Top12/Bottom88 Weighted Ratio I multiplied the price of each of the top QQQ holdings by their percentage weight, and the bottom 88 holdings for a total of 100. I divide the top 12 weighted price by the bottom 88 weighted price. So I can see when money is flowing in and out of the megacaps. It needs to be updated every quarter, which I may need to do now....
In den Scripts nach "北京地铁3号线和12号线线路图" suchen
Recessions & crises shading (custom dates & stats)Shades your chart background to flag events such as crises or recessions, in similar fashion to what you see on FRED charts. The advantage of this indicator over others is that you can quickly input custom event dates as text in the menu to analyse their impact for your specific symbol. The script automatically labels, calculates and displays the peak to through percentage corrections on your current chart.
By default the indicator is configured to show the last 6 US recessions. If you have custom events which will benefit others, just paste the input string in the comments below so one can simply copy/paste in their indicator.
Example event input (No spaces allowed except for the label name. Enter dates as YYYY-MM-DD.)
2020-02-01,2020-03-31,COVID-19
2007-12-01,2009-05-31,Subprime mortgages
2001-03-01,2001-10-30,Dot-com bubble
1990-07-01,1991-03-01,Oil shock
1981-07-01,1982-11-01,US unemployment
1980-01-01,1980-07-01,Volker
1973-11-01,1975-03-01,OPEC
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.
Adaptive Price Channel StrategyThis strategy is an adaptive price channel strategy based on the Average True Range (ATR) indicator and the Average Directional Index (ADX). It aims to identify sideways markets and trends in the price movements and make trades accordingly.
The strategy uses a length parameter for the ATR and ADX indicators, which determines the length of the calculation for these indicators. The strategy also uses an ATR multiplier, which is multiplied by the ATR to determine the upper and lower bounds of the price channel.
The first step of the strategy is to calculate the highest high (HH) and lowest low (LL) over the specified length. The ATR is also calculated over the same length. Then the strategy calculates the positive directional indicator (+DI) and negative directional indicator (-DI) based on the up and down moves in the price, and uses these to calculate the ADX.
If the ADX is less than 25, the market is considered to be in a sideways phase. In this case, if the price closes above the upper bound of the price channel (HH - ATR multiplier * ATR), the strategy enters a long position, and if the price closes below the lower bound of the price channel (LL + ATR multiplier * ATR), the strategy enters a short position.
If the ADX is greater than or equal to 25 and the +DI is greater than the -DI, the market is considered to be in a bullish phase. In this case, if the price closes above the upper bound of the price channel, the strategy enters a long position. If the ADX is greater than or equal to 25 and the +DI is less than the -DI, the market is considered to be in a bearish phase. In this case, if the price closes below the lower bound of the price channel, the strategy enters a short position.
The strategy exits a position after a certain number of bars have passed since the entry, as specified by the exit_length input.
In summary, this strategy attempts to trade in accordance with the prevailing market conditions by identifying sideways markets and trends and making trades based on price movements within a dynamically-adjusted price channel.
This strategy takes a read on the market and either takes a channel strategy or trades volatility based on current trend. Works well on 2, 3 ,4, 12 hour for BTC. It’s my first attempt and creating a strategy. I am very interested in constructive criticism. I will look into better risk management, maybe a trailing stop loss. Other suggestions welcome. This is my first attempt at a strategy.
Here are the settings I used.
Inputs
Length 20
Exit 10
ATR 3.2
Dates I picked when I got into Crypto
Properties
Capital 1000
Order size 2 Contracts
Pyramiding 1
Commission .05
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!
COT-index rangeA graph showing the commercials (part of COT-data) positioning in relation to its own range, X periods back. I usually choose the look-back period to equal approximately one year. This will be around 52 on a weekly chart and 250 on a daily chart.
In my opinion a high data-point for the commercials is bullish and vice versa. But instead of only looking att absolute values I now look more at how the commercials are positioned compared to the previous 12 och 6 months.
Example:
a) if COT-index range = 0.8, then the commercials are in the 80th percentile for this specific look-back period, i.e. the commercials has only been more bullish 20% of the time and more bearish 80% of the time.
b) a) if COT-index range = 0.5, then the commercials are in the 50th percentile for this specific look-back period, i.e. the commercials has been more bullish 50% of the time and more bearish 50% of the time.
c) if COT-index range = 0.2, then the commercials are in the 20th percentile for this specific look-back period, i.e. the commercials has been more bullish 80% of the time and more bearish 20% of the time.
In other words, a high reading is bullish and a low reading is bearish.
Trend Reversal System with SR levelsHello All,
This is the Trend Reversal System with Support/Resistance levels script. long time ago I published it as closed source but now I upgraded it and and published as open-source with a different name. I hope it would be useful for you all while trading/analyzing.
The script has some parts in it: Setup, Count, SR levels, Risk levels & Targets . Now lets check them:
Setup Part: it has two part, Buy or Sell Setup. one of them can be active only. Buy setup: if current close checks if current is lower/equal than the close of the 5. bar. if yes then the script increases number of buy setup. and if it reaches 9 then the script checks if current low is lower/equal than the lows of last 3. and 4. bars, or if the low of the last bar is lower/equal than the lows of last 3. and 4. bars. if yes then the script increases the buy setup by 1. if these conditions met then it puts the label 'S' , same for Sell setup. S labels on both setup are potential reversals.
Count Part: If buy or sell setup reaches the 9 then Count part starts from 1. lets see buy count: If current close is lower/equal than the low of the 3. bar and buy count is lower than 12 or low of the bar 13 is less than or equal to the close of bar 8 then buy count increase or it's completed. if it's completed then the script puts C label, and it's potential reversal. of course there are some conditions that can cancel the count buy/sell or recycle/restart.
By using Setup and Count levels the script can show Support/Resistance Levels, Risk levels & Targets. SR levels are potential reversal levels.
Lets see some example screenshots:
Support/Resistance levels:
Potential Reversal levels and how setup/counts are shown:
Count part can recycle and the script shows it as 'R' , ( you can see the conditions for Recycle in the script ):
Count can be cancelled and and it's shown as 'x'
If the scripts find 9 on Setup or 13 on Count then it checks if it's a good level to buy/sell and if it decides it's good level then it shows TRSSetup Buy/Sell or TRSCount Buy/Sell and also shows the target. in following example the script checks and decide it's a good level to take long position. it can be aggressive or conservative, Conservative is recommended.
Enjoy!
Optimized Zhaocaijinbao strategyIntroduction:
The Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It generates buy and sell signals by using a combination of exponential moving averages, moving averages, volume and slope indicators. It generates buy signals when the stock is above the 35-day moving average, the trading volume is higher than the 20-day moving average, and the stock is in an upward trend on a weekly timeframe."招财进宝" is a Chinese phrase that can be translated to "Attract Wealth and Bring in Treasure" in English. It is a common expression used to wish for good luck and prosperity in various contexts, such as in business or personal finances.
Highlights:
The strategy has several special optimizations that make it unique.
Firstly, the strategy is optimized for T+1 trading in the Chinese stock market and is only suitable for long positions. The optimizations are also applicable to international stock markets.
Secondly, the trend strategy is optimized to only show indicators on the right side and oscillations. This helps to prevent false signals in choppy markets.
Thirdly, the strategy uses a risk factor for dynamic position sizing to ensure position sizes are adjusted according to the current net asset value and risk preferences. This helps to lower drawdown risks.
The strategy has good resilience even without using stop loss modules in backtesting, making it suitable for trading hourly, 2-hourly, and daily K-line charts (depending on the stock being traded). We recommend experimenting with backtesting using SSE 1-hour or 2-hour or daily Kline charts.
Backtesting outcomes:
The strategy was backtested over the period from October 13th, 2005 to April 14th, 2023, using daily candlestick charts for the commodity code SSE:600763, with a currency of CNY and tick size of 0.01. The strategy used an initial capital of 1,000,000 CNY, with order sizes set to 10% equity and a pyramid of 1 order. The strategy also had a Max Position Size of 0.01 and a Risk Factor of 2.
Here is a summary of the performance of the trading strategy:
Total net profit: 288,577.32 CNY, representing a return of 128.86%
Total number of closed trades: 61
Winning trades: 37, representing a win rate of 60.66%
Profit factor: 2.415
Largest losing trade: 222,021.46 CNY, representing a loss of 14.08%
Average trade: 21,124.22 CNY, representing a return of 3.1%
Average holding period for all trades: 12 days
Conclusion:
In conclusion, the Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It is suitable for both Chinese stocks and global stocks. While the Optimized Zhaocaijinbao strategy has performed well in backtesting, it is important to note that past performance is not a guarantee of future results. Traders should conduct their own research and analysis and exercise caution when using any trading strategy.
Moonhub Cycle IndexMoonhub Cycle Index is a composite index derived from three popular technical analysis indicators: Moving Average Convergence Divergence (MACD), Schaff Trend Cycle (STC), and Detrended Price Oscillator (DPO). The indicator is designed to help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
Key components of the indicator include:
Input Parameters:
COEMA Length (len_DIema): The length of the Exponential Moving Average (EMA) applied to the Custom Index. Default is set to 9.
COSMA Length (len_DIsma): The length of the Simple Moving Average (SMA) applied to the Custom Index. Default is set to 30.
Indicators:
MACD: A momentum oscillator that shows the relationship between two moving averages of a security's price. It is calculated using the difference between the 12-period and 26-period EMA, and a 9-period EMA (signal line) of the MACD.
STC: A cyclic indicator that identifies cyclical trends in the market. It is calculated using the Stochastic oscillator formula applied to the close, high, and low prices over a 10-period lookback window.
DPO: A price oscillator that eliminates the trend from price data to focus on underlying cycles. It is calculated using a custom function that shifts the price by half the length and subtracts the SMA from the shifted price.
Custom Index: The composite index is calculated by taking the average of the MACD line, STC, and DPO.
COEMA and COSMA: Exponential and Simple Moving Averages applied to the Custom Index using the lengths specified by the input parameters (len_DIema and len_DIsma).
Plots: The Custom Index, COEMA, and COSMA are plotted with different colors and line widths to visualize their interaction and provide insights into potential market trends.
This Custom Index Indicator can be useful for traders who want to analyze the market using a combination of these indicators to make more informed decisions. It can also help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
FX Sessions & Killzones ETJust another sessions indicator. Among all the many existing ones, I didn't find anything simple that would cover my needs and that would actually be correct.
New York time is forced here for plotting the stripes so you don't need to worry about the time zone currently set on your chart. The indicator will be accurate during Daylight Saving Time (which, in 2023 for example, started on Sunday, 12 March , 02:00:00 and will be in effect until Sunday, 5 November, 02:00:00).
ADX Trend FilterADX Trend Filter Indicator is a traditional ADX indicator with a different presentation. its consist of two indicators EMA TREND and ADX / DMI
About Indicator:
1. BAND / EMA band to represent EMA Trend of EMA-12 and EMA-50
(Band is plotted at level-20 which is the Threshold level of DMI / ADX indicator)
2. Histogram showing the direction of ADX / DMI trend
3. Area behind the histogram showing ADX/DMI strength
How to use?
1. Histogram represents current Trend Red for Bearish / Green for Bullish
2. Area behind the histogram represents Strength of ADX / DMI Threshold level is 0-20(represented as band). (Area below the Band is Sideways)
3. Band represents the current MA Trend.
4. Buy Sell signals are plotted as triangles in red/green obtained from ADX / DMI Crossovers
Buy Signal (Green Triangle on band- ADX Crossover)
1.Band below Histogram must be Green
2.Histogram must be green
3.Area behind histogram must be above the lower trend band (20level) and visible
Sell Signal (Red Triangle on band- ADX Crossover)
1.Band below Histogram must be Red
2.Histogram must be Red
3.Area behind histogram must be above the lower trend band (20level) and visible
Alerts provided for ADX crossovers.
SAR MACDSAR MACD is an idea of implementing Directional MACD with Parabolic SAR to exactly detect and confirm Trend. This p-SAR MACD consist of a HYBRID MACD which acts as MACD TREND oscillator, MACD Oscillator, PSAR Indicator combined with MA line. thus Fake MACD Signals can be eliminated using this SAR MACD. Sideways can be detected using Threshold Levels must be adjusted based on timeframe.
Indicators Hybrid model contains:
1.MACD (12,26,9) Standard with MA Crossovers
2.MACD Trend
3.Parabolic SAR with 0.02
4.Threshold level - indicates Sideways
How to use.
Histogram:
-> HIST MODE: normal MACD indicator
MA Line Color is based on PSAR Direction Blue-Up/ Pink -Down
A crossover upside with a Blue MA line denotes Up confirmation
A Crossover downwards with a red MA line denotes Down Confirmation
Additionally Histogram above zero line and below zero line are to be confirmed
-> MACD MODE: MACD Trend indicator
MA Line Color is based on PSAR Direction Blue-Up/ Pink -Down
A crossover upside with a Blue MA line denotes Up confirmation
A Crossover downwards with a red MA line denotes Down Confirmation
Additionally Histogram above zero line and below zero denotes long term Trend
-> Histogram Color: Indicates candles direction
Yellow indicates Unconfirmed Direction
Green Indicates up direction
Red Indicates Down Direction
Buy Condition:
MA Color - Blue
Histogram- Above Zero
Histogram/Candle -Green
MA Crossover is must
Sell Condition:
MA Color - Red
Histogram- Below Zero
Histogram/Candle -Red
MA Cross under is must
Warning: Must not be used as a standalone indicator. Use for confirmation of your Buy Sell Signals and Entry only.
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.
Ignition Cha Cha ChaIgnition Cha Cha Cha (ICCC) is a 3 color coded moving average indicator which numerically quantify the angle of their trends. I have labeled them as fast, medium and slow. The trend colors are Green for bullish, Red for bearish and Grey for sideways. The sideways movement can be user defined for all 3 in the settings under Threshold. If you regard for example anything under 10º as sideways then place 10 in the corresponding threshold and any angle under 10º will give a grey moving average and a grey labeled text. I use this chart in several ways. If you don't want moving averages all over your Chartistic Masterpiece you can turn off the plots and leave the numeric angles which will give you an overview of the trend. Conversely if you want to make the ultimate trend chart you can setup a 4 chart layout, Weekly, Daily, 12 hour and 4 hour and add the indicator with 200/50/25 moving averages and look for confluence. I find the best way for this is turn off the candles and use the moving averages with the numeric labels. You also have the ability to turn off and on different aspects of the indicator so that there is good control over its look. Also I have given the indicator lots of Alert presets for all 3 of the moving averages so you can avoid demented screen-stairing. Please forgive the name, my mother made me do Ballroom dancing lessons as a kid.
RS RatingHello everyone.
The RS Rating (or Relative Strenght Rating) is a metric that tracks a stock's price performance relative to the rest of the market. Specifically, it looks at a stock's relative strength over the last 52 weeks.
It allows you to identify at a glance stocks that are outperforming the market and may be poised for further gains.
Designed for break-out traders, trend follower, value investors, the RS Rating can help you identify promising opportunities and make informed investment decisions.
The Rating stands as follow:
- From 1 (worst) to 99 (best)
- 99 rating means the stock is outperforming 99% of all stocks in terms of relative share price performance over the last 52 weeks.
The RS Rating is accompanied by the RS line which is a representation of the progress of the asset against the comparative symbol. (Here SP500)
Of course this script is inspired by the IBD rating system.
The results may be equivalent but it is not guaranteed.
This indicator proposes a scoring system in the style of the one proposed by IBD.
Indeed for an optimal result, it would be necessary to compare the relative performance of all actions, which is not yet possible on PineScript.
Here is the formula for calculating the score:
RS Score = 40% * P3 + 20% * P6 + 20% * P9 + 20% * P12
With
P3 = Performance over the last 3 months
P6 = Performance over the last 6 months
P9 = Performance over the last 9 months
P12 = Performance over the last 12 months
There is no equivalent solution for the moment on TradingView.
The rating score will only appear on the daily timeframe.
For now it's my pleasure to share!
ICT Algorithmic Macro Tracker° (Open-Source) by toodegreesDescription:
The ICT Algorithmic Macro Tracker° Indicator is a powerful tool designed to enhance your trading experience by clearly and efficiently plotting the known ICT Macro Times on your chart.
Based on the teachings of the Inner Circle Trader , these Time windows correspond to periods when the Interbank Price Delivery Algorithm undergoes a series of checks ( Macros ) and is probable to move towards Liquidity.
The indicator allows traders to visualize and analyze these crucial moments in NY Time:
- 2:33-3:00
- 4:03-4:30
- 8:50-9:10
- 9:50-10:10
- 10:50-11:10
- 11:50-12:10
- 13:10-13:50
- 15:15-15:45
By providing a clean and clutter-free representation of ICT Macros, this indicator empowers traders to make more informed decisions, optimize and build their strategies based on Time.
Massive shoutout to @reastruth for his ICT Macros Indicator , and for allowing to create one of my own, go check him out!
Indicator Features:
– Track ongoing ICT Macros to aid your Live analysis.
- Gain valuable insights by hovering over the plotted ICT Macros to reveal tooltips with interval information.
– Plot the ICT Macros in one of two ways:
"On Chart": visualize ICT Macro timeframes directly on your chart, with automatic adjustments as Price moves.
Pro Tip: toggle Projections to see exactly where Macros begin and end without difficulty.
"New Pane": move the indicator two a New Pane to see both Live and Upcoming Macro events with ease in a dedicated section
Pro Tip: this section can be collapsed by double-clicking on the main chart, allowing for seamless trading preparation.
This indicator is available only on the TradingView platform.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
ICT Macros by CryptoforICT Macros by Cryptofor
Time periods in which the price is most volatile. At this time, the algorithm is programmed to attack liquidity or fill a significant FVG from which the OF can continue.
Plots of macros:
1. London Macros:
02:33 - 03:00
04:03 - 04:30
2. New York AM Macros:
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
3. New York Lunch + PM Macros:
11:50 - 12:10
13:10 - 13:40
15:15 - 15:45
Features:
Flexible line settings
Flexible text settings
Display data for all time or for the last 24 hours
Switch for each type of macro
Macro background color settings
Multi-Timeframe Trend IndicatorThe Multi-Timeframe Trend Indicator (MTFTI) is a trend analysis tool designed to help traders quickly and easily assess the market direction across multiple timeframes. With the help of a table to visualize the trends on different timeframes.
Key features:
Multi-timeframe trend indicator for the following timeframes: 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 1 day, and 1 week and average.
Displays trends for selected timeframes in a table.
Considers short and long-term exponential moving averages (EMAs) to determine trends.
Calculation of the average trend for all timeframes.
Display of trends with appropriate coloring for better readability (green for "Up", red for "Down", and intermediate shades for neutral or strong trends).
List of Parameters
Customization of the table's position on the screen (top-left, top-right, middle-left, middle-right, bottom-left, bottom-right).
Setting the lengths of the short and long-term exponential moving averages.
Option to activate or deactivate the display of EMAs for better customization (true by default).
Please note that the MTFTI is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Hikkake Hunter 2.0This script serves as a successor to a previous script I wrote for identifying Hikkakes nearly two years ago.
The old version has been preserved here:
█ OVERVIEW
This script is a rework of an old script that identified the Hikkake candlestick pattern. While this pattern is not usually considered a part of the standard candlestick patterns set, I found a lot of value when finding a solution to identifying it. A Hikkake pattern is a 3-candle pattern where a middle candle is nested in between the range of the prior candle, and a candle that follows has a higher high and a higher low (bearish setup) or a lower high and a lower low (bullish setup). What makes this pattern unique is the "confirmation" status of the pattern; within 3 candles of this pattern's appearance, there must be a candle that closes above the high (bullish setup) or below the low (bearish setup) of the second candle. Additional flexibility has been added which allows the user to specify the number of candles (up to 5) that the pattern may have to confirm after its appearance.
█ CONCEPTS
This script will cover concepts mainly focusing on candlestick analysis, price analysis (with higher timeframes), and statistical analysis. I believe there is also educational value presented with the use of user-defined-types (UDTs) in accomplishing these concepts that I hope others will find useful.
Candlestick Analysis - Identification and confirmation of the patterns in the deprecated script were clunky and inefficient. While the previous script required the use of 6 candles to perform the confirmations of patterns (restricted solely to identifying patterns that confirmed in 3 candles or less), this script only requires 3 candles to identify and process patterns by utilizing a UDT representing a 'pattern object'. An object representing a pattern will be created when it has been identified, and fields within that object will be set for processing by the functions it is passed to. Pattern objects are held by a var array (values within the array persist between bars) and will be removed from this array once they have been confirmed or non-confirmed.
This is a significant deviation from the previous script's methods, as it prevents unnecessary re-evaluations of the confirmation status of patterns (i.e. Hikkakes confirmed on the first candle will no longer need to be checked for confirmations on the second or third; a pitfall of the deprecated version which required multiple booleans tracking prior confirmation statuses). This deviation is also what provides the flexibility in changing the number of candles that can pass before a pattern is deemed non-confirmed.
As multiple patterns can be confirmed simultaneously, this script uses another UDT representing a linked-list reduction of the pattern object used to process it. This liked-list object will then be used for Price Analysis.
Price Analysis - This script employs the use of a UDT which contains all the returns of confirmed patterns. The user specifies how many candles ahead of the confirmed pattern to calculate its return, as well as where this calculation begins. There are two settings: FROM APPEARANCE and FROM CONFIRMATION (default). Price differences are calculated from the open of the candle immediately following the candle which had confirmed the pattern to the close of the candle X candles ahead (default 10). ( SEE FEATURES )
Because of how Pine functions, this calculation necessitates a lookback on prior candles to identify when a pattern had been confirmed. This is accomplished with the following pseudo-code:
if not na(confirmed linked-list )
for all confirmed in list
GET MATRIX PLACEMENT
offset = FROM CONFIRMATION ? 0 : # of candles to confirm
openAtFind = open
percent return = ((close - openAtFind) / openAtFind) * 100
ADD percent return TO UDT IN MATRIX
All return UDTs are held in a matrix which breaks up these patterns into specific groups covered in the next section.
Higher Timeframes - This script makes a request.security call to a higher timeframe in order to identify a price range which breaks up these patterns into groups based on the 'partition' they had appeared in. The default values for this partitioning will break up the chart into three sections: upper, middle, and lower. The upper section represents the highest 20% of the yearly trading range that an asset has experienced. The lower section represents the trading range within a third (33%) of the yearly low. And the middle section represents the yearly high-low range between these two partitions.
The matrix containing all return UDTs will have these returns split up based on the number of candles required to confirm the pattern as well as the partition the pattern had appeared in. The underlying rationale is that patterns may perform better or worse at different parts of an asset's trading range.
Statistical Analysis - Once a pattern has been confirmed, the matrix containing all return UDTs will be queried to check if a 'returnArray' object has been created for that specific pattern. If not, one will be initialized and a confirmed linked-list object will be created that contains information pertinent to the matrix position of this object.
This matrix contains the returns of both the Bullish and Bearish Hikkake patterns, separated by the number of candles needed to confirm them, and by the partitions they had appeared in. For the standard 3 candles to confirm, this means the matrix will contain 18 elements (dependent on the number of candles allowed for confirmations; its size will range from 12 to 30).
When the required number of candles for Price Analysis passes, a percent return is calculated and added to the returnArray contained in the matrix at the location derived from the confirmed linked-list object's values. The return is added, and all values in the returnArray are updated using Pine's built in array.___ functions. This returnArray object contains the array of all returns, its size, its average, the median, the standard deviation of returns, and a separate 3-integer array which holds values that correspond to the types of returns experienced by this pattern (negative, neutral, and positive)*.
After a pattern has been confirmed, this script will place the partition and all of the aforementioned stats values (plus a 95% confidence interval of expected returns) related to that pattern onto the tooltip of the label that identifies it. This allows users to scroll over the label of a confirmed pattern to gauge its prior performance under specific conditions. The percent return of the specific pattern identified will later be placed onto the label tooltip as well. ( SEE LIMITATIONS )
The stats portion of this script also plays a significant role in how patterns are presented when using the Adaptive Coloring mode described in FEATURES .
*These values are incremented based on user-input related to what constitutes a 'negative' or 'positive' return. Default values would place any return by a pattern between -3% and 3% in the 'neutral' category, and values exceeding either end will be placed in the 'negative' or 'positive' categories.
█ FEATURES
This script contains numerous inputs for modifying its behavior and how patterns are presented/processed, separated into 5 groups.
Confirmation Setting - The most important input for this script's functioning. This input is a 'confirm=true' input and must be set by the user before the script is applied to the chart. It sets the number of candles that a pattern has to confirm once it has been identified.
Alert Settings - This group of booleans sets which types of alerts will fire during the scripts execution on the chart. If enabled, the four alerts will trigger when: a pattern has been identified, a pattern has been confirmed, a pattern has been non-confirmed, and show the return for that confirmed pattern in an alert. Because this script uses the 'alert' function and not 'alertcondition', these must be enabled before 'any alert() function call' is set in TradingView's 'alerts' settings.
Partition Settings - This group of inputs are responsible for creating (and viewing) the partitions that breaks the returns of the patterns identified up into their respective groups. The user may set the resolution to grab the range from, the length back of this resolution the partitions get their values from, the thresholds which breaks the partitions up into their groups, and modify the visibility (if they're shown, the colors, opacity) of these partitions.
Stats Settings - These inputs will drastically alter how patterns are presented and the resulting information derived from them after their appearance. Because of this section's importance, some of these inputs will be described in more detail.
P/L Sample Length - Defines the number of candles after the starting point to grab values from in the % return calculation for that pattern.
P/L Starting Point - Defines the starting point where the P/L calculation will take place. 'FROM APPEARANCE' will set the starting point at the candle immediately following the pattern's appearance. 'FROM CONFIRMATION' will place the starting point immediately following the candle which had confirmed the pattern. ( SEE LIMITATIONS )
Min Returns Needed - Sets how many times a specific pattern must appear (both by number of candles needed to confirm and by partition) before the statistics for that pattern are displayed onto the tooltip (and for gradient coloration in Adaptive Coloring mode).
Enable Adaptive Coloring - Changes the coloration of the patterns based on the bullish/bearishness of the specified Gradient Reference value of that pattern compared to the Return Tolerance values OR the minimum and maximum values of that specified Gradient Reference value contained in the matrix of all returns. This creates a color from a gradient using the user-specified colors and alters how many of the patterns may appear if prior performance is taken into account.
Gradient Reference - Defines which stats measure of returns will be used in the gradient color generation. The two settings are 'AVG' and 'MEDIAN'.
Hard Limit - This boolean sets whether the Return Tolerance values will not be replaced by values that exceed them from the matrix of returns in color gradient generation. This changes the scale of the gradient where any Gradient Reference values of patterns that exceed these tolerances will be colored the full bullish or bearish gradient colors, and anything in between them will be given a color from the gradient.
Visibility Settings - This last section includes all settings associated with the overall visibility of patterns found with this script. This includes the position of the labels and their colors (+ pattern colors without Adaptive Coloring being enabled), and showing patterns that were non-confirmed.
Most of these inputs in the script have these kinds of descriptions to what they do provided by their tooltips.
█ HOW TO USE
I attempted to make this script much easier to use in terms of analyzing the patterns and displaying the information to the user. The previous script would have the user go to the 'data window' side bar on TradingView to view the returns of a pattern after they had specified which pattern to analyze through the settings, needlessly convoluted. This aim at simplicity was achieved through the use of UDTs and specific code-design.
To use, simply apply the indicator to a chart, set the number of candles (between 2 and 5) for confirming this specific pattern and adjust the many settings described above at your leisure.
█ LIMITATIONS
Disclaimer - This is a tool created with the hopes of helping identify a specific pattern and provide an informative view about the performance of that pattern. Previous performance is not indicative of future results. None of this constitutes any form of financial advice, *use at your own risk*.
Statistical Analysis - This script assumes that all patterns will yield a NORMAL DISTRIBUTION regarding their returns which may not be reflective of reality. I personally have limited experience within the field of statistics apart from a few high school/college courses and make no guarantees that the calculation of the 95% confidence interval is correct. Please review the source code to verify for yourself that this interval calculation is correct (Function Name: f_DisplayStatsOnLabel).
P/L Starting Point - Because of when the object related to the confirmation status of a pattern is created (specifically the linked-list object) setting the 'P/L Starting Point' to 'FROM APPEARANCE' will yield the results of that P/L calculation at the same time as 'FROM CONFIRMATION'.
█ EXAMPLES
Default Settings:
Partition Background (default):
Partition Background (Resolution D : Length 30):
Adaptive Coloration:
Show Non-Confirmed:
TASC 2023.04 Undersampled Double MA█ OVERVIEW
TASC's April 2023 edition of Traders' Tips features an article entitled "Just Ignore Them: Undersampling The Data As A Smoothing Technique" by John Ehlers, which explores a method for reducing noise through data sampling. This script implements the article's proposed Undersampled Double MA indicator.
█ CONCEPTS
The conventional approach to reducing the impact of noise in the market data on trading rules is to use smoothing filters like moving averages. However, John Ehlers suggests that changing the sample rate of the datastream is a simple and effective way to smooth the data and reduce noise. Specifically, he argues that undersampling the data removes high-frequency components contributing to noisiness. Notably, the elimination of these components produces less lag than that of conventional smoothing filters.
The Undersampled Double MA indicator implemented in this script represents a practical application of smoothing with undersampling. It samples the data at a given rate (for instance, once every five bars, as suggested by Ehlers), then processes the resulting data using a Hann window filter with two different periods, producing two smooth data streams that traders can use in the same way as the combination of two conventional moving averages of different lengths (i.e., fast and slow MAs).
█ CALCULATIONS
The script samples data once every N th bar (by default, N = 5) and smooths the undersampled data with 6-period and 12-period Hann filters, which it plots on the main chart. Users can adjust the sampling period and the periods of each Hann filter to their liking from the inputs in the script settings.
Vigilant Asset Allocation G4 Backtesting EngineThis script was based off of an idea that @CubanEmissary had so the description and some of the code that @CubanEmissary built on TradingView was used.
Vigilant Asset Allocation G4 (VAA G4) is a dual-momentum based investment strategy that aggressively monitors the market and reallocates portfolio funds based on the relative momentums of user-defined risk assets and safety assets. It was created by Wouter Keller and JW Keuning, based on their paper "Breadth Momentum and Vigilant Asset Allocation." In contrast to traditional dual momentum strategies, VAA G4 monitors the market itself through the two asset types. When all risk assets have positive momentum, the portfolio is allocated entirely into the risk asset with the strongest momentum At any other time, the portfolio is allocated entirely into the safety asset with the strongest momentum. The combination of breadth momentum with a very defensive reallocation trigger results in a strategy which captures alpha consistently.
The Strategy Rules:
1. Calculate each asset's momentum score on each monthly close:
momentumScore = (12*(currentMonthlyClose/lastMonthlyClose))+(4*(currentMonthlyClose/thirdLastMonthlyClose))+(2*(currentMonthlyClose/sixthLastMonthlyClose))+(currentMonthlyClose/twelvethLastMonthlyClose)-19
2. If all risk asset momentums are positive, allocate entire portfolio to the risk asset with the strongest momentum.
3. If any risk asset's momentum is negative, allocate entire portfolio to the safety asset with the strongest momentum.
4. Reevaluate at the end of each month.
Caveats:
1. It seems like TradingView only has limited price data for these tickers that are listed in the strategy. So it is best to start the strategy when they all have ample data (~ June 2nd, 2008)
2. This backtesting engine is basic and doesn't account for slippage and trading fees. So I implemented a basic "trading fee" input that will subtract a trading fee whenever the strategy makes a trade at the end of the month.
3. It is assumed in this engine that the trades will be made the exact second a new monthly bar opens up.
4. MUST USE ON MONTHLY CHART. It is hard-coded to work on monthly chart, if you open it on a daily chart , the Sharpe, Sortino, & CAGR calculations might not be right as well as the momentum score
