MACDh with divergences & impulse system (overlayed on prices)-----------------------------------------------------------------
General Description:
This indicator ( the one on the top panel above ) consists on some lines, arrows and labels drawn over the price bars/candles indicating the detection of regular divergences between price and the classic MACD histogram (shown on the low panel). This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra features" Impulse System and Keltner Channels, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
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Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Some cool features included in this indicator:
1. This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Price bars are colored blue when conditions for a Red Price Bar or Green Price Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green price bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red price bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue price bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
2. Another "extra feature" included here is the " Keltner Channels ". Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
3. It were also included a couple of EMAs.
Everything can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*Shows a pair of EMAs.
*Shows Keltner Channels (using ATR)
Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
*This indicator also has the option to show the Impulse System over the price bars/candles.
在腳本中搜尋"俄罗斯军工股+俄乌战争+股价走势+2022"
MACDh with divergences & impulse system-----------------------------------------------------------------
General Description:
This indicator ( the one on the low panel ) is a classic MACD that also shows regular divergences between its histogram and the prices. This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra feature" Impulse System, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
-----------------------------------------------------------------
Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Extra feature: Impulse System
This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars or macd histogram bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Histogram bars are colored blue when conditions for a Red Histogram Bar or Green Histogram Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green histogram bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red histogram bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue histogram bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
The impulse system can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*This indicator also has the option to show the Impulse System over the MACD histogram bars
Volume ValueWhen VelocityTitle: Volume ValueWhen Velocity Trading Strategy
▶ Introduction:
The " Volume ValueWhen Velocity " trading strategy is designed to generate long position signals based on various technical conditions, including volume thresholds, RSI (Relative Strength Index), and price action relative to the Simple Moving Average (SMA). The strategy aims to identify potential buy opportunities when specific criteria are met, helping traders capitalize on potential bullish movements.
▶ How to use and conditions
★ Important : Only on Spot Binance BINANCE:BTCUSDT
Name: Volume ValueWhen Velocity
Operating mode: Long on Spot BINANCE BINANCE:BTCUSDT
Timeframe: Only one hour
Market: Crypto
currency: Bitcoin only
Signal type: Medium or short term
Entry: All sections in the Technical Indicators and Conditions section must be saved to enter (This is explained below)
Exit: Based on loss limit and profit limit It is removed in the settings section
Backtesting:
⁃ Exchange: BINANCE BINANCE:BTCUSDT
⁃ Pair: BTCUSDT
⁃ Timeframe:1h
⁃ Fee: 0.1%
- Initial Capital: 1,000 USDT
- Position sizing: 500 usdt
-Trading Range: 2022-07-01 11:30 ___ 2023-07-21 14:30
▶ Strategy Settings and Parameters:
1. `strategy(title='Volume ValueWhen Velocity', ...`: Sets the strategy title, initial capital, default quantity type, default quantity value, commission value, and trading currency.
↬ Stop-Loss and Take-Profit Settings:
1. long_stoploss_value and long_stoploss_percentage : Define the stop-loss percentage for long positions.
2. long_takeprofit_value and long_takeprofit_percentage : Define the take-profit percentage for long positions.
↬ ValueWhen Occurrence Parameters:
1. occurrence_ValueWhen_1 and occurrence_ValueWhen_2 : Control the occurrences of value events.
2. `distance_value`: Specifies the minimum distance between occurrences of ValueWhen 1 and ValueWhen 2.
↬ RSI Settings:
1. rsi_over_sold and rsi_length : Define the oversold level and RSI length for RSI calculations.
↬ Volume Thresholds:
1. volume_threshold1 , volume_threshold2 , and volume_threshold3 : Set the volume thresholds for multiple volume conditions.
↬ ATR (Average True Range) Settings:
1. atr_small and atr_big : Specify the periods used to calculate the Average True Range.
▶ Date Range for Back-Testing:
1. start_date, end_date, start_month, end_month, start_year, and end_year : Define the date range for back-testing the strategy.
▶ Technical Indicators and Conditions:
1. rsi: Calculates the Relative Strength Index (RSI) based on the defined RSI length and the closing prices.
2. was_over_sold: Checks if the RSI was oversold in the last 10 bars.
3. getVolume and getVolume2 : Custom functions to retrieve volume data for specific bars.
4. firstCandleColor : Evaluates the color of the first candle based on different timeframes.
5. sma : Calculates the Simple Moving Average (SMA) of the closing price over 13 periods.
6. numCandles : Counts the number of candles since the close price crossed above the SMA.
7. atr1 : Checks if the ATR_small is less than ATR_big for the specified security and timeframe.
8. prevClose, prevCloseBarsAgo, and prevCloseChange : ValueWhen functions to calculate the change in the close price between specific occurrences.
9. atrval: A condition based on the ATR_value3.
▶ Buy Signal Condition:
Condition: A combination of multiple volume conditions.
buy_signal: The final buy signal condition that considers various technical conditions and their interactions.
▶ Long Strategy Execution:
1. The strategy will enter a long position (buy) when the buy_signal condition is met and within the specified date range.
2. A stop-loss and take-profit will be set for the long position to manage risk and potential profits.
▶ Conclusion:
The " Volume ValueWhen Velocity " trading strategy is designed to identify long position opportunities based on a combination of volume conditions, RSI, and price action. The strategy aims to capitalize on potential bullish movements and utilizes a stop-loss and take-profit mechanism to manage risk and optimize potential returns. Traders can use this strategy as a starting point for their own trading systems or further customize it to suit their preferences and risk appetite. It is crucial to thoroughly back-test and validate any trading strategy before deploying it in live markets.
↯ Disclaimer:
Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Yesterday's High v.17.07Yesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of INJ, a 12% Take-Profit and a 1.5% Stop-Loss were set, with an activated trailing-stop percentage, TRL 1 and OFF 0.5.
To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name: Yesterday's High Breakout - Trend Follower Strategy
Author: @tumiza999
Category: Trend Follower, Breakout of Yesterday's High.
Operating mode: Spot or Futures (only long).
Trade duration: Intraday.
Timeframe: 30M, 1H, 2H, 4H
Market: Crypto
Suggested usage: Short-term trading, when the market is in trend and it is showing high volatility.
Entry: When there is a breakout of Yesterday's High.
Exit: Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration:
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting:
⁃ Exchange: BINANCE
⁃ Pair: INJUSDT
⁃ Timeframe: 4H
- Treshold: 1
- Gap%: 1
- SL: 1.5
- TP:12
- TRL: 1
- OFF-TRL: 0.5
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits: LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer: Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Modern Portfolio Management IndicatorAfter weeks of grueling over this indicator, I am excited to be releasing it!
Intro:
This is not a sexy, technical or math based indicator that will give you buy and sell signals or anything fancy, but it is an indicator that I created in hopes to bridge a gap I have noticed. That gap is the lack of indicators and technical resources for those who also like to plan their investments. This indicator is tailored to those who are either established investors and to those who are looking to get into investing but don't really know where to start.
The premise of this indicator is based on Modern Portfolio Theory (MPT). Before we get into the indicator itself, I think its important to provide a quick synopsis of MPT.
About MPT:
Modern Portfolio Theory (MPT) is an investment framework that was developed by Harry Markowitz in the 1950s. It is based on the idea that an investor can optimize their investment portfolio by considering the trade-off between risk and return. MPT emphasizes diversification and holds that the risk of an individual asset should be assessed in the context of its contribution to the overall portfolio's risk. The theory suggests that by diversifying investments across different asset classes with varying levels of risk, an investor can achieve a more efficient portfolio that maximizes returns for a given level of risk or minimizes risk for a desired level of return. MPT also introduced the concept of the efficient frontier, which represents the set of portfolios that offer the highest expected return for a given level of risk. MPT has been widely adopted and used by investors, financial advisors, and portfolio managers to construct and manage portfolios.
So how does this indicator help with MPT?
The thinking and theory that went behind this indicator was this: I wanted an indicator, or really just a "way" to test and back-test ticker performance over time and under various circumstances and help manage risk.
Over the last 3 years we have seen a massive bull market, followed by a pretty huge bear market, followed by a very unexpected bull market. We have been and continue to be plagued with economic and political uncertainty that seems to constantly be looming over everyone with each waking day. Some people have liquidated their retirement investments, while others are fomoing in to catch this current bull run. But which tickers are sound and how tickers and funds have compared amongst each other remains somewhat difficult to ascertain, absent manually reviewing and calculating each ticker individually.
That is where this indicator comes in. This indicator permits the user to define up to 5 equities that they are potentially interested in investing in, or are already invested in. The user can then select a specific period in time, say from the beginning of 2022 till now. The user can then define how much they want to invest in each company by number of shares, so if they want to buy 1 share a week, or 2 shares a month, they can input these variables into the indicator to draw conclusions. As many brokers are also now permitting fractional share trading, this ability is also integrated into the indicator. So for shares, you can put in, say, 0.25 shares of SPY and the indicator will accept this and account for this fractional share.
The indicator will then show you a portfolio summary of what your earnings and returns would be for the defined period. It will provide a percent return as well as the projected P&L based on your desired investment amount and frequency.
But it goes beyond just that, you can also have the indicator display a simple forecasting projection of the portfolio. It will show the projected P&L and % Return over various periods in time on each of the ticker (see image below):
The indicator will also break down your portfolio allocation, it will show where the majority of your holdings are and where the majority of your P&L in coming from (best performers will show a green fill and worst will show a red fill, see image below):
This colour coding also extends to the portfolio breakdown itself.
Dollar cost averaging (DCA) is incorporated into the indicator itself, by assuming ongoing contributions. If you want to stop contributions at a certain point, you just select your end time for contributions at the point in which you would stop contributing.
The indicator also provides some basic fundamental information about the company tickers (if applicable). Simply select the "Fundamental" chart and it will display a breakdown of the fundamentals, including dividends paid, market cap and earnings yield:
The indicator also provides a correlation assessment of each holding against each other holding. This emphasizes the profound role of diversification on portfolios. The less correlation you have in your portfolio among your holdings, the better diversified you are. As well, if you have holdings that are perfectly inverse other holdings, you have a pseudo hedge against the downturn of one of your holdings. This is even more helpful if the inverse is a company with solid fundamentals.
In the below example you will see NASDAQ:IRDM in the portfolio. You will be able to see that NASDAQ:IRDM has a slight inverse relationship to SPY:
Yet IRDM has solid fundamentals and is performing well fundamentally. Thus, this makes IRDIM a solid addition to your portfolio as it can potentially hedge against a downturn for SPY and is less risky than simply holding an inverse leveraged share on SPY which is most likely just going to cost you money than make you money.
Concluding remarks:
There are many fun and interesting things you can do with this indicator and I encourage you to try it out and have fun with it! The overall objective with the indicator is to help you plan for your portfolio and not necessarily to manage your portfolio. If you have a few stocks you are looking at and contemplating investing in, this will help you run some theoretical scenarios with this stock based on historical performance and also help give you a feel of how it will perform in the future based on past behaviour.
It is important to remember that past behaviour does not indicate future behaviour, but the indicator provides you with tools to get a feel for how a stock has performed under various circumstances and get a general feel of the fundamentals of the company you could potentially be investing in.
Please note, this indicator is not meant to replace full, fundamental analyses of individual companies. It is simply meant to give you a "gist" of how companies are fundamentally and how they have performed historically.
I hope you enjoy it!
Safe trades everyone!
MA Correlation CoefficientThis script helps you visualize the correlation between the price of an asset and 4 moving averages of your choice. This indicator can help you identify trendy markets as well as trend-shifts.
Disclaimer
Bear in mind that there is always some lag when using Moving-Averages, hence the purpose of this indicator is as a trend identification tool rather than an entry-exit strategy.
Working Principle
The basic idea behind this indicator is the following:
In a trendy market you will find high correlation between price and all kinds of Moving-Averages. This works both ways, no matter bull or bear trend.
In sideways markets you might find a mix of correlations accross timeframes (2018) or high correlation with Low-Timeframe averages and low correlation with High-Timeframe averages (2021/2022).
Trend shifts might be characterised by a 'staircase' type of correlation (yellow), where the asset regains correlation with higher timeframe averages
Indicator Options
1. Source : data used for indicator calculation
1. Correlation Window : size of moving window for correlation calculation
2. Average Type :
Simple-Moving-Average (SMA)
Exponential-Moving-Average (EMA)
Hull-Moving-Average (HMA)
Volume-Weighted-Moving-Average (VWMA)
3. Lookback : number of past candles to calculate average
4. Gradient : modify gradient colors. colors relate to correlation values.
Plot Explanation
The indicator plots, using colors, the correlation of the asset with 4 averages. For every candle, 4 correlation values are generated, corresponding to 4 colors. These 4 colors are stacked one on top of the other generating the patterns explained above. These patterns may help you identify what kind of market you're in.
Bollinger Bands - Breakout StrategyThe Bollinger Bands - Breakout Strategy is a trend-following optimized for short-term trading in the crypto market. This strategy employs the Bollinger Bands, a widely recognized technical indicator, as its primary instrument for pinpointing potential trades. It is capable of executing both long and short positions, depending on whether the market is in a spot or futures, and is particularly effective in trending markets.
The strategy boasts a high degree of configurability, allowing users to set the Bollinger Bands period and deviation, trend filter, volatility filter, trade direction filter, rate of change filter, and date filter. Furthermore, it offers options for Take Profit, Stop Loss, and Trailing Stop for both long and short positions, ensuring a comprehensive risk management approach. The inclusion of a maximum intraday loss feature adds another layer of protection, making this strategy a valuable tool for traders seeking a professional and adaptable trading system.
Name : Bollinger Bands - Breakout Strategy
Category : Trend Follower based on Bollinger Bands
Operating mode : Long and Short on Futures or Long on Spot
Trade duration : Intraday
Timeframe : 2H, 3H, 4H, 5H
Market : Crypto
Suggested usage : Trending Markets
Entry : When the price crosses above or below the Bollinger Bands
Exit : Opposite Cross or Profit target, Trailing stop or Stop loss
Configuration :
- Bollinger Bands period and deviation
- Trend Filter
- Volatility Filter
- Trade direction filter
- Rate of Change filter
- Date Filter (for backtesting purposes)
- Take Profit, Stop Loss and Trailing Stop for long and short positions
- Risk Management: Max Intraday Loss
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: BTCUSDT.P
⁃ Timeframe: 4H
⁃ Fee: 0.025%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2019-09-19 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits :
- LucF of Pine Coders for f_security function to avoid repainting using security.
- QuantNomad for Monthly Table.
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Yesterday’s High Breakout - Trend Following StrategyYesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of NULS, a 9% Take-Profit and a 3% Stop-Loss were set, with an activated trailing-stop percentage. To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name : Yesterday's High Breakout - Trend Follower Strategy
Author : @tumiza999
Category : Trend Follower, Breakout of Yesterday's High.
Operating mode : Spot or Futures (only long).
Trade duration : Intraday.
Timeframe : 30M, 1H, 2H, 4H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility.
Entry : When there is a breakout of Yesterday's High.
Exit : Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration :
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: NULSUSDT
⁃ Timeframe: 2H
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits : LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Simple ICT Market Structure by toodegreesThis Simple ICT Market Structure is based on the teachings of ICT, specifically in his episode 12 of the Public 2022 Mentorship.
The only omission here is the peculiar calculation of Intermediate Term points, for which I am not using the concept of repricing imbalances – this can be added later!
Feel free to use this tool, however it is quite simple and market structure is something we all know very well how to spot. In my opinion it is helpful to display the long term swing points to identify more mature pools of liquidity.
The reason for coding this tool is to help new coders understand PineScript (I have a video tutorial where I code this from start to finish), as well as fostering some algorithmic thinking in your trading of ICT Concepts and Algorithmic Delivery.
If you have any questions about the code, shoot me a message!
Hope you learn something and GLGT!
Lorentzian Classification Strategy Based in the model of Machine learning: Lorentzian Classification by @jdehorty, you will be able to get into trending moves and get interesting entries in the market with this strategy. I also put some new features for better backtesting results!
Backtesting context: 2022-07-19 to 2023-04-14 of US500 1H by PEPPERSTONE. 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:
Machine learning: Lorentzian Classification by @jdehorty
One Ema of 200 periods for identifying the trend
Supertrend indicator as a filter for some exits
Atr stop loss from Gatherio
Trade conditions:
For longs:
Close price is above 200 Ema
Lorentzian Classification indicates a buying signal
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 1:1 and take profit of 3:1 where half position will be closed. This will be showed as buy.
The other half will be closed when the model indicates a selling signal or Supertrend indicator gives a bearish signal. This will be showed as cl buy.
For shorts:
Close price is under 200 Ema
Lorentzian Classification indicates a selling signal
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 1:1 and take profit of 3:1 where half position will be closed. This will be showed as sell.
The other half will be closed when the model indicates a buying signal or Supertrend indicator gives a bullish signal. This will be showed as cl sell.
Risk management
To 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 or last swing 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 or last swing 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.
> You can also choose a fixed amount, so you will have to activate fixed amount in risk management for trades and set the fixed amount for backtesting.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, a table of some stats from backtesting, etc.
You will find the settings for risk management at the end of the script if you want to change something or trying new values for other assets for backtesting.
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
I also added a function for backtesting if you had added or withdrawn money frequently:
Adding money: You can choose how often you want to add money (Monthly, yearly, daily or weekly). Then a fixed amount of money and activate or deactivate this function
Withdraw money: You can choose if you want to withdraw a fixed amount or a percentage of earnings. Then you can choose a fixed amount of money, the period of time and activate or deactivate this function. Also, the percentage of earnings if you choosed this option.
Some other assets where strategy has worked
BTCUSD 4H, 1D
ETHUSD 4H, 1D
BNBUSD 4H
SPX 1D
BANKNIFTY 4H, 15 min
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!. If you have problems loading the script reduce max bars back number in general settings
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 !
Please, visit the post from @jdehorty called Machine Learning: Lorentzian Classification for a better understanding of his script!
Any support and boosts will be well received. If you have any question, do not doubt to ask!
ICT Concepts [LuxAlgo]The ICT Concepts indicator regroups core concepts highlighted by trader and educator "The Inner Circle Trader" (ICT) into an all-in-one toolkit. Features include Market Structure (MSS & BOS), Order Blocks, Imbalances, Buyside/Sellside Liquidity, Displacements, ICT Killzones, and New Week/Day Opening Gaps.
🔶 SETTINGS
🔹 Mode
When Present is selected, only data of the latest 500 bars are used/visualized, except for NWOG/NDOG
🔹 Market Structure
Enable/disable Market Structure.
Length: will set the lookback period/sensitivity.
In Present Mode only the latest Market Structure trend will be shown, while in Historical Mode, previous trends will be shown as well:
You can toggle MSS/BOS separately and change the colors:
🔹 Displacement
Enable/disable Displacement.
🔹 Volume Imbalance
Enable/disable Volume Imbalance.
# Visible VI's: sets the amount of visible Volume Imbalances (max 100), color setting is placed at the side.
🔹 Order Blocks
Enable/disable Order Blocks.
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Color settings.
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
Change in Order Blocks style:
🔹 Liquidity
Enable/disable Liquidity.
Margin: sets the sensitivity, 2 points are fairly equal when:
'point 1' < 'point 2' + (10 bar Average True Range / (10 / margin)) and
'point 1' > 'point 2' - (10 bar Average True Range / (10 / margin))
# Visible Liq. boxes: sets the amount of visible Liquidity boxes (max 50), this amount is for Sellside and Buyside boxes separately.
Colour settings.
Change in Liquidity style:
🔹 Fair Value Gaps
Enable/disable FVG's.
Balance Price Range: this is the overlap of latest bullish and bearish Fair Value Gaps.
By disabling Balance Price Range only FVGs will be shown.
Options: Choose whether you wish to see FVG or Implied Fair Value Gaps (this will impact Balance Price Range as well)
# Visible FVG's: sets the amount of visible FVG's (max 20, in the same direction).
Color settings.
Change in FVG style:
🔹 NWOG/NDOG
Enable/disable NWOG; color settings; amount of NWOG shown (max 50).
Enable/disable NDOG ; color settings; amount of NDOG shown (max 50).
🔹 Fibonacci
This tool connects the 2 most recent bullish/bearish (if applicable) features of your choice, provided they are enabled.
3 examples (FVG, BPR, OB):
Extend lines -> Enabled (example OB):
🔹 Killzones
Enable/disable all or the ones you need.
Time settings are coded in the corresponding time zones.
🔶 USAGE
By default, the indicator displays each feature relevant to the most recent price variations in order to avoid clutter on the chart & to provide a very similar experience to how a user would contruct ICT Concepts by hand.
Users can use the historical mode in the settings to see historical market structure/imbalances. The ICT Concepts indicator has various use cases, below we outline many examples of how a trader could find usage of the features together.
In the above image we can see price took out Sellside liquidity, filled two bearish FVGs, a market structure shift, which then led to a clean retest of a bullish FVG as a clean setup to target the order block above.
Price then fills the OB which creates a breaker level as seen in yellow.
Broken OBs can be useful for a trader using the ICT Concepts indicator as it marks a level where orders have now been filled, indicating a solidified level that has proved itself as an area of liquidity. In the image above we can see a trade setup using a broken bearish OB as a potential entry level.
We can see the New Week Opening Gap (NWOG) above was an optimal level to target considering price may tend to fill / react off of these levels according to ICT.
In the next image above, we have another example of various use cases where the ICT Concepts indicator hypothetically allow traders to find key levels & find optimal entry points using market structure.
In the image above we can see a bearish Market Structure Shift (MSS) is confirmed, indicating a potential trade setup for targeting the Balanced Price Range imbalance (BPR) below with a stop loss above the buyside liquidity.
Although what we are demonstrating here is a hindsight example, it shows the potential usage this toolkit gives you for creating trading plans based on ICT Concepts.
Same chart but playing out the history further we can see directly after price came down to the Sellside liquidity & swept below it...
Then by enabling IFVGs in the settings, we can see the IFVG retests alongside the Sellside & Buyside liquidity acting in confluence.
Which allows us to see a great bullish structure in the market with various key levels for potential entries.
Here we can see a potential bullish setup as price has taken out a previous Sellside liquidity zone and is now retesting a NWOG + Volume Imbalance.
Users also have the option to display Fibonacci retracements based on market structure, order blocks, and imbalance areas, which can help place limit/stop orders more effectively as well as finding optimal points of interest beyond what the primary ICT Concepts features can generate for a trader.
In the above image we can see the Fibonacci extension was selected to be based on the NWOG giving us some upside levels above the buyside liquidity.
🔶 DETAILS
Each feature within the ICT Concepts indicator is described in the sub sections below.
🔹 Market Structure
Market structure labels are constructed from price breaking a prior swing point. This allows a user to determine the current market trend based on the price action.
There are two types of Market Structure labels included:
Market Structure Shift (MSS)
Break Of Structure (BOS)
A MSS occurs when price breaks a swing low in an uptrend or a swing high in a downtrend, highlighting a potential reversal. This is often labeled as "CHoCH", but ICT specifies it as MSS.
On the other hand, BOS labels occur when price breaks a swing high in an uptrend or a swing low in a downtrend. The occurrence of these particular swing points is caused by retracements (inducements) that highlights liquidity hunting in lower timeframes.
🔹 Order Blocks
More significant market participants (institutions) with the ability of placing large orders in the market will generally place a sequence of individual trades spread out in time. This is referred as executing what is called a "meta-order".
Order blocks highlight the area where potential meta-orders are executed. Bullish order blocks are located near local bottoms in an uptrend while bearish order blocks are located near local tops in a downtrend.
When price mitigates (breaks out) an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
🔹 Buyside & Sellside Liquidity
Buyside / Sellside liquidity levels highlight price levels where market participants might place limit/stop orders.
Buyside liquidity levels will regroup the stoploss orders of short traders as well as limit orders of long traders, while Sellside liquidity levels will regroup the stoploss orders of long traders as well as limit orders of short traders.
These levels can play different roles. More informed market participants might view these levels as source of liquidity, and once liquidity over a specific level is reduced it will be found in another area.
🔹 Imbalances
Imbalances highlight disparities between the bid/ask, these can also be defined as inefficiencies, which would suggest that not all available information is reflected by the price and would as such provide potential trading opportunities.
It is common for price to "rebalance" and seek to come back to a previous imbalance area.
ICT highlights multiple imbalance formations:
Fair Value Gaps: A three candle formation where the candle shadows adjacent to the central candle do not overlap, this highlights a gap area.
Implied Fair Value Gaps: Unlike the fair value gap the implied fair value gap has candle shadows adjacent to the central candle overlapping. The gap area is constructed from the average between the respective shadow and the nearest extremity of their candle body.
Balanced Price Range: Balanced price ranges occur when a fair value gap overlaps a previous fair value gap, with the overlapping area resulting in the imbalance area.
Volume Imbalance: Volume imbalances highlight gaps between the opening price and closing price with existing trading activity (the low/high overlap the previous high/low).
Opening Gap: Unlike volume imbalances opening gaps highlight areas with no trading activity. The low/high does not reach previous high/low, highlighting a "void" area.
🔹 Displacement
Displacements are scenarios where price forms successive candles of the same sentiment (bullish/bearish) with large bodies and short shadows.
These can more technically be identified by positive auto correlation (a close to open change is more likely to be followed by a change of the same sign) as well as volatility clustering (large changes are followed by large changes).
Displacements can be the cause for the formation of imbalances as well as market structure, these can be caused by the full execution of a meta order.
🔹 Kill Zones
Killzones represent different time intervals that aims at offering optimal trade entries. Killzones include:
- New York Killzone (7:9 ET)
- London Open Killzone (2:5 ET)
- London Close Killzone (10:12 ET)
- Asian Killzone (20:00 ET)
🔶 Conclusion & Supplementary Material
This script aims to emulate how a trader would draw each of the covered features on their chart in the most precise representation to how it's actually taught by ICT directly.
There are many parallels between ICT Concepts and Smart Money Concepts that we released in 2022 which has a more general & simpler usage:
ICT Concepts, however, is more specifically aligned toward the community's interpretation of how to analyze price 'based on ICT', rather than displaying features to have a more classic interpretation for a technical analyst.
MarkovChainLibrary "MarkovChain"
Generic Markov Chain type functions.
---
A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the
probability of each event depends only on the state attained in the previous event.
---
reference:
Understanding Markov Chains, Examples and Applications. Second Edition. Book by Nicolas Privault.
en.wikipedia.org
www.geeksforgeeks.org
towardsdatascience.com
github.com
stats.stackexchange.com
timeseriesreasoning.com
www.ris-ai.com
github.com
gist.github.com
github.com
gist.github.com
writings.stephenwolfram.com
kevingal.com
towardsdatascience.com
spedygiorgio.github.io
github.com
www.projectrhea.org
method to_string(this)
Translate a Markov Chain object to a string format.
Namespace types: MC
Parameters:
this (MC) : `MC` . Markov Chain object.
Returns: string
method to_table(this, position, text_color, text_size)
Namespace types: MC
Parameters:
this (MC)
position (string)
text_color (color)
text_size (string)
method create_transition_matrix(this)
Namespace types: MC
Parameters:
this (MC)
method generate_transition_matrix(this)
Namespace types: MC
Parameters:
this (MC)
new_chain(states, name)
Parameters:
states (state )
name (string)
from_data(data, name)
Parameters:
data (string )
name (string)
method probability_at_step(this, target_step)
Namespace types: MC
Parameters:
this (MC)
target_step (int)
method state_at_step(this, start_state, target_state, target_step)
Namespace types: MC
Parameters:
this (MC)
start_state (int)
target_state (int)
target_step (int)
method forward(this, obs)
Namespace types: HMC
Parameters:
this (HMC)
obs (int )
method backward(this, obs)
Namespace types: HMC
Parameters:
this (HMC)
obs (int )
method viterbi(this, observations)
Namespace types: HMC
Parameters:
this (HMC)
observations (int )
method baumwelch(this, observations)
Namespace types: HMC
Parameters:
this (HMC)
observations (int )
Node
Target node.
Fields:
index (series int) : . Key index of the node.
probability (series float) : . Probability rate of activation.
state
State reference.
Fields:
name (series string) : . Name of the state.
index (series int) : . Key index of the state.
target_nodes (Node ) : . List of index references and probabilities to target states.
MC
Markov Chain reference object.
Fields:
name (series string) : . Name of the chain.
states (state ) : . List of state nodes and its name, index, targets and transition probabilities.
size (series int) : . Number of unique states
transitions (matrix) : . Transition matrix
HMC
Hidden Markov Chain reference object.
Fields:
name (series string) : . Name of thehidden chain.
states_hidden (state ) : . List of state nodes and its name, index, targets and transition probabilities.
states_obs (state ) : . List of state nodes and its name, index, targets and transition probabilities.
transitions (matrix) : . Transition matrix
emissions (matrix) : . Emission matrix
initial_distribution (float )
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.
Distance from the High/Low priceThis indicator shows how far the price is from the Top and Bottom over a set period of time.
The basic purpose of this indicator is to quickly compare how many symbols have risen over a certain period of time.
For example,
For example, let's say I want to see what the maximum increase is from the December, and how much it's currently down from there.
Then, let's set the "Length" to approximately 1500 and check it from December 18th.
So now you can see that bitcoin is up to about 44%, and it's down 6.9% from its peak.
-----
For the second example, let's say I want to see what the maximum increase in ALPHA is and how far it is currently from that maximum.
So, as you can see in the chart above, the maximum increase over the period was about 120%, and now it's down by 22.8%.
-----
In addition, if you check 'Retracement' in the indicator setting, you can see the ratio of the currently located returns based on Top and Bottom.
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이 지표는, 특정 기간동안 여러개의 symbol들이 얼마만큼의 상승을 했는지 빠르게 비교하기 위해 만들었습니다.
위에 첨부한 사진을 기준으로 말씀드리겠습니다.
2022년 12월 말부터 올라온 상승의 최대폭이 얼마인지, 그리고 그 최대 상승으로부터 현재 얼마나 떨어졌는지를 확인하고 싶은 상황이라고 하겠습니다.
그렇다면 'Length'를 대략 1500으로 설정하여 12월 18일부터 확인해보겠습니다.
그러면 비트코인은 최대 약 44%만큼 상승하였고, 현재 최고점으로부터 6.9% 떨어진 상황이라는 것을 확인할 수 있습니다.
---
두 번째 예시로, ALPHA의 최대 상승폭이 얼마인지, 그리고 그 최댓값으로부터 현재 얼마만큼 떨어져 있는 상황인지를 확인하고 싶다고 가정해보겠습니다.
그렇다면 위의 차트에서 보이는 바와 같이, 해당 기간동안 최대 상승폭이 약 120%였고, 현재 그 최댓값으로부터 22.8%정도 하락한 상황이라는 것을 확인할 수 있습니다.
---
번외로, 지표 설정에서 'Retracement'를 체크하시면, Top과 Bottom을 기준으로 현재 위치한 되돌림의 비율을 확인할 수 있습니다.
Dark Energy Divergence OscillatorThe Dark Energy Divergence Oscillator (DEDO)
What makes The Universe grow at an accelerating pace?
Dark Energy.
What makes The Economy grow at an accelerating pace?
Debt.
Debt is the Dark Energy of The Economy.
I pronounce DEDO "Deed-oh", but variations are fine with me.
Note: The Pine Script version of DEDO is improved from the original formula, which used a constant all-time high calculation in the normalization factor. This was technically not as accurate for calculating liquidity pressure in historical data because it meant that historical prices were being tested against future liquidity factors. Now using Pine, the functions can be normalized for the bar at the time of calculation, so the liquidity factors are normalized per candle, not across the entire series, which feels like an improvement to me.
Thought Process:
It's all about the liquidity. What I started with is a correlation between major stock indices such as SPX and WRESBAL , a balance sheet metric on FRED
After September 2008, when QE was initiated, many asset valuations started to follow more closely with liquidity factors. This led me to create a function that could combine asset prices and liquidity in WRESBAL , in order to calculate their divergence and chart the signal in TradingView.
The original formula:
First, we don't want "non-QE" data. we only want data for the market affected by QE .
So, find SPX on the day of pre-QE: 1255.08 and subtract that from the 2022 top 4818.62 = 3563.54
With this post-QE SPX range, now you can normalize the price level simply by dividing by the range = ( SPX -1255.08)/3563.54)
Normalization produces values from 0 to 1 so that they can be compared with other normalized figures.
In order to test the 0 to 1 normalized SPX range measure against the liquidity number, WRESBAL , it's the same idea: normalize it using the max as the denominator and you get a 0 to 1 liquidity index:
( WRESBAL /4276000000000)
Subtract one from the other to get the divergence:
(( WRESBAL /4276000000000)-(( SPX -1255.08)/3563.54))*10
x10 to reduce decimal places, but this option is configurable in DEDO's input settings tab.
Positive values indicate there's ample liquidity to hold up price or even create bullish momentum in some cases. Negative values mean price levels are potentially extended beyond what liquidity levels can support.
Note: many viewers of the charts on social media wanted the values to go down in alignment with price moving down, so inverting the chart is what I do with Option + I. I like the fact that negative values represent a deficit in liquidity to hold up price but that's just me.
Now with Pine Script and some help from other liquidity focused accounts on TradingView , I was able to derive a script that includes central bank liquidity and Reverse Repo liquidity drain, all in one algorithm, with adjustable settings.
Central bank assets included in this version:
-JPY (Japan)
-CNY (China)
-UK (British Pound)
-SNB (Swiss National Bank)
-ECB (European Central Bank )
Central Bank assets can be adjusted to an allocation % so that the formula is adjusted for the market cap of the asset.
A handy table in the lower right corner displays useful information about the asset market cap, and percentage it represents in the liquidity pool.
Reverse repo soak is also an optional addition in the Input settings using the RRPONTSYD value from FRED. This value is subtracted from global liquidity used to determine divergence since it is swept away from markets when residing in the Fed's reverse repo facility.
There is an option to draw a line at the Zero bound. This provides a convenience so that the line doesn't keep having to be redrawn on every chart. The normalized equation produces a value that should oscillate around zero, as price/valuation grows past liquidity support, falls under it, and repeats in cycles.
Volume scaled Price + auto colour change light/dark mode🔶 OVERVIEW
🔹 This script shows price in a similar style as volume . To accomplish this we use the body of the candle ( close - open ), which is placed on a zero line.
This can be useful when comparing volume ~ price .
🔹 3 options are included to show additional lines, to make comparisons easier:
· Percentile nearest rank
· Bollinger Bands (BB)
· Simple Moving Average (SMA)
🔶 SETTINGS
🔹 Option : choose whether to show price (candles) or volume . Adding 2 versions of this indicator on the chart enables you to compare these 2 options:
🔹 Lines:
· (Percentile nearest rank (only the setting mult is used for this option).
· Bollinger Bands (BB) (only the setting % perc. nearest rank is used for this option).
· Simple Moving Average (SMA )
All 3 options will use length , this is the amount of bars used for calculations.
🔹 Show wick will show you... wicks :)
🔶 PERCENTILE NEAREST RANK
🔹 This script has 2 extra types of background color
dvP = volume > volume and z < z and z < prP_ and volume > prV
· In this case:
· volume is higher than previous volume ( volume > volume )
· volume is above 90th percentile rank ( volume > prV )
· price is lower than previous price ( z < z )
· price is below 10th percentile rank ( z < prP_ )
dvV = volume < volume and z > z and z > prP and volume < prV_
· The second type background color is reversed ( volume lower, price higher)
🔶 AUTOMATIC COLOUR CHANGE WHEN SWITCHING DARK/LIGHT MODE
🔹 chart.bg_color returns the color of the chart’s background from the "Chart settings/Appearance/Background" field, while chart.fg_color returns a color providing optimal contrast with chart.bg_color .
· Following technique gives you the possibility to pick your own colour for either dark/light time.
· We first retrieve separately the red, green and blue component of the measured chart.bg_color
r = color.r(chart.bg_color)
g = color.g(chart.bg_color)
b = color.b(chart.bg_color)
The following assumption states when all 3 colour components' values are below 80, we are in the dark mode:
isDark = r < 80 and g < 80 and b < 80
Now we can use isDark to automatically show your own dark/light mode colours (chosen at settings), dependable on the mode:
Cheers!
Replica of TradingView's Backtesting Engine with ArraysHello everyone,
Here is a perfectly replicated TradingView backtesting engine condensed into a single library function calculated with arrays. It includes TradingView's calculations for Net profit, Total Trades, Percent of Trades Profitable, Profit Factor, Max Drawdown (absolute and percent), and Average Trade (absolute and percent). Here's how TradingView defines each aspect of its backtesting system:
Net Profit: The overall profit or loss achieved.
Total Trades: The total number of closed trades, winning and losing.
Percent Profitable: The percentage of winning trades, the number of winning trades divided by the total number of closed trades.
Profit Factor: The amount of money the strategy made for every unit of money it lost, gross profits divided by gross losses.
Max Drawdown: The greatest loss drawdown, i.e., the greatest possible loss the strategy had compared to its highest profits.
Average Trade: The sum of money gained or lost by the average trade, Net Profit divided by the overall number of closed trades.
Here's how each variable is defined in the library function:
_backtest(bool _enter, bool _exit, float _startQty, float _tradeQty)
bool _enter: When the strategy should enter a trade (entry condition)
bool _exit: When the strategy should exit a trade (exit condition)
float _startQty: The starting capital in the account (for BTCUSD, it is the amount of USD the account starts with)
float _tradeQty: The amount of capital traded (if set to 1000 on BTCUSD, it will trade 1000 USD on each trade)
Currently, this library only works with long strategies, and I've included a commented out section under DEMO STRATEGY where you can replicate my results with TradingView's backtesting engine. There's tons I could do with this beyond what is shown, but this was a project I worked on back in June of 2022 before getting burned out. Feel free to comment with any suggestions or bugs, and I'll try to add or fix them all soon. Here's my list of thing to add to the library currently (may not all be added):
Add commission calculations.
Add support for shorting
Add a graph that resembles TradingView's overview graph.
Clean and optimize code.
Clean up in a way that makes it easy to add other TradingView calculations (such as Sharpe and Sortino ratio).
Separate all variables, so they become accessible outside of calculations (such as gross profit, gross loss, number of winning trades, number of losing trades, etc.).
Thanks for reading,
OztheWoz
US Fed Rate Hike Historical DatesThe script applies Blue (color can be changed) highlights to the days that the US Federal Reserve Hiked interest rates. Data goes back to the 60's. This can be applied to any chart/timeframe to view how the asset behaved before/during/after Federal Rate Hikes.
****This was updated as of Dec 2022... Any decisions after Dec 2022 will not show up in this indicator.
Versions may be updated periodically to include new data.
Hope this helps. Happy Trades
-SnarkyPuppy
US Fed Rate Cut Historical DatesThe script applies Purple (color can be changed) highlights to the days that the US Federal Reserve Cut interest rates. Data goes back to the 60's. This can be applied to any chart/timeframe to view how the asset behaved before/during/after Federal Rate cuts.
****This was updated as of Dec 2022... Any decisions after Dec 2022 will not show up in this indicator.
Versions may be updated periodically to include new data.
Hope this helps. Happy Trades
-SnarkyPuppy
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.
Market Breadth: Trends & BreakoutsVisualize the percentage of stocks in an index participating in trends and breakouts/breakdowns.
The default data source is the S & P 500: the percent of stocks above/below the 200 and 50 day moving averages, and the percentage of stocks making new 52 week breakouts/breakdowns. You can pick new data sources in the settings.
The blue band represents the percentage of stocks above/below the 200 day moving average. (It's always 100% in width, unlike say Bollinger bands). The thin blue lines are the same but for the 50 day moving average. The red and green areas represent the percentage of stocks making new 52 week highs/lows.
In the example chart you can see a divergence between the market as a whole which continues up and to the right throughout 2021, where as fewer and fewer stocks were above their own 200 day moving average, causing the blue band to trend down. Before the market turns beginning 2022 you can see more stocks making new 52 week lows, even as other stocks make 52 week highs. After the market tops, the percentage of 52 week lows intensifies and the percentage of stocks below their 200 day moving average is already over 50%.
Market Crashes/Chart Timeframes HighlightThis extremely helpful indicator allows you to highlight 7 custom date-based timeframes on your charts.
The default dates selected are what I consider to be the most significant 7 most recent market declines, including and since the 87 flash crash.
Note: The default dates are approximate but good enough to highlight the key timeframes of these pullbacks/crashes/corrections.
It's simple to use and does exactly what it should.
I created this indicator to make it easier when looking at the overall story of a chart. I found it helpful to highlight these areas to see how a market or equity has responded during these significant market pullbacks.
The highlight alone I’ve found helpful, and it becomes more powerful if you combine it with your own trusted trade system.
Also, to get the most out of using the default dates it’s important to understand the narrative behind each pullback/crash. Here’s the list of what I consider significant pullbacks:
Black Monday - Oct 87
1990s Recession - Jul 90 to Mar 91
Dot Com Bubble - 2000 to 2002 or so
Real Estate 2008 Crisis - I choose 2007-2009 to cover full insider knowledge and aftermath
2016 - 2018 - This isn't seen as a pullback, but I have it as significant because in many markets and equities, this was an almost equal percentage pullback as 2008. See Notes below
2020 Crash - Covid-19 and related shenanigans pullback
April 2021 to August 2022 - I believe we are in a current SHORT cycle so I've highlighted April 2021 as the start of what might be the start of a major decline testing Dot Com or lower levels.
A few notes on the above.
You'll find on most of the pullbacks listed above most equities and related markets behave similarly or have similar patterns.
The 2016-18 pullback is the most difficult to track. For instance, GE in this timeframe had a -80% decline, whereas BA depending on how you want to measure it had a 50-110% gain.
Correlation Coefficient: Visible Range Dynamic Average R -Correlation Coefficient with Dynamic Average R (shows R average for the visible chart only, changes as you zoom in or out)
-Label: Vis-Avg-R = Visable Average R
-the Correlation Coefficient function for Pearson's R is taken from "BA🐷 CC" indicator by @balipour (highly recommended; more thorough treatment of R and other stats, but without the dynamic average)
-I wrote this primarily to add a dynamic Average R, showing correlation for arbitrary start times/end times; whether it be the last month, last year, of some specific period from the past (backtest mode)
-I have been using this to get an idea of correlation regimes over time between Bonds vs Stocks (ZB1! vs ES1!).
-As you see from the above, most of 2022 has seen an unusually strong positive correlation between Bonds and Stocks
~~inputs:
-lookback length for calculation of R
-Backtest mode (true by default): displays Average R for ONLY the visible range displayed on any part of chart history (LHS to RHS of screen only)
-source for both Ticker and compared Asset (close, open, high, low, ohlc4.. etc)
~~some other assets worth comparing:
Aussie vs Gold; Aussie vs ES; Btc vs ES; Copper vs ES
