N Bar Reversal Detector [LuxAlgo]The N Bar Reversal Detector is designed to detect and highlight N-bar reversal patterns in user charts, where N represents the length of the candle sequence used to detect the patterns. The script incorporates various trend indicators to filter out detected signals and offers a range of customizable settings to fit different trading strategies.
🔶 USAGE
The N-bar reversal pattern extends the popular 3-bar reversal pattern. While the 3-bar reversal pattern involves identifying a sequence of three bars signaling a potential trend reversal, the N-bar reversal pattern builds on this concept by incorporating additional bars based on user settings. This provides a more comprehensive indication of potential trend reversals. The script automates the identification of these patterns and generates clear, visually distinct signals to highlight potential trend changes.
When a reversal chart pattern is confirmed and aligns with the price action, the pattern's boundaries are extended to create levels. The upper boundary serves as resistance, while the lower boundary acts as support.
The script allows users to filter patterns based on the trend direction identified by various trend indicators. Users can choose to view patterns that align with the detected trend or those that are contrary to it.
🔶 DETAILS
🔹 The N-bar Reversal Pattern
The N-bar reversal pattern is a technical analysis tool designed to signal potential trend reversals in the market. It consists of N consecutive bars, with the first N-1 bars used to identify the prevailing trend and the Nth bar confirming the reversal. Here’s a detailed look at the pattern:
Bullish Reversal : In a bullish reversal setup, the first bar is the highest among the first N-1 bars, indicating a prevailing downtrend. Most of the remaining bars in this sequence should be bearish (closing lower than where they opened), reinforcing the existing downward momentum. The Nth (most recent) bar confirms a bullish reversal if its high price is higher than the high of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be higher than the high of the first bar.
Bearish Reversal : In a bearish reversal setup, the first bar is the lowest among the first N-1 bars, indicating a prevailing uptrend. Most of the remaining bars in this sequence should be bullish (closing higher than where they opened), reinforcing the existing upward momentum. The Nth bar confirms a bearish reversal if its low price is lower than the low of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be lower than the low of the first bar.
🔹 Min Percentage of Required Candles
This parameter specifies the minimum percentage of candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) among the first N-1 candles in a pattern. For higher values of N, it becomes more challenging for all of the first N-1 candles to be consistently bullish or bearish. By setting a percentage value, P, users can adjust the requirement so that only a minimum of P percent of the first N-1 candles need to meet the bullish or bearish condition. This allows for greater flexibility in pattern recognition, accommodating variations in market conditions.
🔶 SETTINGS
Pattern Type: Users can choose the type of the N-bar reversal patterns to detect: Normal, Enhanced, or All. "Normal" detects patterns that do not necessarily surpass the high/low of the first bar. "Enhanced" detects patterns where the last bar surpasses the high/low of the first bar. "All" detects both Normal and Enhanced patterns.
Reversal Pattern Sequence Length: Specifies the number of candles (N) in the sequence used to identify a reversal pattern.
Min Percentage of Required Candles: Sets the minimum percentage of the first N-1 candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) to qualify as a valid reversal pattern.
Derived Support and Resistance: Toggles the visibility of the support and resistance levels/zones.
🔹 Trend Filtering
Filtering: Allows users to filter patterns based on the trend indicators: Moving Average Cloud, Supertrend, and Donchian Channels. The "Aligned" option only detects patterns that align with the trend and conversely, the "Opposite" option detects patterns that go against the trend.
🔹 Trend Indicator Settings
Moving Average Cloud: Allows traders to choose the type of moving averages (SMA, EMA, HMA, etc.) and set the lengths for fast and slow moving averages.
Supertrend: Options to set the ATR length and factor for Supertrend.
Donchian Channels: Option to set the length for the channel calculation.
🔶 RELATED SCRIPTS
Reversal-Candlestick-Structure.
Reversal-Signals.
Pesquisar nos scripts por "THE SCRIPT"
Prometheus Black-Scholes Option PricesThe Black-Scholes Model is an option pricing model developed my Fischer Black and Myron Scholes in 1973 at MIT. This is regarded as the most accurate pricing model and is still used today all over the world. This script is a simulated Black-Scholes model pricing model, I will get into why I say simulated.
What is an option?
An option is the right, but not the obligation, to buy or sell 100 shares of a certain stock, for calls or puts respective, at a certain price, on a certain date (assuming European style options, American options can be exercised early). The reason these agreements, these contracts exist is to provide traders with leverage. Buying 1 contract to represent 100 shares of the underlying, more often than not, at a cheaper price. That is why the price of the option, the premium , is a small number. If an option costs $1.00 we pay $100.00 for it because 100 shares * 1 dollar per share = 100 dollars for all the shares. When a trader purchases a call on stock XYZ with a strike of $105 while XYZ stock is trading at $100, if XYZ stock moves up to $110 dollars before expiration the option has $5 of intrinsic value. You have the right to buy something at $105 when it is trading at $110. That agreement is way more valuable now, as a result the options premium would increase. That is a quick overview about how options are traded, let's get into calculating them.
Inputs for the Black-Scholes model
To calculate the price of an option we need to know 5 things:
Current Price of the asset
Strike Price of the option
Time Till Expiration
Risk-Free Interest rate
Volatility
The price of a European call option 𝐶 is given by:
𝐶 = 𝑆0 * Φ(𝑑1) − 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(𝑑2)
where:
𝑆0 is the current price of the underlying asset.
𝐾 is the strike price of the option.
𝑟 is the risk-free interest rate.
𝑇 is the time to expiration.
Φ is the cumulative distribution function of the standard normal distribution.
𝑑1 and 𝑑2 are calculated as:
𝑑1 = (ln(𝑆0 / 𝐾) + (𝑟 + (𝜎^2 / 2)) * 𝑇) / (𝜎 * sqrt(𝑇))
𝑑2= 𝑑1 - (𝜎 * sqrt(𝑇))
𝜎 is the volatility of the underlying asset.
The price of a European put option 𝑃 is given by:
𝑃 = 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(−𝑑2) − 𝑆0 * Φ(−𝑑1)
where 𝑑1 and 𝑑2 are as defined above.
Key Assumptions of the Black-Scholes Model
The price of the underlying asset follows a lognormal distribution.
There are no transaction costs or taxes.
The risk-free interest rate and volatility of the underlying asset are constant.
The underlying asset does not pay dividends during the life of the option.
The markets are efficient, meaning that all known information is already reflected in the prices.
Options can only be exercised at expiration (European-style options).
Understanding the Script
Here I have arrows pointing to specific spots on the table. They point to Historical Volatility and Inputted DTE . Inputted DTE is a value the user may input to calculate premium for options that expire in that many days. Historical Volatility , is the value calculated by this code.
length = 252 // One year of trading days
hv = ta.stdev(math.log(close / close ), length) * math.sqrt(365)
And then made daily like the Black-Scholes model needs from this step in the code.
hv_daily = request.security(syminfo.tickerid, "1D", hv)
The user has the option to input their own volatility to the Script. I will get into why that may be advantageous in a moment. If the user chooses to do so the Script will change which value it is using as so.
hv_in_use = which_sig == false ? hv_daily : sig
There is a lot going on in this image but bare with me, it will all make sense by the end. The column to the far left of both the green and maroon colored columns represent the strike price of the contract, if the numbers are white that means the contract is out of the money, gray means in the money. If you remember from the calculation this represents the price to buy or sell shares at, for calls or puts respective. The column second from the left shows a value for Simulated Market Price . This is a necessary part of this script so we can show changes in implied volatility. See, when we go to our brokerages and look at options prices, sure the price was calculated by a pricing model, but that is rarely the true price of the model. Market participant sentiment affects this value as their estimates for future volatility, Implied Volatility changes.
For example, if a call option is supposed to be worth $1.00 from the pricing model, however everyone is bullish on the stock and wants to buy calls, the premium may go to $1.20 from $1.00 because participants juice up the Implied Volatility . Higher Implied Volatility generally means higher premium, given enough time to expiration. Buying an option at $0.80 when it should be worth $1.00 due to changes in sentiment is a big part of the Quant Trading industry.
Of course I don't have access to an actual exchange so get prices, so I modeled participant decisions by adding or subtracting a small random value on the "perfect premium" from the Black-Scholes model, and solving for implied volatility using the Newton-Raphson method.
It is like when we have speed = distance / time if we know speed and time , we can solve for distance .
This is what models the changing Implied Volatility in the table. The other column in the table, 3rd from the left, is the Black-Scholes model price without the changes of a random number. Finally, the 4th column from the left is that Implied Volatility value we calculated with the modified option price.
More on Implied Volatility
Implied Volatility represents the future expected volatility of an asset. As it is the value in the future it is not know like Historical Volatility, only projected. We provide the user with the option to enter their own Implied Volatility to start with for better modeling of options close to expiration. If you want to model options 1 day from expiration you will probably have to enter a higher Implied Volatility so that way the prices will be higher. Since the underlying is so close to expiration they are traded so much and traders manipulate their Implied Volatility , increasing their value. Be safe while trading these!
Thank you all for clicking on my indicator and reading this description! Happy coding, Happy trading, Be safe!
Good reference: www.investopedia.com
Fibonacci Period Range [UkutaLabs]█ OVERVIEW
The Fibonacci Period Range Indicator is a powerful trading tool that draws levels of support and resistance that are based on key Fibonacci levels. The script will identify the high and low of a range that is specified by the user, then draw several levels of support and resistance based on Fibonacci levels.
The script will also draw extension levels outside of the specified range that are also based on Fibonacci levels. These extension levels can be turned off in the indicator settings.
Each level is also labelled to help traders understand what each line represents. These labels can be turned off in the indicator settings.
The purpose of this script is to simplify the trading experience of users by giving them the ability to customize the time period that is identified, then draw levels of support and resistance that are based on the price action during this time.
█ USAGE
In the indicator settings, the user has access to a setting called Session Range. This gives users control over the range that will be used.
The script will then identify the high and low of the range that was specified and draw several levels of support and resistance based on Fibonacci levels between this range. The user can also choose to have extension levels that display more levels outside of the range.
These lines will extend until the end of the current trading day at 5:00 pm EST.
█ SETTINGS
Configuration
• Display Mode: Determines the number of days that will be displayed by the script.
• Show Labels: Determines whether or not identifying labels will be displayed on each line.
• Font Size: Determines the text size of labels.
• Label Position: Determines the justification of labels.
• Extension Levels: Determines whether or not extension levels will be drawn outside of the high and low of the specified range.
Session
• Session Range: Determines the time period that will be used for calculations.
• Timezone Offset (+/-): Determines how many hours the session should be offset by.
Speedometer RevisitedSpeedometer Revisited is a new way to draw custom metric speedometers and is intended to be a utility for other coders to use.
@rumpypumpydumpy originally introduced the Speedometer Toolkit in version 4 of Pine Script. Since then, Pine Script has been updated to version 5, introducing some amazing new features such as polylines and chart.points. This indicator is an example of what can be done with these newer features.
The indicator starts off with a handful of functions that will be used to create the drawings. Notes are left throughout the code explaining what each line of the functions does. My goal was to make these functions user-friendly and somewhat easy to understand. I then demonstrate two examples: one speedometer with five segments and another with three.
The first example demonstrates how to visually represent the analysts' ratings for a stock using the built-in syminfo.recommendations. The speedometer is divided into five segments, each representing a different level of analyst recommendation: strong sell, sell, hold, buy, and strong buy.
Each segment is drawn using a polyline from the createSeg function, with colors assigned as follows:
Red for 'Strong Sell'
Maroon for 'Sell'
Yellow for 'Hold'
Green for 'Buy'
Lime for 'Strong Buy'
The script identifies the maximum value among the analyst ratings, calculates the midpoint of the corresponding segment, and draws a needle pointing to this midpoint.
The second example employs the speedometer design to display market sentiment through the put-call ratio. The put-call ratio is a gauge of investor sentiment, where values above 1 indicate a bearish sentiment (more puts being bought relative to calls), and values below 1 suggest a bullish outlook (more calls being bought relative to puts).
The speedometer is divided into three segments, reflecting different ranges of the put-call ratio:
Red for a ratio greater than 1 (bearish sentiment)
Yellow for a ratio between 0.8 and 1 (neutral to bearish sentiment)
Lime for a ratio less than 0.8 (bullish sentiment)
Depending on the value of the put-call ratio, the script calculates which segment the current value falls into and determines the appropriate segment number. The script calculates the midpoint of the selected segment and draws a needle pointing to this value.
Both examples show how the speedometer can be used as a visual indicator of certain market conditions, helping traders quickly recognize trends and adjust their strategies accordingly.
A big thanks to @rumpypumpydumpy for his original Speedometer Toolbox. I hope this take on it can be useful for other coders.
Squeeze & Release [AlgoAlpha]Introduction:
💡The Squeeze & Release by AlgoAlpha is an innovative tool designed to capture price volatility dynamics using a combination of EMA-based calculations and ATR principles. This script aims to provide traders with clear visual cues to spot potential market squeezes and release scenarios. Hence it is important to note that this indicator shows information on volatility, not direction.
Core Logic and Components:
🔶EMA Calculations: The script utilizes the Exponential Moving Average (EMA) in multiple ways to smooth out the data and provide indicator direction. There are specific lengths for the EMAs that users can modify as per their preference.
🔶ATR Dynamics: Average True Range (ATR) is a core component of the script. The differential between the smoothed ATR and its EMA is used to plot the main line. This differential, when represented as a percentage of the high-low range, provides insights into volatility.
🔶Squeeze and Release Detection: The script identifies and highlights squeeze and release scenarios based on the crossover and cross-under events between our main line and its smoothed version. Squeezes are potential setups where the market may be consolidating, and releases indicate a potential breakout or breakdown.
🔶Hyper Squeeze Detection: A unique feature that detects instances when the main line is rising consistently over a user-defined period. Hyper squeeze marks areas of extremely low volatility.
Visual Components:
The main line (ATR-based) changes color depending on its position relative to its EMA.
A middle line plotted at zero level which provides a quick visual cue about the main line's position. If the main line is above the zero level, it indicates that the price is squeezing on a longer time horizon, even if the indicator indicates a shorter-term release.
"𝓢" and "𝓡" characters are plotted to represent 'Squeeze' and 'Release' scenarios respectively.
Standard Deviation Bands are plotted to help users gauge the extremity and significance of the signal from the indicator, if the indicator is closer to either the upper or lower deviation bands, this means that statistically, the current value is considered to be more extreme and as it is further away from the mean where the indicator is oscillating at for the majority of the time. Thus indicating that the price has experienced an unusual amount or squeeze or release depending on the value of the indicator.
Usage Guidelines:
☝️Traders can use the script to:
Identify potential consolidation (squeeze) zones.
Gauge potential breakout or breakdown scenarios (release).
Fine-tune their entries and exits based on volatility.
Adjust the various lengths provided in the input for better customization based on individual trading styles and the asset being traded.
Liquidation Estimates (Real-Time) [LuxAlgo]The Liquidation Estimates (Real-Time) experimental indicator attempts to highlight real-time long and short liquidations on all timeframes. Here with liquidations, we refer to the process of forcibly closing a trader's position in the market.
By analyzing liquidation data, traders can gauge market sentiment, identify potential support and resistance levels, identify potential trend reversals, and make informed decisions about entry and exit points.
🔶 USAGE
Liquidation refers to the process of forcibly closing a trader's position. It occurs when a trader's margin account can no longer support their open positions due to significant losses or a lack of sufficient margin to meet the maintenance requirements.
Liquidations can be categorized as either a long liquidation or a short liquidation. A long liquidation is a situation where long positions are being liquidated, while short liquidation is a situation where short positions are being liquidated.
The green bars indicate long liquidations – meaning the number of long positions liquidated in the market. Typically, long liquidations occur when there is a sudden drop in the asset price that is being traded. This is because traders who were bullish on the asset and had opened long positions on the same will now face losses since the market has moved against them.
Similarly, the red bars indicate short liquidations – meaning the number of short positions liquidated in the futures market. Short liquidations occur when there is a sudden spike in the price of the asset that is being traded. This is because traders who were bearish on the asset and had opened short positions will now face losses since the market has moved against them.
Liquidation patterns or clusters of liquidations could indicate potential trend reversals.
🔹 Dominance
Liquidation dominance (Difference) displays the difference between long and short liquidations, aiming to help identify the dominant side.
🔹 Total Liquidations
Total liquidations display the sum of long and short liquidations.
🔹 Cumulative Liquidations
Cumulative liquidations are essentially the cumulative sum of the difference between short and long liquidations aiming to confirm the trend and the strength of the trend.
🔶 DETAILS
It's important to note that liquidation data is not provided on the Trading View's platform or can not be fetched from anywhere else.
Yet we know that the liquidation data is closely tied in with trading volumes in the market and the movement in the underlying asset’s price. As a result, this script analyzes available data sources extracts the required information, and presents an educated estimate of the liquidation data.
The data presented does not reflect the actual individual quantitative value of the liquidation data, traders and analysts shall look to the changes over time and the correlation between liquidation data and price movements.
The script's output with the default option values has been visually checked/compared with the liquidation chart presented on coinglass.com.
🔶 SETTINGS
🔹Liquidations Input
Mode: defines the presentation of the liquidations chart. Details are given in the tooltip of the option.
Longs Reference Price: defines the base price in calculating long liquidations.
Shorts Reference Price: defines the base price in calculating short liquidations.
🔶 RELATED SCRIPTS
Liquidation-Levels
Liquidity-Sentiment-Profile
Buyside-Sellside-Liquidity
Liquidity Sentiment Profile (Auto-Anchored) [LuxAlgo]
The Liquidity Sentiment Profile (Auto-Anchored) is an advanced charting tool that measures by combining PRICE and VOLUME data over specified anchored periods and highlights the distribution of the liquidity and the market sentiment at specific price levels. This version is a variation of the previously published Liquidity Sentiment Profile , wherewith this version allows users to select a variety of different anchoring periods, such as 'Auto', 'Fixed Range', 'Swing High', 'Swing Low', 'Session', 'Day', 'Week', 'Month', 'Quarter', and 'Year'
Liquidity refers to the availability of orders at specific price levels in the market, allowing transactions to occur smoothly.
🔶 USAGE
A Liquidity Sentiment Profile (Auto-Anchored) is a combination of liquidity and a sentiment profile, where the right side of the profile highlights the distribution of the traded activity at different price levels, and the left side of the profile highlights the market sentiment at those price levels
The liquidity profile is categorized by assigning different colors based on the significance of the traded activity of the specific price levels, allowing traders to reveal significant price levels, such as support and resistance levels, supply and demand zones, liquidity gaps, consolidation zones, etc
The Liquidity Sentiment Profiles aim to present Value Areas based on the significance of price levels, thus allowing users to identify value areas that can be formed more than once within the range of a single profile
Level of Significance Line - displays the changes in the price levels with the highest traded activity (developing POC)
Buyside & Sellside Liquidity Zones - displays Liquidity Levels, also known as Supply and Demand Zones
🔶 SETTINGS
The script takes into account user-defined parameters and plots the profiles, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Sentiment Profile
Anchor Period: The indicator resolution is set by the input of the Anchor Period.
Fixed Period: Applicable if the Anchor Period is set to 'Fixed Range' then the period of the profile is defined with this option
Swing Detection Length: Applicable if the Anchor Period is set to 'Swing High' or 'Swing Low' then the length required to detect the Swing Levels is defined with this option which is then used to determine the period of the profile
🔹 Liquidity Profile
Liquidity Profile: Toggles the visibility of the Liquidity Profiles
High Traded Nodes: Threshold and Color option for High Traded Nodes
Average Traded Nodes: Color option for Average Traded Nodes
Low Traded Nodes: Threshold and Color option for Low Traded Nodes
🔹 Sentiment Profile
Sentiment Profile: Toggles the visibility of the Sentiment Profiles
Bullish Nodes: Color option for Bullish Nodes
Bearish Nodes: Color option for Bearish Nodes
🔹 Buyside & Sellside Liquidity Zones
Buyside & Sellside Liquidity Zones: Toggles the visibility of the Liquidity Levels
Buyside Liquidity Nodes: Color option for Buyside Liquidity Nodes
Sellside Liquidity Nodes: Color option for Sellside Liquidity Nodes
🔹 Other Settings
Level of Significance: Toggles the visibility of the Level of Significance Line
Price Levels, Color: Toggles the visibility of the Profile Price Levels
Number of Rows: Specify how many rows each profile histogram will have. Caution, having it set to high values will quickly hit Pine Script™ drawing objects limit and fewer historical profiles will be displayed
Profile Width %: Alters the width of the rows in the histogram, relative to the profile length
Profile Range Background Fill: Toggles the visibility of the Profiles Range
🔶 RELATED SCRIPTS
Liquidity-Sentiment-Profile
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ICT-Concepts
Candle Close AlertCandle Close Alert (CCA) :
The "Candle Close Alert" (CCA) is a custom technical analysis tool. It operates as an overlay on price charts and serves to detect and notify users about significant changes in consecutive candle closes. The script calculates the difference between the closing price of the current candle and the previous candle, referred to as the "close difference." It then compares this close difference against a user-specified threshold value.
When the close difference exceeds the threshold, the script triggers an alert, notifying users of a potential noteworthy event. This alert can serve as a prompt for traders and investors to investigate the current price action further or to consider possible trading decisions .
Additionally, the script enhances visualization by plotting the close differences on the price chart. Positive close differences exceeding the threshold are plotted in green, while negative close differences exceeding the threshold in magnitude are plotted in red. This color-coded visualization helps users quickly identify periods of significant price movement and potential market trends.
However, it's important to note that the CCA script is a standalone tool and should be used in conjunction with comprehensive market analysis. Trading decisions should not be solely based on the alerts and visualizations provided by this script. Instead, they should be considered within the broader context of other technical indicators, fundamental analysis, and risk management strategies. Enjoy it!
Liquidity Levels/Voids (VP) [LuxAlgo]The Liquidity Levels/Voids (VP) is a script designed to detect liquidity voids & levels by measuring traded volume at all price levels on the market between two swing points and highlighting the distribution of the liquidity voids & levels at specific price levels.
🔶 USAGE
Liquidity is a fundamental market force that shapes the trajectory of assets.
The creation of a liquidity level comes as a result of an initial imbalance of supply/demand, which forms what we know as a swing high or swing low. As more players take positions in the market, these are levels that market participants will use as a historical reference to place their stops. When the levels are then re-tested, a decision will be made. The binary outcome here can be a breakout of the level or a reversal back to the mean.
Liquidity voids are sudden price changes that occur in the market when the price jumps from one level to another with little trading activity (low volume), creating an imbalance in price. The price tends to fill or retest the liquidity voids area, and traders understand at which price level institutional players have been active.
Liquidity voids are a valuable concept in trading, as they provide insights about where many orders were injected, creating this inefficiency in the market. The price tends to restore the balance.
🔶 SETTINGS
The script takes into account user-defined parameters and detects the liquidity voids based on them, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Levels / Voids
Liquidity Levels/Voids: Color customization option for Unfilled Liquidity Levels/Voids.
Detection Length: Lookback period used for the calculation of Swing Levels.
Threshold %: Threshold used for the calculation of the Liquidity Levels & Voids.
Sensitivity: Adjusts the number of levels between two swing points, as a result, the height of a level is determined, and then based on the above-given threshold the level is checked if it matches the liquidity level/void conditions.
Filled Liquidity Levels/Voids: Toggles the visibility of the Filled Liquidity Levels/Voids and color customization option for Filled Liquidity Levels/Voids.
🔹 Other Features
Swing Highs/Lows: Toggles the visibility of the Swing Levels, where tooltips present statistical information, such as price, price change, and cumulative volume between the two swing levels detected based on the detection length specified above, Coloring options to customize swing low and swing high label colors, and Size option to adjust the size of the labels.
🔹 Display Options
Mode: Controls the lookback length of detection and visualization.
# Bars: Lookback length customization, in case Mode is set to Present.
🔶 RELATED SCRIPTS
Liquidity-Voids-FVG
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AI SuperTrend Clustering Oscillator [LuxAlgo]The AI SuperTrend Clustering Oscillator is an oscillator returning the most bullish/average/bearish centroids given by multiple instances of the difference between SuperTrend indicators.
This script is an extension of our previously posted SuperTrend AI indicator that makes use of k-means clustering. If you want to learn more about it see:
🔶 USAGE
The AI SuperTrend Clustering Oscillator is made of 3 distinct components, a bullish output (always the highest), a bearish output (always the lowest), and a "consensus" output always within the two others.
The general trend is given by the consensus output, with a value above 0 indicating an uptrend and under 0 indicating a downtrend. Using a higher minimum factor will weigh results toward longer-term trends, while lowering the maximum factor will weigh results toward shorter-term trends.
Strong trends are indicated when the bullish/bearish outputs are indicating an opposite sentiment. A strong bullish trend would for example be indicated when the bearish output is above 0, while a strong bearish trend would be indicated when the bullish output is below 0.
When the consensus output is indicating a specific trend direction, an opposite indication from the bullish/bearish output can highlight a potential reversal or retracement.
🔶 DETAILS
The indicator construction is based on finding three clusters from the difference between the closing price and various SuperTrend using different factors. The centroid of each cluster is then returned. This operation is done over all historical bars.
The highest cluster will be composed of the differences between the price and SuperTrends that are the highest, thus creating a more bullish group. The lowest cluster will be composed of the differences between the price and SuperTrends that are the lowest, thus creating a more bearish group.
The consensus cluster is composed of the differences between the price and SuperTrends that are not significant enough to be part of the other clusters.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Smooth: Degree of smoothness of each output from the indicator.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
Liquidity Sentiment Profile [LuxAlgo]The Liquidity Sentiment Profile is an advanced charting tool that measures by combining PRICE and VOLUME data over specified anchored periods and highlights within a sequence of profiles the distribution of the liquidity and the market sentiment at specific price levels.
The Liquidity Sentiment Profile allows traders to reveal significant price levels, dominant market sentiment, support and resistance levels, supply and demand zones, liquidity availability levels, liquidity gaps, consolidation zones, and more based on price and volume data.
Liquidity refers to the availability of orders at specific price levels in the market, allowing transactions to occur smoothly.
🔶 USAGE
A Liquidity Sentiment Profile is a combination of a liquidity and a sentiment profile, where the right part of the profile displays the distribution of the traded activity at different price levels and the left part displays the market sentiment at those price levels.
The Liquidity Sentiment Profiles are visualized with different colors, where each color has a different meaning.
The Liquidity Sentiment Profiles aim to present Value Areas based on the significance of price levels, thus allowing users to identify value areas that can be formed more than once within the range of a single profile.
Level of Significance Line - displays the changes in the price levels with the highest traded activity (developing POC)
🔶 SETTINGS
The script takes into account user-defined parameters and plots the profiles, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Sentiment Profiles
Anchor Period: The indicator resolution is set by the input of the Anchor Period, the default option is AUTO.
🔹 Liquidity Profile Settings
Liquidity Profile: Toggles the visibility of the Liquidity Profiles
High Traded Nodes: Threshold and Color option for High Traded Nodes
Average Traded Nodes: Color option for Average Traded Nodes
Low Traded Nodes: Threshold and Color option for Low Traded Nodes
🔹 Sentiment Profile Settings
Sentiment Profile: Toggles the visibility of the Sentiment Profiles
Bullish Nodes: Color option for Bullish Nodes
Bearish Nodes: Color option for Bearish Nodes
🔹 Other Settings
Level of Significance: Toggles the visibility of the Level of Significance Line
Profile Price Levels: Toggles the visibility of the Profile Price Levels
Number of Rows: Specify how many rows each profile histogram will have. Caution, having it set to high values will quickly hit Pine Script™ drawing objects limit and fewer historical profiles will be displayed
Profile Width %: Alters the width of the rows in the histogram, relative to the profile length
Profile Range Background Fill: Toggles the visibility of the Profiles Range
🔶 LIMITATIONS
The amount of drawing objects that can be used is limited, as such using a high number of rows can display fewer historical profiles and occasionally incomplete profiles.
🔶 RELATED SCRIPTS
🔹 Buyside-Sellside-Liquidity
🔹 ICT-Concepts
🔹 Swing-Volume-Profiles
New York, London and custom trading sessionsHi Traders
The script :
The Time sessions script plots the trading sessions of both New York and London markets (background fills), In addition to the above the script also plots a user defined trading session period (vertical lines). All plots may be toggled true or false inorder to ensure you can focus on the respective market / markets / custom session.
Market sessions are useful for technical or quantitative analysis, as the majority of trading activity and net daily volume occurs in these zones, in fact the U.S./London market overlap tends to have the greatest volume accumulation across that range of time / bars than that range at any other time within the daily session. For FX traders it may also be important to take into account for many currency pairs the average exchange rate pip movement is greatest within these zones.
The custom session, is intended to be used for traders who trade only within specific intervals within the market session or day for 24/7 traded asset classes
Additional notes :
Not as of now, I have only added three optional trading sessions. If you would like to change the sessions, copy the scripts code and change the "ctm_session" default time range value, insuring the second time value is 1 min > than the first.
As always i Hope this is a useful script, and I will be updating this script in the near future.
Heikin Ashi ROC Percentile Strategy**User Guide for the "Heikin Ashi ROC Percentile Strategy"**
This strategy, "Heikin Ashi ROC Percentile Strategy", is designed to provide an easy-to-use framework for trading based on the Heikin Ashi Rate of Change (ROC) and its percentiles.
Here's how you can use it:
1. **Setting the Start Date**: You can set the start date for the strategy in the user inputs at the top of the script. The variable `startDate` defines the point from which the script begins executing trades. Simply input the desired date in the format "YYYY MM DD". For example, to start the strategy from March 3, 2023, you would enter `startDate = timestamp("2023 03 03")`.
2. **Adjusting the Midline, Lookback Period, and Stop Loss Level**: The `zerohLine`, `rocLength`, and `stopLossLevel` inputs allow you to adjust the baseline for ROC, the lookback period for the SMA and ROC, and the level at which the strategy stops the loss, respectively. By tweaking these parameters, you can fine-tune the strategy to better suit your trading style or the particular characteristics of the asset you are trading.
3. **Understanding the Trade Conditions**: The script defines conditions for entering and exiting long and short positions based on crossovers and crossunders of the ROC and the upper and lower "kill lines". These lines are defined as certain percentiles of the ROC's highest and lowest values over a specified lookback period. When the ROC crosses above the lower kill line, the script enters a long position; when it crosses below the upper kill line, it exits the position. Similarly, when the ROC crosses below the upper kill line, the script enters a short position; when it crosses above the lower kill line, it exits the position.
In my testing, this strategy performed best on a day and hour basis. However, I encourage you to experiment with different timeframes and settings to see how the strategy performs under various conditions. Remember, there's no one-size-fits-all approach to trading; what works best will depend on your specific circumstances, goals, and risk tolerance.
If you find other useful applications for this strategy, please let me know in the comments. Your feedback is invaluable in helping to refine and improve this tool. Happy trading!
Pi - Intraday High-Low Predictor
Pi - Intraday High-Low Predictor
This is not my Strategy/Research , I've just coded it into a indicator.
I found it interesting & useful so I'm sharing it here.
This Strategy/Research is by Kshirod Chandra Mohanty ( y-o-u-t-u-b-e : Trade with IITIAN )
You can watch his video on y-o-u-t-u-b-e for more info on this one.
the video has following title :
"1Cr Paid Strategy For Free || 10000 Subscribers Special Giveaway || How to find Day High or Low"
This will not tell you which is day high or day low, but it will help you to predict the day high from a day low and day low from a day high.
It will give you a possible range to which the prices could move to.
He has explained/used this on Banknifty.
How to Find out Day High from Day Low & Day Low from Day High :-
He uses the value of Pi (3.14) and the Range of 1st 5minute candle to find out the possible highs from day low and the possible lows from day high.
Range = value of Pi * 1st 5minutes Range
Small range = Range / 2
Large range = Range + Small range
so to find out the possible lows from day high we do following calculations
Small range low = day high - Small range
Range low = day high - Range
Large range low = day high - Large range
and to find out the possible highs from day low we do following calculations
Small range high = day low + Small range
Range high = day low + Range
Large range high = day low + Large range
Note :- This Indicator does Repaint in following ways,
As the script uses the Day High to predict the possible lows ,
so if it's an up-trending day and price keeps on making new High's then the ranges for lows will keep on changing.
similarly the script uses the Day Low to predict the possible high's ,
so if it's an down-trending day and price keeps on making new Low's then the ranges for highs will keep on changing.
My observations / thoughts about this :-
This script does not provide buy/sell recommendations. it just provides possible ranges to where prices can go from Day-High & Day-Low.
It's better to avoid trading when the price is trading between the Small range high & Small range low levels.
As it has high probability that it will be a range bound day and price will stay in between those two levels.
There is a high probability that it will be a trending day if price breaks either the Small range high/low ,
then the price could move to Range low/high.
If price breaks from Range High/Low then there is a high probability that it will be a trending day and the price could move to Large Range low/high.
Note :- If you want to use this on instruments/scripts/indexes which are active for large session such as forex/cryptos , then i suggest that you use the Opening Range period of 4Hours i.e 240minutes, to get better results.
using the default setting of 5minutes will not give good results on them.
play around with this value to find out which one suits that instrument/script/index the best.
Don't trust these levels blindly, do backtest or live testing of this then use for real trade if you want.
Use Price action near these levels to make any trading decision's.
The script provides following options :
1. Option to display Ranges in a Table (which you can enable/hide as you wish)
You can set the Table's location, size , background color & text color according to your preference.
2. Option to enable/hide Predicted-Highs from Day-Low on chart.
3. Option to enable/hide Predicted-Lows from Day-High on chart.
4. Option to set the Opening range period - here you can select your preferred opening range for calculation purpose.
5. Option to enable/hide historical levels on chart.
6. Options to customize the colors & line styles for lines.
7. Options to customize the colors , position & size for labels.
Market Sessions - By LeviathanA simple indicator to help you keep track of 4 market sessions (default: Tokyo, London, New York, Sydney) in 4 different visual forms (boxes, timeline, zones, colored candles) with many other useful tools.
You can choose between 4 different market sessions. The default ones are Tokyo, London, New York and Sydney but you can easily customize the times, names and colors to make the script plot any session you need. Sessions can be viewed in 4 different ways: boxes, zones, timelines, or just colored candles, all with customizable appearances. You can make your chart cleaner by merging sessions overlaps, choosing a custom lookback period and also picking between various additional settings such as viewing session High/Low or Open/Close change in % or pips, hiding weekends, viewing the Open/Close Line to identify session’s direction and 0.5 level to see session’s “Equilibrium” and much more. More updates with interesting tools will be added in the future.
Note: The script will plot the correct default Tokyo, London, New York and Sydney sessions automatically, your chart/Tradingview app timezone does not matter! If you wish to tweak the open/close times of sessions, just make sure you input them in UTC (but even this can be changed later in the settings)
Settings Overview
SESSIONS
- You can show/hide Tokyo Session, rename it, change the color and set up start/end time.
- You can show/hide London Session, rename it, change the color and set up start/end time.
- You can show/hide New York Session, rename it, change the color and set up start/end time.
- You can show/hide Sydney Session, rename it, change the color and set up start/end time.
* Keep in mind that you can fully change and customize these sessions and therefore create any other sessions or a zone you wish to display.
ADDITIONAL TOOLS AND SETTINGS
1. “Change (Pips)” - this will add the pip distance between Session High and Session Low or the pip distance between Session Open and Session Close to the session label.
2. “Change (%)” - this will add the percentage distance between Session High and Session Low or the percentage distance between Session Open and Session Close to the session label.
3. “Merge Overlaps” - this will merge the overlapping sessions and show only one at a time (end of Tokyo is moved to start of London, the end of London is moved to the start of New York, end of New York is moved to start of Sydney and end of Sydney is moved to start of Tokyo).
4. “Hide Weekends” - this will prevent the script from plotting sessions over the weekend when the markets are closed.
5. “Open/Close Line” - this will draw a line from the session open to the session close (or current price, if session is ongoing).
6. “Session 0.5 Level” - this will draw a horizontal line halfway between the session’s high and the session’s low.
7. “Color Candles” - this will color the bars/candlesticks with the color of the session in which they occurred.
8. Display Type” - Choose between three different ways of session visualization (Boxes, Zones and Candles).
9. “Lookback (Days)” - this input tells the script to only draw sessions for X days back (1 = one day).
10. “Change (%/Pips) Source) - this is where you choose the source of “Change (Pips)” and ”Change (%) ” labels. Picking “Session High/Low” will show you the change between Session High and Session Low and picking “Session Open/Close” will show you the change between Session Open and Session Close.
11. “Input Timezone” - this defines the timezone of the session start/end inputs (you don’t have to change this unless you know what you’re doing)
Make sure to read future update logs to keep track of the most recent additions and settings of this script.
Box generation code inspired by Jos(TradingCode), session box visuals inspired by @boitoki's FX Market Sessions
TPO Profile with Day StatFirst of all I want to Thank @noop42 for creating this wonderful Market Profile chart in Pine script
I have made some changes to this scripts
This Script can auto calculate the TPO Size for NSE Symbols and MCX Crude oil.
This Script Will only calculate the TPO's for visible range only so that the script use less heap size.
I have added some of the day Statistics to enhance your visualization.
Limitations of this Script
Currently This Script can Plot Market Profile Chart only for Historical Data.
It Can only Plot Market Profile Charts in 30-Mins Time Frame only so that you can't use it for Composite Profile Analysis.
To plot Market Profile Chart in Real Time and Historical please use "Market Profile With TPO by Drother"
[ChasinAlts] Best Volatility Indicator I hope you all enjoy this one as it does a great job at finding runners I did try to search for an example script to reference for quite a while when i first dreamt up this idea bc needed assistance implementing it. This script in particular was one that I began long ago but got put on the back-burner because I couldn't figure out how to implement the flow of logic until I came across a library titled 'Conditional Averages' and published by the “Pinecoders" account. Thus, the logic in this code is partially derived from that () . To understand what the functions/logic do in the beginning of the 'Functions'' section, you must understand how TV presents it's data through the charts.
Wether on the 1sec TF or the 1day (or ANY other), the only time TV prints a bar/candle is when a trade occurs for that asset (i.e. a change in volume). Even if Open=Close on the same candle, the candle will print with the updated price. The % of candles printed out of the TOTAL possible amount that COULD HAVE been printed is the ultimate output that’s calculated in the script. So, if the lookback setting=10min on the 1min TF and only 7 out of the last 10 candles have printed then the value will appear as 70(%). There are MANY benefits to using this method to measure volatility but its vital to recall that the indicator does nothing to provide the direction of future price movement. One thing I’ve noticed is that when a coin is just beginning it’s ascent and its move is considerably larger/longer than all the other coins OR the plots angle is very steep, it is usually the end of a move and the direction is about to abruptly reverse, continuing with it’s volatility. As volatility increases more and more the plot gets brighter and brighter…and also vise versa.
The settings are as follows:
1) which set of Kucoin’s Margin Coins to use (8 possible sets with 32 coins in each set).
2) input how many minutes ago to start counting the total printed candles from (i.e. if setting is input as 1440, count begins from exactly 24hrs(1440min) ago to present candle.
3) there are 3 different lines to choose from to be able to plot:
i. ‘Includes Open==Close’ = adds to count when bar prints but price does NOT change (=t1)
ii. ‘Does NOT include Open==Close’ = count ONLY updates upon price movement (=t2)
iii. ‘Difference’ = (( t1 - t2 ) / t1 ) *100
*** I’ve got some more great ones I will be uploading soon. Just have to create a description for them
Peace out,
- ChasinAlts
Bar Count for BacktestingHello!
Not much special about this script; you can use date & time, or bar count, to ascertain the number of bars in a time period for backtesting.
This script can be used in conjunction with large scripts incorporating complex intricacies that won't load on 20,000+ bar data sets.
If your script's load time transcends the TV allotted load time - use this script to quickly determine the number of bars in the data set.
Through trial & error you should be able to determine the approximate number of bars your script can execute on without exceeding the imposed time limit!
The image above shows a user-defined time window and, consequently, the script returns the number of bars that constitute the time period.
You can drag the white vertical lines to efficiently configure the calculated time period.
The image above shows functionality for the "Bars Back" feature.
Enjoy!
Wolfe Scanner (Multi - zigzag) [HeWhoMustNotBeNamed]Before getting into the script, I would like to explain bit of history around this project. Wolfe was in the back of my mind for some time and I had several attempts so far.
🎯Initial Attempt
When I first developed harmonic patterns, I got many requests from users to develop script to automatically detect Wolfe formation. I thought it would be easy and started boasting everywhere that I am going to attempt this next. However I miserably failed that time and started realising it is not as simple as I thought it would be. I started with Wolfe in mind. But, ran into issues with loops. Soon figured out that finding and drawing wedge is more trickier. I decided will explore trendline first so that it can help find wedge better. Soon, the project turned into something else and resulted in Auto-TrendLines-HeWhoMustNotBeNamed and Wolfe left forgotten.
🎯Using predefined ratios
Wolfe also has predefined fib ratios which we can use to calculate the formation. But, upon initial development, it did not convince me that it matches visual inspection of Wolfe all the time. Hence, I decided to fall back on finding wedge first.
🎯 Further exploration in finding wedge
This attempt was not too bad. I did not try to jump into Wolfe and nor I bragged anywhere about attempting anything of this sort. My target this time was to find how to derive wedge. I knew then that if I manage to calculate wedge in efficient way, it can help further in finding Wolfe. While doing that, ended up deriving Wedge-and-Flag-Finder-Multi-zigzag - which is not a bad outcome. I got few reminders on Wolfe after this both in comments and in PM.
🎯You never fail until you stop trying!!
After 2 back to back hectic 50hr work weeks + other commitments, I thought I will spend some time on this. Took less than half weekend and here we are. I was surprised how much little time it took in this attempt. But, the plan was running in my subconscious for several weeks or even months. Last two days were just putting these plans into an action.
Now, let's discuss about the script.
🎲 Wolfe Concept
Wolfe concept is simple. Whenever a wedge is formed, draw a line joining pivot 1 and 4 as shown in the chart below:
Converging trendline forms the stop loss whereas line joining pivots 1 and 4 form the profit taking points.
🎲 Settings
Settings are pretty straightforward. Explained in the chart below.
Market Bias (CEREBR)Hello Everyone. I hope you are all doing great. It's been a long time since I posted my first script here, and I got a lot of response from that.
So, I thought I should share this script also to everyone, and anyone that may find it useful. Personally, I use it to tell the general market conditions.
Here's how I works : The script tries to determine the overall direction of the market, using smoothed Heiken Ashi candles. The coloring system (using bright and dark colors) is an attempt to detect strong market and weak market conditions. There's also an oscillator within the script, but for now it isn't plotted. Credits to @jackvmk, I used part of his open-script code in this indicator.\
I have considered using the slope of the indicator plot as a filter for ranging market conditions. The plot goes relatively flat in 'flat' markets. However, I have not done anything about that yet. Maybe some other time.
I hope you find this useful. If you find a way to use this, please share it with the community in the comment section.
NOTE: THIS IS BY NO MEANS FINANCIAL ADVICE. You'll have to make your studies and come up with a way to apply this indicator to your trading style and strategy.
By the way, I would be going with the name 'CEREBR' for any subsequent scripts I release from now on.
Happy Trading, guys.
ICT Fair Value Gap [LM]Hello traders,
I would like to present you ICT Fair Value Gap script. The idea is the same as in my other script to look form imbalances. I have improved the previous script from teaching of ICT and created this script to train the eye to see those gaps. Shrinking option also shows if the gap has been already filled and also in case gap is filled you can get alert in case you will set it up .
The script has two settings:
general settings - definition of volatility condition for middle candle
box settings - setting for boxes, box colors, shrinking
I hope you enjoy it,
Lukas
SIMPLE CANDLESTICK PATTERN ALGO BACKTESTING - TESLA 4HMany traders spend a lot of time to create algorithms full of unrealistic and far from reality indicators and market conditions. With this script I want to help traders understand the advantage of the Pine language. Using indicators with no statistical foundation and creating algorithms with technical indicators and thousands of conditions is not always the right way to create an efficient tool.
With this script that we have called "SimpleBarPattern_LongOnly" we analyse the market through a simple condition, using bars or candles.
How it works
The condition is constructed as follows. You go long with 100% of the established capital and 0.03% commission. The first condition is that the minimum of the period under analysis falls below the opening level. The second condition is that the low of the period is below the low of the previous period. The third condition is that the close of the period is above the opening level. The final condition wants the current close to be higher than the previous open and higher than the previous close. We used a statistical approach in the creation of this script, some candlestick patterns that reflect these conditions are: Bullish Engulfing, Bullish Hammer and Morning Star .
This strategy aims to help traders make more accurate decisions while using candlesticks for their trading and scientifically demonstrates that candlesticks are valid statistical tools for financial analysis.
"SimpleBarPattern_LongOnly" is a very lightweight script created with Pine v5. We developed a user interface that can adjust the analysis period from a few days to several years.
The initial capital set is €1,000 (You can change this from the "Properties" section of the user interface).
Each individual trade uses 100% of the set capital, in this case €1,000.
The default commission per trade is 0.03% (You can change this in the "Properties" section of the user interface).
User Interface
1) General backtest time settings: Set the history period to be analysed
StartDate: backtest start date
StartMonth: backtest start month
StartYear: backtest start year
EndDate: backtest end day
EndMonth: backtest end month
EndYear: backtest end year
3) Stop Loss
4) Take Profit
Please do not hesitate to contact us for any questions or information.
Disclaimer
Be careful, the past is not a guarantee of future performance, so remember to use the script as a pure analysis tool. The developer takes no responsibility for any use other than research and analysis and can in no way be held liable for damages resulting from wrong use of this code.
