ARCHENS SHARESThis script marks the high and low of 9.45 to 10.15 price. When the price breaks high, then gives Buy signal. When the price breaks low, then it gives Sell Signal. These buy and sell signals are given with labels "ARCHENS BUY" or "ARCHENS SELL". With my observation in stock market, I have made this strategy.
This strategy works in normal candle pattern but i observed that it works well in heikenashi candle. For this strategy to work well, we have to select 5 mins heikenashi candles.
If this strategy gives "ARCHENS buy", then buy it. Target should be as per individuals mind. But Stop loss should be hitted when there are two continue opposite {red} heikenashi candle.
If this strategy gives "ARCHENS sell", then sell it. Target should be as per individuals mind. But Stop loss should be hitted when there are two continue opposite {green} heikenashi candle.
Индикаторы и стратегии
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
Fibonacci Moving Averages Input(FibMAI) Fibonacci Moving Averages Input is a strategy based on moving averages cross-over or cross-under signals. The bullish golden cross appears on a chart when a stock's short-term moving average crosses above its long-term moving average. The bearish death cross appears on a chart when a stock’s short-term moving average, crosses below its long-term moving average. The general market consensus values used are the 50-day moving average and the 200-day moving average.
With the (FibMAI) Fibonacci Moving Averages Input strategy you can use any value you choose for your bullish or bearish cross. For visual display purposes I have a lot of the Fib Moving Averages 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987 shown while hiding the chart candlesticks. But to use this indicator I click on only a couple of MA's to see if there's a notable cross-over or cross-under pattern signal. Then, most importantly, I back test those values into the FibMAI strategy Long or Short settings input.
For example, this NQ1! day chart has it's Long or Short settings input as follows:
Bullish =
FibEMA34
cross-over
FibEMA144
Bearish =
FibEMA55
cross-under
FibSMA144
As you can see you can mix or match 4 different MA's values either Exponential or Simple.
Default color settings:
Rising value = green color
Falling value = red color
Default Visual FibMA settings:
FibEMA's 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181
Default Visual MA settings:
SMA's 50, 100, 150, 200
Default Long or Short settings:
Bullish =
FibEMA34
cross-over
FibEMA144
Bearish =
FibEMA55
cross-under
FibSMA144
Strategy for UT Bot Alerts indicator Using the UT Bot alerts indicator by @QuantNomad, this strategy was designed for showing an example of how this indicator could be used, also, it has the goal to help some people from a group that use to use this indicator for their trading. Under any circumstance I recommend to use it without testing it before in real time.
Backtesting context: 2020-02-05 to 2023-02-25 of BTCUSD 4H by Tvc. Commissions: 0.03% for each entry, 0.03% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 3 indicators are used:
UT Bot Alerts indicator by Quantnomad
One Ema of 200 periods for indicate the trend
Atr stop loss from Gatherio
Trade conditions:
For longs:
Close price is higher than Atr from UT Bot
Ema from UT Bot cross over Atr from UT Bot.
This gives us our long signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 0.75:1 and take profit of 3:1 where half position will be closed. This will be showed as buy (open long position)
The other half will be closed when close price is lower than Atr and Ema from UT Bot cross under Atr. This will be showed as cl buy (close long position)
For shorts:
Close price is lower than Atr from UT Bot
Ema from UT Bot cross over Atr from UT Bot.
This gives us our short signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 0.75:1 and take profit of 3:1 where half position will be closed. This will be showed as sell (open short position)
The other half will be closed when close price is higher than Atr and Ema from UT Bot cross over Atr. This will be showed as cl sell (close short position)
Risk management
For calculate the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a long signal at price of 20,000 usd. The stop loss price from atr stop loss is 19,000. You calculate the distance in percent between 20,000 and 19,000. In this case, that distance would be of 5,0%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(5,0%) = 500usd. It means, you have to use 500 usd for risking 2.5% of your account.
We will use this risk management for apply compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital
---> Do not forget to deactivate Trades on chart option in style settings for a cleaner look of the chart <---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Strategies for trending markets use to have more looses than wins and it takes a long time to get profits, so do not forget to be patient and consistent !
---> The strategy can still be improved, you can change some parameters depending of the asset and timeframe like risk/reward for taking profits, for break even, also the main parameters of the UT Bot Alerts <----
NIFTY 50 5mint StrategyThis is an intraday strategy for NIFTY50 Based First candle High and Low breakout.
The strategy takes user inputs for the start and end dates, start and end months, and start and end years, which define the time range to trade. The user can also specify the maximum number of trades to take during the time range and the length of the Exponential Moving Average ( EMA ) used in the strategy
In this strategy, the First candle's high and low are calculated and used as entry and exit points for trades. If the close price breaks above the First candle's high, a buy signal is generated. Conversely, if the close price breaks below the First candle's low, a sell signal is generated.
The strategy uses the Exponential Moving Average ( EMA ) as a filter to close entered positions either long or short, EMA also acts Target. If the close price falls below the EMA, a long position is closed, and if the close price rises above the EMA, a short position is closed or the PreviousCandleClose is above the First candle's high a short position is closed, When the PreviousCandleClose is below the First candle's low a long position is closed, First candle's high act as Stoploss
The strategy limits the number of trades taken within the specified time range, and if the time range is exceeded, all positions are closed.
Finally, the strategy plots the First candle's high and low, EMAs on the chart for visual reference.
Default settings work best with the 5mint candle, you may tweak settings according to your needs.
backtesting helps in interpreting how the trading strategy would have behaved in the past, and forward testing (paper trading) informs the traders how it would perform now.
Bollinger Band BreakoutThis strategy buys when price crosses above an upper Bollinger Band and sells when the lower band is breached. What makes this strategy different than others:
Long only with filtering for only showing strong tickers
Filter out trades below a moving average on both the current timeframe and a longer period timeframe to keep you out of bear markets
Optional ability to set a tighter initial stop level to increase exposure and decrease downside risk on freshly opened trades while you wait for the lower Bollinger Band trailing stop to catch up
Take entries/exits on wicks/stops or wait for candle closes before entry
Select which dates to backtest
Customize Bollinger Band parameters including the ability to have different values for the upper and lower band standard deviation
Baseline Cross Qualifier Volatility Strategy with HMA Trend BiasFor trading ES on 30min Chart
Trading Rules
Post Baseline Cross Qualifier (PBCQ): If price crosses the baseline but the trade is invalid due to additional qualifiers, then the strategy doesn't enter a trade on that candle. This setting allows you override this disqualification in the following manner: If price crosses XX bars ago and is now qualified by other qualifiers, then the strategy enters a trade.
Volatility: If price crosses the baseline, we check to see how far it has moved in terms of multiples of volatility denoted in price (ATR x multiple). If price has moved by at least "Qualifier multiplier" and less than "Range Multiplier", then the strategy enters a trade. This range is shown on the chart with yellow area that tracks price above/blow the baseline. Also, see the dots at the top of the chart. If the dots are green, then price passes the volatility test for a long. If the dots are red, then price passes the volatility test for a short.
Take Profit/Stoploss Quantity Removed
1 Take Profit: 100% of the trade is closed when the profit target or stoploss is reached.
2 Take Profits: Quantity is split 50/50 between Take Profit 1 and Take Profit 2
3 Take Profits: Quantify is split 50/25/25.
Stratgey Inputs
Baseline Length
37
Post Baseline Cross Qualifier Enabled
On
Post Baseline Cross Qualifier Bars Ago
9
ATR Length
9
Volatility Multiplier
0
Volatility Range Multiplier
10
Volatility Qualifier Multiplier
2
Take Profit Type
1 Take Profit
HMA Length
11
Combined Strategy Trading Bot (RSI ADX 20SMA)Trading Bot V1, This code implements a combined trading strategy that uses several indicators and strategies to make buy and sell decisions in the market. The code is written in Pine Script™, which is a programming language used in the TradingView platform. By BraelonWhitfield.Eth
The strategy uses the Average Directional Movement Index (ADX) and the Pine SuperTrend indicator to identify trends and price movements in the market. The SuperTrend indicator is a popular technical analysis tool that helps to identify the direction of the current trend and provides entry and exit points for trades.
The strategy also uses the Relative Strength Index (RSI) to identify overbought and oversold conditions in the market. The RSI is a momentum indicator that measures the speed and change of price movements in the market.
The first part of the code defines the inputs for the ADX and DI Length, which are used to calculate the ADX and DI values. The dirmov() function is used to calculate the positive and negative directional indicators (plusDM and minusDM) based on the high and low prices. The truerange variable is then calculated using the True Range (TR) formula. Finally, the plus and minus variables are calculated using the smoothed moving average of the plusDM and minusDM values.
The adx() function is then used to calculate the ADX values based on the plus and minus variables. The Pine SuperTrend indicator is defined using the pine_supertrend() function. This function uses the high-low average (hl2) and the Average True Range (ATR) to calculate the upper and lower bands for the indicator. The direction of the current trend is then determined based on whether the current price is above or below the upper or lower bands.
The RSI values are then calculated using the ta.rsi() function, with the inputs for the close price and the RSI period. The overbought and oversold conditions are defined using the OB and OS inputs, which specify the threshold values for the RSI. The upTrend and downTrend variables are defined based on the direction of the Pine SuperTrend indicator.
The next part of the code defines the 20-period Simple Moving Average (SMA) using the ta.sma() function. The os and ob variables are then calculated based on the RSI values and the OB and OS inputs. The strategy.entry() function is used to define the buy and sell orders based on the upTrend and downTrend variables, as well as the Pine SuperTrend indicator, the 20-period SMA, and the os variable.
The final part of the code defines the Channel Breakout Strategy using the ta.highest() and ta.lowest() functions to calculate the upper and lower bounds of the channel. The strategy.entry() function is then used to define the buy and sell orders based on whether the current price is above or below the upper or lower bounds.
In summary, this code implements a combined trading strategy that uses several indicators and strategies to make buy and sell decisions in the market. The strategy is designed to identify trends and price movements in the market, as well as overbought and oversold conditions, to provide entry and exit points for trades. The strategy uses the Pine SuperTrend indicator, the ADX and DI indicators, the RSI, and the 20-period SMA, as well as the Channel Breakout Strategy to make informed trading decisions.
Ema ScalpThis is another simple strategy based on ema
Entry Buy - 1) when close crossover ema then buy and only open one trade till it not close
2) if previous buy trade is profitable open another trade and check again trade is profitable or not
3)if trade is not profitable reset and wait for sell condition...
Entry Sell -1) when close crossunder ema then sell and only open one trade till it not close
2) if previous sell trade is profitable open another trade and check again trade is profitable or not
3) if trade is not profitable reset and wait for buy condition.....
stop loss and take profit is percentage based ...
Investments/swing trading strategy for different assetsStop worrying about catching the lowest price, it's almost impossible!: with this trend-following strategy and protection from bearish phases, you will know how to enter the market properly to obtain benefits in the long term.
Backtesting context: 1899-11-01 to 2023-02-16 of SPX by Tvc. Commissions: 0.05% for each entry, 0.05% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 5 indicators are used:
One Ema of 200 periods
Atr Stop loss indicator from Gatherio
Squeeze momentum indicator from LazyBear
Moving average convergence/divergence or Macd
Relative strength index or Rsi
Trade conditions:
There are three type of entries, one of them depends if we want to trade against a bearish trend or not.
---If we keep Against trend option deactivated, the rules for two type of entries are:---
First type of entry:
With the next rules, we will be able to entry in a pull back situation:
Squeeze momentum is under 0 line (red)
Close is above 200 Ema and close is higher than the past close
Histogram from macd is under 0 line and is higher than the past one
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
For closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Second type of entry:
With the next rules, we will not lose a possible bullish movement:
Close is above 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entry, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
---If we keep Against trend option activated, the rules are the same as the ones above, but with one more type of entry. This is more useful in weekly timeframes, but could also be used in daily time frame:---
Third type of entry:
Close is under 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entries, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Risk management
For calculating the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
If you activate break even using rsi, when rsi crosses under overbought zone break even will be activated. This can work in some assets.
---Important: In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Some assets and timeframes where the strategy has also worked:
BTCUSD : 4H, 1D, W
SPX (US500) : 4H, 1D, W
GOLD : 1D, W
SILVER : 1D, W
ETHUSD : 4H, 1D
DXY : 1D
AAPL : 4H, 1D, W
AMZN : 4H, 1D, W
META : 4H, 1D, W
(and others stocks)
BANKNIFTY : 4H, 1D, W
DAX : 1D, W
RUT : 1D, W
HSI : 1D, W
NI225 : 1D, W
USDCOP : 1D, W
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.
Backtest AdapterThis is a proof-of-concept Backtest Adapter that can be used with my recent publication "Machine Learning: Lorentzian Classification" located here:
This adapter is helpful because it enables interactive backtesting with TradingView's built-in "Strategy Tester" framework without the need to translate the logic from an "indicator" script to a "strategy" script.
To use this, one must have the "Machine Learning: Lorentzian Classification" script and this Backtest Adapter open simultaneously on the same chart. From there, simply change the "Source" setting of the Backtest Adapter to "Lorentzian Classification: Backtest Stream" to transfer the entry/exit signals stream to the Backtest Adapter.
For an example of how to implement your own backtest stream in your indicators, please refer to the "Backtesting" section in the source code of the "Machine Learning: Lorentzian Classification" script, which is shown below for convenience:
