameter that allows the user to set a percentage profit target for closing the trade. The take profit is set using the "strategy.exit" function.
Overall, the strategy aims to take advantage of divergences in RSI values between the current symbol and the S&P 500 by opening long or short trades accordingly. The take profit parameter allows the user to set a specific profit target for each trade. However, the script does not include any stop loss or risk management features, which should be considered when implementing the strategy in a real trading scenario.
MVRV Z Score and MVRV Free Float Z-ScoreIMPORTANT: This script needs as much historic data as possible. Please run it on INDEX:BTCUSD , BNC:BLX or another chart of sufficient length.
MVRV
The MVRV (Market Value to Realised Value Ratio) simply divides bitcoins market cap by bitcoins realized market cap. This was previously impossible on Tradingview but has now been made possible thanks to Coinmetrics providing us with the realized market cap data.
In the free float version, the free float market cap is used instead of the regular market cap.
Z-Score
The MVRV Z-score divides the difference between Market cap and realized market cap by the historic standard deviation of the market cap.
Historically, this has been insanely accurate at detecting bitcoin tops and bottoms:
A Z-Score above 7 means bitcoin is vastly overpriced and at a local top.
A Z-Score below 0.1 means bitcoin is underpriced and at a local bottom.
In the free float version, the free float market cap is used instead of the regular market cap.
The Z-Score, also known as the standard score is hugely popular in a wide range of mathematical and statistical fields and is usually used to measure the number of standard deviations by which the value of a raw score is above or below the mean value of what is being observed or measured.
Credits
MVRV Z Score initially created by aweandwonder
MVRV initially created by Murad Mahmudov and David Puell
Kimchi Premium StrategyThis strategy is based on the Korea Premium, also known as the “Kimchi Premium,” which indicates how expensive or cheap the price of Bitcoin in Korean Won on a Bitcoin exchange in South Korea is relative to the price of Bitcoin being traded in USD or Tether. Inverse Kimchi Premium RSI was newly defined to create a strategy with Kimchi Premium. Assuming that the larger the kimchi premium, the greater the individual's purchasing power. In this case, if the Inverse Kimchi Premium RSI falls and closes the candle below the bear level, a short is triggered. Long is the opposite.
This strategy defaults to a combination of the traditional RSI and the Inverse Kimchi Premium RSI. If the user wishes to unlock the Inverse Kimchi Premium RSI combination and only use it as a traditional RSI strategy, the following settings can be used.
Use Combination of Inverse Kimchi Premium RSI: Uncheck
Resolution: Chart (4hr Candle)
Source: Close
Length of RSI: 14
Bull Level: 74
Bear Level: 25
__________________________________________________________________________________
김치프리미엄(김프) 전략은 달러 혹은 테더로 거래되고 있는 비트코인 가격 대비 한국에 있는 비트코인 거래소의 비트코인 원화 가격이 얼마나 비싸고 싼 지를 나타내는 코리아 프리미엄, 일명 "김치 프리미엄" 지표를 기반으로 만들어졌습니다. 김치 프리미엄을 가지고 전략을 만들기위해 Inverse Kimchi Premium RSI를 새롭게 정의하였습니다. 김치 프리미엄이 커질수록 개인의 매수세가 커진다고 가정하고, 이 경우 Inverse Kimchi Premium RSI이 하락하여 Bear Level 아래에서 캔들 마감을 하면 Short을 트리거 합니다. Long은 그 반대입니다.
이 전략은 전통적인 RSI와 Inverse Kimchi Premium RSI을 조합하여 기본값을 설정하였습니다. 유저가 원한다면 Inverse Kimchi Premium RSI의 조합을 해제하고 전통적인 RSI 전략으로만 사용하려면 아래 다음의 설정값을 사용할 수 있습니다.
Use Combination of Inverse Kimchi Premium RSI: 체크 해제
Resolution: Chart (4hr Candle)
Source: Close
Length of RSI: 14
Bull Level: 74
Bear Level: 25
Athena Momentum Squeeze - Short, Lean, and Mean This is a very profitable strategy focusing on 15 minute intervals on the Micro Nasdaq Futures contracts. CME_MINI:MNQH2023
As this contract only keeps positions for on average about an hour risk is managed. At a profit factor of 3.382 with a max drawdown of $123 from January 1st to February 15. Looking back to Dec 2019 still maintains a profit factor of 1.3.
See backtesting: www.screencast.com
2019 backtesting: www.screencast.com
Based on the classic Lazy Bear Oscillator Squeeze with a number of modifications from ADX, MAs and adding fibonacci levels.
We like keeping strategies simple yet powerful, no completely where you can't understand your own trades.
Our team is always modifying and improving the strategy. Always open to collaborating on improving as there is no perfect strategy. www.screencast.com
Exponential Stochastic Strategywhat is Exponential Stochastic?
it is a modified version of the stochastic indicator. This strategy does not include pyramiding, repaint, trailing stop or take profit.
what it does?
It contains an extra input in addition to the stochastic indicator. Thanks to this input, different exponential weights can be given to the outputs and the indicator can be made more sensitive or insensitive. The strategy buys when the indicator leaves the overbought zone, sells when it leaves the oversold zone and always stays in the trade.
how it does it?
it uses this formula: i.hizliresim.com
Thanks to this formula, even if the weights given to the outputs change, the indicator always continues to take a value between 0 and 100.
how to use it ?
With the input named "exp", you can change the sensitivity of the indicator and develop different strategies. other inputs are the same as the stochastic indicator. Increasing the exp value causes the indicator to signal less, decreasing it makes it much more sensitive.
TradePro's 2 EMA + Stoch RSI + ATR StrategySaw TradePro's "NEW BEST HIGHEST PROFITING STRATEGY WITH CRAZY RESULTS - 2 EMA+ Stochastic RSI+ ATR", and was curious on the back testing results. This strategy is an attempt to recreate it.
This strategy uses 50 / 200 EMAs, Stochastic RSI and ATR.
Long Entry Criteria:
- 50 EMA > 200 EMA
- Price closes below 50 EMA
- Stochastic RSI has gone into oversold < 20
- Stochastic RSI crosses up while making higher low from previous cross up
Short Entry Criteria:
- 50 EMA < 200 EMA
- Price closes above 50 EMA
- Stochastic RSI has gone into overbought > 80
- Stochastic RSI crosses down while making lower high from previous cross down
Stop-loss is set to ATR stop-loss
Take Profit is 2x the risk
All parameters are configurable.
Enjoy~~
Fair Value Strategy UltimateThis is a strategy using an index's (SPX, NDX, RUT) Fair Value derived from Net Liquidity.
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of and Index using Net Liquidity looks like this: net_liquidity/1000000000/scalar - subtractor
The Index Fair Value is then subtracted from the Index value which creates an oscillating diff value.
When diff is greater than the overbought threshold, Index is considered overbought and we go short/sell.
When diff is less than the oversold signal, Index is considered oversold and we cover/buy.
The net liquidity values I calculate outside of TradingView. If you'd like the strategy to work for future dates, you'll need to update the reference to my NetLiquidityLibrary , which I update daily.
Parameters:
Index: SPX, NDX, RUT
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Scalar (float)
Subtractor (int)
Overbought Threshold (int)
Oversold Threshold (int)
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
Optimal Parameters:
I've optimized the parameters for each index using the python backtesting library and they are as follows =>
SPX
Scalar: 1.1
Subtractor: 1425
OB Threshold: 0
OS Threshold: -175
NDX
Scalar: 0.5
Subtractor: 250
OB Threshold: 0
OS Threshold: -25
RUT
Scalar: 3.2
Subtractor: 50
OB Threshold: 25
OS Threshold: -25
Strategy Myth-Busting #5 - POKI+GTREND+ADX - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our fifth one we are automating is one of the strategies from "The Best 3 Buy And Sell Indicators on Tradingview + Confirmation Indicators ( The Golden Ones ))" from "Online Trading Signals (Scalping Channel)". No formal backtesting was done by them and resuructo messaged me asking if we could validate their claims.
Originally, we mimic verbatim the settings Online Trading Signals was using however weren't getting promising results. So before we stopped there we thought we might want to see if this could be improved on. So we adjusted the Renko Assignment modifier from ATR to Traditional and adjusted the value to be higher from 30 to 47. We also decided to try adding another signal confirmation to eliminate some of the ranged market conditions so we choose our favorite, ADX . Also, given we are using this on a higher time-frame we adjusted the G-Channel Trend detection source from close to OHLC4 to get better average price action indication and more accurate trend direction.
This strategy uses a combination of 2 open-source public indicators:
poki buy and sell Take profit and stop loss by RafaelZioni
G-Channel Trend Detection by jaggedsoft
Trading Rules
15m - 4h timeframe. We saw best results at the recommended 1 hour timeframe.
Long Entry:
When POKI triggers a buy signal
When G-Channel Trend Detection is in an upward trend (Green)
ADX Is above 25
Short Entry:
When POKI triggers a sell signal
When G-Channel Trend Detection is in an downward trend (red)
ADX Is above 25
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
PSAR BBPT ZLSMA BTC 1minLong entry:
PSAR gives buy signal
BBPT prints green histogram
ZLSMA is below the price
ZLSMA has uptrend
SL is smaller than the max SL
Optional Sessions and EMA filters
Short entry
PSAR gives sell signal
BBPT prints red histogram
ZLSMA is above the price
ZLSMA has downtrend
SL is smaller than the max SL
Optional Sessions and EMA filters
SL:
Placed below ZLSMA + offset on long
Placed above ZLSMA + offset on short
TP1:
1x the SL by default
Takes no profit by default, 50% is also a good setting
TP2:
2x the SL by default
Take out all remaining position size.
If price reaches TP1, the SL is set to the entry price.
Bull Trend Filtered StochRSI (BTFS)Ride Bull Trends Via Stochastic with Special Rules for Heavy Bullish Bias
TLDR: Long Only Trend Indicator Where you are always entered Long if the stochastic is over the lower band line and the price is above the Donchian Chanel high. Exit when Stochastic RSI is below the lower band.
Indicators:
Filter = Trend/Bullish indicator is Donchian of ema(high) this is set as the highest ema(high, 6) in the last 30 candles. this can be adjusted to fit the market as desired.
**indicator prints green background when the filter condition is satisfied***
Entry Exit = enter when the Stoch RSI is above the given lower trend band. This value is set at 35 but can be adjusted according to risk tolerance and market conditions.
Logic:
this indicator allows a trader to be present during bullish/parabolic trends by only triggering if the close is > than the highest 6 candle average high over the last 30 candles. This filter requires the market to be in a generally bullish posture. If the market is in this condition the stochastic RSI indicator value offers a good gauge of price action and only goes significantly down if price trends below the average range of the rsi period. This filters out noise and keeps a trader from over trading on inconsequential corrections while responding fairly quickly to changes in general trend direction. the response is fast enough to produce an unprofitable amount of false signals if the bull market filter is not implemented. However when used in combination the signals return desirable results in bull trending markets.
Hope this Helps. Happy Trades.
-Snarky Puppy
Ichimoku Cloud and ADX with Trailing Stop Loss (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
DMI is simple to interpret. When +DI > - DI, it means the price is trending up. On the other hand, when -DI > +DI, the trend is weak or moving on the downside. The ADX does not give an indication of the direction but about the strength of the trend.
Typically values of ADX above 25 mean that the trend is steeply moving up or down, based on the -DI and +DI positioning. This script aims to capture swings in the DMI, and thus, in the trend of the asset, using a contrarian approach.
Trading on high values of ADX, the strategy tries to spot extremely oversold and overbought conditions. Values of ADX above 45 may suggest that the trend has overextended and is maybe about to reverse.
This strategy combines the Ichimoku Cloud with the ADX indicator to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
-DI is greater than +DI
ADX is greater than 45
Close Position:
3% increase trailing
3% decrease trailing
The script is backtested from December 2022 and provides good returns.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Super 8 - 30M BTCWelcome to Super 8, the ultimate automatic trading script for Pine!
This bad boy is designed to go both long and short, and it's equipped with all the tools you need to maximize your profits. Whether you're looking to take profit, set a trailing stop, or protect yourself with a stop loss, Super 8 has you covered.
But that's not all! Super 8 is also loaded with 8 powerful indicators to help you make informed decisions. We've got the EMA, ADX, SAR, MACD, VOLUME, BOLLINGER BANDS, DONCHIAN, and ATR all working together to give you the best possible trading experience.
And if you want to take it to the next level, Super 8 also has a feature that lets you use stepped entries in normal mode or incremental 1,2,3,... to improve your average price. Plus, if you're using trailing stop, you can activate the Backtest precision to use lower timeframes.
But what's in a name? Super 8 is called that because it's just that... super! It's tailored specifically for the OKX:BTCUSDT.P pair, so you know you're getting the best possible results. it's highly adjustable and can be used with any other pair. So no matter what market you're trading in, Super 8 has got you covered.
So if you want to level up your trading game, give Super 8 a try. You won't be disappointed.
Certain Risks of Live Algorithmic Trading:
Backtesting Cannot Assure Actual Results.
The relevant market might fail or behave unexpectedly.
Your broker may experience failures in its infrastructure, fail to execute your orders in a correct or timely fashion or reject your orders.
The system you use for generating trading orders, communicating those orders to your broker, and receiving queries and trading results from your broker may fail.
Time lag at various point in live trading might cause unexpected behavior.
The systems of third parties in addition to those of the provider from which we obtain various services, your broker, and the applicable securities market may fail or malfunction.
ATR_RSI_Strategy v2 with no repaint [liwei666]🎲 Overview
🎯 this is a optimized version based on ATR_RSI_Strategy with no-repaint.
Sharpe ratio: 1.4, trade times: 116 ,
trade symbol: BINANCE:BTCUSDTPERP 15M
you can get same backtesting result with the correct settings.
🎲 Strategy Logic
🎯 the core logic is quite simple, use ATR and RSI and SMA
1. when price is in high volatility ( atr_value > atr_ma);
2. wait for a break signal (rsi_value > rsi_buy or rsi_value < rsi_sell);
3. entry Long or Short,use trailing stop-loss to max security and percent TP to keep profit.
🎲 Settings
🎯 there are 7 input properties in script, but I only finetune 4 of them ( bold field below ),
you may change other parameter to get better result by yourself.
atr_length: length to get atr value
atr_ma_length : length of smoothing atr value
atr_ma_norm_min : atr_ma normalized min value, filter high volatility ranges
atr_ma_norm_max : atr_ma normalized max value, filter high volatility ranges
rsi_length : length to get rsi value
rsi_entry: 50 +/- rsi_entry to get entry threshold
trailing_percent: trailing stop-loss percent
🎲 Usage
🎯 the commission set to 0.05% , part of exchange the commission is less than 0.05% in reality,
but I will still use 0.05% in my next script.
🎯 this script use 50% of equity to size positions follow general script position,
you can adjust the value to fix size or 100% of equity to compare result with other strategy,
but I still suggest you use 5-10% of equity for each strategy in reality.
🎯any questions please comment below. if there are any words violate House Rule, please tell me below and i will revise immediately
don't want be hiddened again 😂😂
Additionally, I plan to publish 20 profitable strategies in 2023;
let‘s witness it together!
Hope this strategy will be usefull for you :)
enjoy! 🚀🚀🚀
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.
RSI and MA with Trailing Stop Loss and Take Profit (by Coinrule)The relative strength index is a momentum indicator used in technical analysis. It measures the speed and magnitude of a coin's recent price changes to evaluate overvalued or undervalued conditions in the price of that coin. The RSI is displayed as an oscillator (a line graph essentially) on a scale of zero to 100. When the RSI reaches oversold levels, it can provide a signal to go long. When the RSI reaches overbought levels, it can mark a good exit point or alternatively, an entry for a short position. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A moving average (MA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. Essentially it is used to help smooth out price data by creating a constantly updated average price.
The Strategy enters and closes trades when the following conditions are met:
Entry Conditions:
RSI is greater than 50
MA9 is greater than MA50
RSI increases by 5
Exit Conditions:
Price increases by 1% trailing
Price decreases by 2% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
M0PB (Momentum Pullback)Long/short strategy that identifies extreme readings on the rsi as a *momentum signal*, unlike most RSI strategies the script will look to buy or sell the first pullback in the direction of the extreme RSI reading.
Enters positions on the first pullback to the 5ema(low)/ 5ema(high) and exits at rolling 12 bar high/ low. The rolling high/ low feature means that if the price enters into a prolonged consolidation the profit target will begin to reduce with each new bar. The best trades tend to work within 2-6 bars.
Built for use on 5 min intervals on FX, Indexes, and Crypto. Lower than 5 minute time frames tend to be noisier and mean more commissions and a higher risk of slippage so the suggested timeframe is 5 mins.
Hard stop is X ATR (users can experiment with this) from the position entry price. This can be adjusted in user inputs.
There is a lot of slack left in entries and exits but the overall strategy is fairly robust across timeframes and markets and has between 60%-70% win rate with larger winners.
Signals that occur from economic news volatility are best avoided.
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.
RSI Divergence Strategywhat is "RSI Divergence Strategy"?
it is a RSI strategy based this indicator:
what it does?
it gives buy or sell signals according to RSI Divergences. it also has different variables such as "take profit", "stop loss" and trailing stop loss.
how it does it?
it uses the "RSI Divergence" indicator to give signal. For detailed information on how it works, you can visit the link above. The quantity of the inputs is proportional to the rsi values. Long trades are directly traded with "RSI" value, while short poses are traded with "100-RSI" value.
How to use it?
The default settings are for scalp strategy but can be used for any type of trading strategy. you can develop different strategies by changing the sections. It is quite simple to use.
RSI length is length of RSİ
source is source of RSİ
RSİ Divergence lenght is length of line on the RSI
The "take profit", "stop" and "trailing stop" parts used in the "buy" group only affect buys. The "sell" group is similarly independent of the variables in the "buy" group.
The "zoom" section is used to enlarge or reduce the indicator. it only changes the appearance, it does not affect the results of the strategy.
I11L - Reversal Trading Ideas by Larry ConnorsThis is my own Twist on Larry Connors Simple Tradingideas.
It Combines the RSI, Averaging In and the Lowest Bars in a Single System.
The current Configuration is designed for the Daily Timeframe.
Feel free to play with the Parameters and keep in mind that Larry Intended to buy fear and sell the greed!
The Rules are the following:
---Buy---
Buy, if the lowest Bar of your Configuration has been hit (default is set to 7).
---Average Down--
Buy, if the lowest Bar of your Configuration * Your open trades has been hit AND only if the buyin is atleast 1% cheaper.
---Close---
Close, if the RSI closes above a certain level (default is set to 70).
---TP---
There is no TP
---SL---
There is no SL, so be cautions of your tail Risk!
