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:
"12月4号是什么星座" için komut dosyalarını ara
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
MACD & RSI Overlay (Expo)█ Overview
The MACD & RSI Overlay (Expo) trading indicator is a technical analysis tool that combines two popular indicators, the Relative Strength Index (RSI ) and the Moving Average Convergence Divergence (MACD ), and overlays them onto the price chart. The indicator oscillates relative to price, so it plots the RSI and MACD around price while still displaying the same insights as the regular MACD and RSI indicators. This feature gives traders a unique perspective, allowing them to see the relationship between price, momentum, and trend in a single chart.
This indicator is a valuable addition to any trader's technical analysis toolkit, whether they are a beginner or an experienced trader.
█ MACD
█ RSI
The RSI comes with overbought and oversold areas, which can be set by the trader.
█ MACD & RSI
█ Trend Feature
What sets the MACD & RSI Overlay indicator apart is its ability to factor in the underlying trend. This feature makes the indicator more useful than ever before, as traders can use it to filter trades in the direction of the trend. By considering the underlying trend, traders can gain valuable insights into market trends.
█ Benefits
One of the primary benefits of having the MACD and RSI plotted directly on the price chart is that it provides a more intuitive understanding of the relationship between price, momentum, and trend. Traders can quickly identify the direction of the trend by observing the price movement relative to the MACD and RSI lines. In addition, by having these indicators plotted on the chart, traders can quickly identify potential buy and sell signals and develop new trading strategies.
█ How to use
One of the most popular strategies is to use the MACD & RSI Overlay indicator to look for crossings. A crossing occurs when the MACD and RSI lines cross over each other or when they cross over the signal line. These crossings can signal potential trend reversals and momentum shifts. For example, if the MACD line crosses over the signal line from below, it could indicate a bullish signal, while a cross from above could indicate a bearish signal.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Advanced Price Direction AlgorithmPrices can go up or down or falter in their movement.
This code evaluates this by looking at two consecutive bars or sets of bars.
If you put the set size to 1, the current and previous bar is evaluated.
If put to 2, the last2 and the 2 before these are evaluated.
Default is 12 because this seems to coincide with trend changes.
This code provides an advanced way to evaluate what the price does in a sort of three-value Boolean with the values up, down or falter.
I use this code in indicators I develop where price direction is taken into account.
The simple output makes it possible to use it as an indicator on its own.
[Uhokang] Bollinger Band BB EMA SMMA SMA Multy timeframeYou can view indicators from the specified upper timeframe together.
( Bollinger Bands, SMMA, EMA, SMA )
If it is based on a 1-hour bar, you can see indicators for 4-hour bars and 1-day bars at the same time.
=> =>
Minutes
1 => 5 => 30
2 => 10 => 60
3 => 15 => 90
4 => 20 => 120
5 => 30 => 120
6 => 30 => 120
10 => 60 => 240
15 => 60 => 240
30 => 120 => 480
45 => 180 => 450
over Hours
1 => 4 => D
2 => 8 => 2D
3 => 12 => 3D
4 => D => W
D => W => M
W => M => Y
[-_-] DictionaryThe script shows an example implementation of dictionary-like data type which can store key:value pairs (Python style). Both keys and values can have any of the following type:
• string
• integer
• float
• boolean
• color
You can add items of different types to the same dictionary (e.g. key = 12 and value = "value" stored in the same dictionary with key = "key" and value = 0.23).
Under the hood dictionary is a custom Object (see www.tradingview.com), that has two array fields (one for storing keys, another for storing values). Keys and values of different types are converted into a string representation when adding a new item to the dictionary. The value is then converted back to certain type (bool/color/etc.) from that string representation when being retrieved. Script also utilises the new Methods (see www.tradingview.com).
The following methods are implemented:
• init() -> initialises the array fields of dictionary (without this the script throws an error "Array methods can't be called when ID of array is na"
• set(key, value) -> add a new item to dictionary; if an item for given key already exists - change it to new value
• getS(key) -> get value of string type
• getI(key) -> get value of integer type
• getF(key) -> get value of float type
• getB(key) -> get value of boolean type
• getC(key) -> get value of color type
• remove(key) -> removes item from dictionary
• len() -> get length of dictionary (the number of keys)
I could not make just one "get" function that returns any type of value (color/string/etc.), so instead I created a get function for each value type. Example usage:
• you add a string item: dictionary.set(2, "string here")
• you add a float item: dictionary.set(3, 24.56)
• to retrieve first value (key=2) do this: dictionary.getS(2)
• to retrieve second value (key=3) do this: dictionary.getF(3)
Super 6x: RSI, MACD, Stoch, Loxxer, CCI, & Velocity [Loxx]Super 6x: RSI , MACD , Stoch , Loxxer, CCI , & Velocity is a combination of 6 indicators into one histogram. This includes the option to allow repainting.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
What is CCI?
The Commodity Channel Index ( CCI ) measures the current price level relative to an average price level over a given period of time. CCI is relatively high when prices are far above their average. CCI is relatively low when prices are far below their average. Using this method, CCI can be used to identify overbought and oversold levels.
What is RSI?
The relative strength index is a technical indicator used in the analysis of financial markets. It is intended to chart the current and historical strength or weakness of a stock or market based on the closing prices of a recent trading period. The indicator should not be confused with relative strength .
What is Stochastic?
The stochastic oscillator, also known as stochastic indicator, is a popular trading indicator that is useful for predicting trend reversals. It also focuses on price momentum and can be used to identify overbought and oversold levels in shares, indices, currencies and many other investment assets.
What is Loxxer?
The Loxxer indicator is a technical analysis tool that compares the most recent maximum and minimum prices to the previous period's equivalent price to measure the demand of the underlying asset.
What is Velocity?
In simple words, velocity is the speed at which something moves in a particular direction. For example as the speed of a car travelling north on a highway, or the speed a rocket travels after launching.
How to use
Long signal: All 4 indicators turn green
Short signal: All 4 indicators turn red
Included
Bar coloring
Alerts
Zazzamira 50-25-25 Trend System Alerts OnlyPublishing my trading system script. It consist of several conditions to happen in order to open a trade. Work best on ES/MES 5 minute timeframe.
I like to use it with this settings:
- UTC -6 (don't tick Exchange Timezone)
and rest as default
To enter a trade, the following conditions must be met: Entry 1: the opening range (8:30AM - 9:15AM UTC-6) must be defined and the price must close above or below the opening range on the 5-minute timeframe. This entry condition defines the trade direction (above = long / below = short). Once the opening range is defined, the Trend-Based Fib Extension is applied from the range high to the range low (and vice versa). Fib levels are required for Exit conditions. Entry 2: the 8 - 27 - 67 - 97 EMAs must be defined. If the EMAs value order is 8 > 27 > 67 > 97, long-only trades are allowed. If the EMAs value order is 8 < 27 < 67 < 97, short-only trades are allowed. This entry condition filters fake breakouts of Entry 1. Entry 3: no trades are allowed after 12:59 UTC-6 (2PM EST). Entry 4: if Entry 1, Entry 2, and Entry 3 conditions are valid and the price hasn't reached the 23.6% Fib line, an entry order can be set at the range high/long with 4 contracts. To exit a trade, the following conditions must be met: Exit 1 (Stop loss): set a trailing stop based on 2.1x ATR (14) from entry. Exit 2: take 50% profits at the 23.6% Fib and leave trailing stop untouched. Exit 3: if Exit 2 triggers, take 50% (25% of total entry) off at 61.8% Fib, leaving Exit 2 trailing stop values valid. Exit 4: exit the full position at the FIB 100% value. Exit 5: all trades must be closed at 3pm UTC-6 (4PM EST). So basically Take Profit are 50%-25%-25% of position.
Code has been written by © Hiubris_Indicators who has been an amazing coder and gave me the possibility to make this script public so a really big shoutout to him.
This indicator only works for alerts, please check version without alerts to backtest or tweaks. This indicator is meant to be used to automate the system via webhooks
Expected Move Plotter [CHE]Expected Move Plotter
"There is magic in everything new."
Introduction:
This script is an indicator for financial trading that plots the expected movement of a security based on the average range over the last five periods. The script is written in Pine Script, a high-level programming language used for creating technical indicators, strategies, and other trading tools for the TradingView platform.
Inputs:
Percentage of Open and Close: This input specifies the percentage of the open and close price to use for the expected movement.
Time Periods: The script takes the different time periods into account and translates them to either 60 seconds, 240 seconds, 1 day, 3 days, 7 days, 1 month, 3 months or 12 months.
Calculation:
The script uses the "Open" and "High"/"Low" values of the last 5 periods to calculate the average range and plots the expected movement above and below the current open price. The plot is either green or red depending on whether the expected move is above or below the current close.
Code Breakdown:
The script starts by defining three integer constants: MS_IN_MIN, MS_IN_HOUR, and MS_IN_DAY, which represent the number of milliseconds in a minute, hour, and day, respectively.
The function timeStep_translate() returns a string that represents the timeframe for a chart based on the current timeframe. The function first converts the chart's timeframe to milliseconds and then uses a switch statement to determine the string value to be returned based on the number of milliseconds in the timeframe.
The script then retrieves the data for the open, high, and low values for the last five periods. The high and low values are used to calculate the average range, which is then used to plot the expected movement above and below the current open price.
Conclusion:
This script provides traders with a visual representation of the expected movement of a security based on the average range over the last five periods. It takes different time periods into account and provides a clear indication of whether the expected move is above or below the current close. The script is easy to use and provides a useful tool for traders looking to make informed trading decisions.
Best regards Chervolino
Strategy Myth-Busting #12 - OSGFC+SuperTrend - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 12th one is an automated version of the "The Most Powerful Tradingview Buy Sell Signal Indicator " strategy from "Power of Trading" who doesn't make any official claims but watching how he trades with this, it on the surface looked promising. The strategy author uses this on the 15 min strategy on mostly FOREX. Unfortunately as indicated by the backtest results below, we were not able to substantiate any good positive trading metrics from this, be it Profit, Markdown, Num Of Trades etc. This does seem to do okay with some entries but perhaps adding another indicator to this to filter out more noise might make it better. At least how this strategy is presented now, this is not something I recommend anyone use.
This strategy uses a combination of 2 open-source public indicators:
SuperTrend by TradingView Internal
One-Sided Gaussian Filter w/ Channels By Loxx
The SuperTrend indicator and the One-Sided Gaussian Filter complement each other by providing a more complete and accurate picture of market trends. The SuperTrend indicator is used to identify trends. It does this by calculating a moving average of the underlying securities price and then comparing the current price to the moving average. When the current price is above the moving average, the trend is considered bullish, and when it is below, the trend is considered bearish.
The One-Sided Gaussian Filter is a mathematical tool that is used to smooth out fluctuations in financial data. It does this by removing random noise from the data, making it easier to identify patterns and trends.
When the SuperTrend indicator is used in conjunction with the One-Sided Gaussian Filter, the smoothed price data generated by the filter is used as the input for the SuperTrend calculation. This provides a more accurate representation of market trends and helps to eliminate false signals generated by short-term price movements. As a result, the SuperTrend indicator is able to more accurately identify the underlying trend in the market and provide traders with a cleaner and more reliable signal to act upon.
In summary, the SuperTrend indicator and the One-Sided Gaussian Filter complement each other by providing a more accurate and reliable representation of market trends, resulting in improved performance for traders.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Trading Rules
15 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
SuperTrend and OSGFC generate buy signal
Close Buy on Gaussian generating a sell signal
Short Condition
SuperTrend and OSGFC generate sell signal
Close Buy on Gaussian generating a buy signal
Arron Meter With Alerts [Skiploss]Arron Meter With Alerts is an indicator to identify the trend, and a meter shows the percentage of AroonUP and AroonDown.
Alert Settings
It will be part of a display of bullish and bearish signals by using the condition of the upper line cross lower line and HMA 200 cross under/over EMA 12, and also upper/lower line must be higher than 70%
Stock Relative Strength Power IndexAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade.
This idea recently came out of some discussions I stumbled across in a trading group I am a part of regarding Relative Strength and Relative Weakness (shortened to RS and RW from here on out). The whole mechanism behind this trading system is to filter out underperforming securities relative to the current market direction to be in only the strongest or weakest stocks when the market is currently experiencing a bullish or bearish cycle. The idea behind this is there is no point in parking your money into a stock that is treading water or even going down if the market is making strong moves upwards. At that point, you are at worst losing money, and at best trading equal to the index/ETF, in which case the argument is why are you not just trading the index/ETF instead? RS or RW will filter out these sector laggards and allow you to position yourself into strong (or the strongest) stocks at any given time to help improve portfolio performance. Further, not only does it protect your position should the market shift against you briefly, it also often sees exceptional performance in the same cycle. For example, if $SPY makes a 5% move over the course of a month, a stock with RS/RW may make a 10% move, or more, allowing you to see increased profit potential.
RS/RW is based on the idea of performance, that is the raw percent change of a security over a given time period relative to a benchmark. This benchmark is often the S&P500 (ES/SPX/SPY and their derivatives). I have to stress that this is not beta, which measures the volatility of a stock over a given period (i.e. if $SPY moves $1, $NVDA will often move $1.74). This is a measurement of the market (i.e. $SPY) has moved 1% over the course of a day, $NVDA has moved 8% over the course of the day. This is very often used as a signal of institutional interest as apart from some very unique moments, retail traders cannot and will not provide enough market pressure to move a market outside of a stock's normal trading range, nor will they outperform the sector or market as a whole consistently over time without some big money to make them move. The problem with running strict performance analysis (i.e. % change from period T ago to period T + n at present) is that while it gives us a baseline of how much the stock has moved, it doesn't overall mean much. For instance, if a $100 stock has moved 5% today, but has been experiencing a period of increased volatility and it's Average True Range (ATR) (the amount a stock will move over X number of periods, on average) is $7, performance seems impressive but is actually generally fairly weak to what the stock has been doing recently. Conversely, if we take a second stock, this time worth $20, and it too has moved 5% in one day but has an ATR of only $0.25, that stock has made an exceptional move and we want to be part of that.
Here, I have created an indicator called the Stock Relative Strength Power Index. This takes the stock's rate of change (ROC) (the % move it has made over X number of periods), the stock's normalized ATR (the ATR represented as a percentage instead of a raw value), and compares these to one another to get the "Power Rating": a representation of the true strength of a stock over X number of periods. The indicator does two things. First, the raw ROC is divided by the stock's normalized ATR to assess whether the stock is moving outside of its normal range of variation or not. Second, since we are interested in trading only stocks with exceptional RS/RW to the market, I have also applied this same calculation to the S&P500 ($SPY) and the various SPDR sector indexes. These comparisons allow for a rapid and accurate assessment of the true strength of a stock at any given time on any given time frame. To cycle back above to our examples, the $100 stock has a Power Rating of only 0.71 (i.e. it is trading less than its current average), while our $20 stock has a Power Rating of 5. If we then compare these to both the market as a whole and the sector that the stock is a part of, we get a much clearer indication of the true buying or selling pressure imposed on the stock at any given time.
Use:
The indicator has 3 lines. The blue line is the security of interest, the red line is the market baseline (i.e. the sector ETF $SPY), and the white line is the sector index. I have given an example above on the semiconductor/tech stock $NVDA on a 30min timeframe. You can see that since the start of 2023, $NVDA has generally been strong to the market and its own sector since the blue line is greater than both the red and white lines over many days. This would have provided some nice day trading opportunities, or even some nice short term swing trades. The values themselves are generally meaningless outside of either the 1 or -1 value lines. All that matters is that the current ticker is surpassing both the market and the sector while being > 1.0 for a long trade or less than -1.0 for a short trade. However, I must stress this indicator gives no trade signals on its own, it is purely a confirmation indicator. An example of a trade would be if you had a trade signal given by either an indicator or by price action suggesting to buy some $NVDA for a trade to the upside, the Power Rating indicator would confirm this by showing if $NVDA was actually showing true strength by being both greater than 1 (the cutoff for it surpassing its ATR) and being above both the red and white lines. Further, you can see $NVDA has been stronger than the market when using the comparison function as well, but the has fluxed in and out of strength intraday when using the actual indicator vs. the static performance ratio chart (plotted as line graphs on the chart).
I have made it possible to change the colour of the plots and the line levels. The adjustment of the line levels gives the trader the flexibility to change their target breakout level (i.e. only trading stocks that have a Power Rating > 2, for example, meaning they are trading at least 2X their normal trading range). The third security comparison is flexible and can be used to compare to the sector ETF (initial intention) or it can be used to compare to other tickers within the same sector, for example. The trader should select the appropriate ETF for the given security of interest to avoid false confirmation if they want to use an ETF as their third input. The proper sector should be readily available on most online websites and accessible in a matter of seconds meaning that the delay is minimal, at worst. If a trader wishes to add additional functionality, such as a crypto trader using BTCUSD as the benchmark instead of $SPY, I encourage them to copy and paste this script and modify as needed since I have made this open source.
This indicator works on all timeframes. The lookback period can be changed, so a day trader who may use a 5min chart (and use a period of 12 to get the hourly Power Rating) will find this equally useful as someone who may be a core trader who wants to look at the performance over the course of years and may use a 60 period on a monthly chart.
Happy trading and I hope this helps!
[E5 Trading] Moving AveragesMoving Averages
Plot up to 12 moving averages and customize colors directly on the inputs tab.
Select from any of one of eight (8) moving averages types from the drop-down menu including 'EMA', 'HMA', 'LINREG', 'SWMA', 'SINE', 'SMA', 'VWMA', and 'WMA'.
Default 'SMA' for Plots 1 through 6, and default 'EMA' for plots 7 through 12.
Use this indicator to quickly transition between your favorite moving average combinations.
This indicator can also be used to create the Guppy Multiple Moving Average: www.investopedia.com
Definitions
'EMA' = Exponential Moving Average
'HMA' = Hull Moving Average
'LINREG' = Linear Regression Curve
'SWMA' = Symmetrically Weighted Moving Average
'SINE' = Sine Weighted Moving Average
'SMA' = Simple Moving Average
'VWMA' = Volume Weighted Moving Average
'WMA' = Weighted Moving Average
Zazzamira 50-25-25 Trend SystemPublishing my trading system script. It consist of several conditions to happen in order to open a trade. Work best on ES/MES 5 minute timeframe.
I like to use it with this settings:
- UTC -6 (don't tick Exchange Timezone)
and rest as default
To enter a trade, the following conditions must be met: Entry 1: the opening range (8:30AM - 9:15AM UTC-6) must be defined and the price must close above or below the opening range on the 5-minute timeframe. This entry condition defines the trade direction (above = long / below = short). Once the opening range is defined, the Trend-Based Fib Extension is applied from the range high to the range low (and vice versa). Fib levels are required for Exit conditions. Entry 2: the 8 - 27 - 67 - 97 EMAs must be defined. If the EMAs value order is 8 > 27 > 67 > 97, long-only trades are allowed. If the EMAs value order is 8 < 27 < 67 < 97, short-only trades are allowed. This entry condition filters fake breakouts of Entry 1. Entry 3: no trades are allowed after 12:59 UTC-6 (2PM EST). Entry 4: if Entry 1, Entry 2, and Entry 3 conditions are valid and the price hasn't reached the 23.6% Fib line, an entry order can be set at the range high/long with 4 contracts. To exit a trade, the following conditions must be met: Exit 1 (Stop loss): set a trailing stop based on 2.1x ATR (14) from entry. Exit 2: take 50% profits at the 23.6% Fib and leave trailing stop untouched. Exit 3: if Exit 2 triggers, take 50% (25% of total entry) off at 61.8% Fib, leaving Exit 2 trailing stop values valid. Exit 4: exit the full position at the FIB 100% value. Exit 5: all trades must be closed at 3pm UTC-6 (4PM EST). So basically Take Profit are 50%-25%-25% of position.
Code has been written by © Hiubris_Indicators who has been an amazing coder and gave me the possibility to make this script public so a really big shoutout to him.
Nifty36ScannerThis code is written for traders to be able to automatically scan 36 stocks of their choice for MACD , EMA200 + SuperTrend and Half Trend . Traders can be on any chart, and if they keep this scanner/indicator on , it will start displaying stocks meeting scanning criteria on the same window without having to go to Screener section and running it again and again. It will save time for traders and give them real time signals.
Indicators for scanning stocks are:
MACD
EMA200
Supertrend
HalfTrend - originally developed by EVERGET
Combination of EMA200 crossover/under and MACD crossover/under has worked well for me for long time, so using this combination as one of the criteria to
Scan the stocks. Using Everget's Half Trend method confirms the signal given by MACD , EMA200 and Supertrend Crossover.
I have added 36 of my favourite stocks from Nifty 50 lot. Users of this script can use the same stocks or change it by going into the settings of this scanner.
The Code is divided into 3 Sections
Section 1: Accepting input from users as boolean so that they can scan on the basis of one of the criteria or any combination of the criteria.
Section 2: "Screener function" to calculate Buy/ Sell on the basis of scanning criteria selected y the user.
screener=>
= ta.supertrend(2.5,10)
Buy/Sell on the basis of Supertrend crossing Close of the candle
//using ta.macd function to calculate MACD and Signal
= ta.macd(close, 12, 26, 9)
using HalfTrend indicator to calculate Buy/Sell signals , removed all the plotting functions from the code of Half Trend
Bringing Stock Symbols in S series variables
s1=input.symbol('NSE:NIFTY1!', title='Symbol1', group="Nifty50List", inline='0')
Assigning Bull/Bear ( Buy/Sell) signals to each stocks selected
=request.security(s1, tf, screener())
Assign BUY to all the stocks showing Buy signals using
buy_label1:= c1?buy_label1+str.tostring(s1)+'\n': buy_label1
Follow the same process for SELL Signals
Section 3: Plotting labels for the BUY/SELL result on the in terms of label for any stocks meeting the criteria with deletion of any previous signals to avoid clutter on the chart with so many signals generated in each candle
Display Buy siganaling stocks in teh form of label using Label.new function with parameters as follows:
barindex
close as series
color
textcolor
style as label_up,
yloc =price
textalign=left
Delete all the previous labels
label.delete(lab_buy )
STOCKS SELECTION
We have given range f 36 stocks from NIFTY 50 that can be selected at anytime,. User can chose their own 36 stocks using setting button.
INDICATORS SELECTION
1. MACD: It i sone of the most reliable trading strategy with 39.3% Success rate with 1.187 as profit factor for NIFTY Index on Daily time frame
2. EAM200 + Super trend : Combination of EMA200 crossover and Super trend removes any false positives and considered a very reliable way of scanning for Buy/Sell signals
3. HALF TREND: Originally developed as an indicator by Everget and modified as strategy by AlgoMojo, it generates Buy/Sell signals with 40.2% success rate with 1.469 as profit faction, on 15 minutes timeframe.
