ICT Seek & Destroy Profile [TFO]The goal of this indicator is to anticipate potentially "choppy" New York trading sessions, based on what price does during the Asia and London trading sessions. Based on some user-defined success criteria, we can also track how successful these warnings are.
Many Inner Circle Trader (ICT) students have noted that choppy New York sessions are often preceded by erratic London sessions which take both the high and low of the Asian range.
When this criteria is true and warnings are enabled, a table will automatically populate with a custom warning message for the duration of the NY session, indicating to the user that it could be a choppy trading day.
We can measure and track the success rate of these warnings via the following success criteria:
- NY stays within London range
- NY exceeds London high and low
- NY closes within London range
- NY range is too small
The first three criteria should be self explanatory - the NY range either stays within the London high & low, exceeds them both, or closes within them.
The last criteria is a measure of the New York range compared to a user defined standard deviation of all historical ranges (for the number of sessions that the current chart can load). The default value of 1.5 would imply that a "successful" S&D day could be if the NY range (from high to low) was less than or equal to 1.5 standard deviations of all past ranges.
All these options can be toggled on/off as well, for those that only want to consider certain success criteria and not others. When any of the selected success criteria are true, that essentially indicates that the current session's warning was successful.
Choppy
Advanced Choppiness Indicator with CPMA"The Advanced Choppiness Indicator with CPMA is a technical analysis tool designed to assist traders in identifying choppy market conditions and determining trend direction. It combines two key components: the Choppiness Index and a Custom Price Moving Average (CPMA).
The Choppiness Index is calculated using the Average True Range (ATR), which measures market volatility. It compares the ATR to the highest high and lowest low over a specified period. A higher Choppiness Index value indicates choppier market conditions, while a lower value suggests smoother and more directional price movements.
The CPMA is a custom moving average that takes into account various price types, including the close, high, low, and other combinations. It calculates the average of these price types over a specific length. The CPMA provides a smoother trend line that can help identify support and resistance levels more accurately than traditional moving averages.
When using this indicator, pay attention to the following elements:
Yellow range boxes: These indicate choppy zones, where market conditions are characterized by low momentum and erratic price action. Avoid entering trades during these periods.
Histogram bars: Green bars suggest an uptrend, while red bars indicate a downtrend. These bars are based on the CPMA and can help confirm the prevailing trend direction.
CPMA angle: The angle of the CPMA line provides further insight into the trend. A positive angle indicates an uptrend, while a negative angle suggests a downtrend.
Choppiness thresholds: The indicator includes user-defined thresholds for choppiness. Values above the high threshold indicate high choppiness, while values below the low threshold suggest low choppiness.
Trade decisions: Consider the information provided by the indicator to make informed trading decisions. Avoid trading during choppy zones and consider entering trades in the direction of the prevailing trend.
Remember that the indicator's parameters, such as ATR length and CPMA length, can be adjusted to suit your trading preferences and timeframe. However, it's important to use this indicator in conjunction with other technical analysis tools and your trading strategy for comprehensive market analysis."
By combining the Choppiness Index, CPMA, and other visual cues, this indicator aims to help traders identify suitable trading conditions and make more informed decisions based on market trends and volatility.
Local Model Kalman Market ModeIntroduction
Heyo guys, I made a new (repainting) indicator called Local Model Kalman Market Mode.
I created it, because I wanted a reliable market mode filter for a potential mean-reversion strategy (e. g. BB Scalping).
On the screenshot you can see an example of how to use it in a BB strategy.
E.g. you would enter long when you have bullish divergence, price is under lower BB, price is under PoC and this indicator here shows range-bound market phase.
You would exit long on cross of the middle band.
Description
The indicator attempts to model the underlying market using different local models (i.e., trending, range-bound, and choppy) and combines them using the T3 Six Pole Kalman Filter to generate an overall estimate of the market.
The Fisher Transform is applied on the price to reach a Gaussian distribution, which increases the accuracy of the indicator itself.
The script first defines state variables for each local model, which include trend direction, trend strength, upper and lower bounds of the range, volatility of the range, level of choppiness, and strength of noise.
Then, likelihood functions are defined for each local model based on the state variables.
Next, the script calculates weights for each local model based on their likelihoods and uses them to calculate state variables for the overall estimate.
Finally, the script combines the state variables using the T3 Six Pole Kalman Filter to generate the overall estimate of the market, which is plotted in blue.
Fundamental Knowledge
To understand the explanation of the indicator and the script, there are a few fundamental concepts that you need to know:
Market: A market is a place where buyers and sellers come together to exchange goods or services.
In the context of trading, the market refers to the exchange where financial instruments such as stocks, currencies, and commodities are bought and sold.
Local models: Local models are statistical models that attempt to capture the characteristics of a particular market regime.
For example, a trending market may have different characteristics than a range-bound market or a choppy market.
The indicator uses different local models to capture the different market regimes.
Trend direction and strength: The trend direction refers to the direction in which the market is moving, either up or down.
The trend strength refers to the magnitude of the trend and how likely it is to continue.
Range-bound market: A range-bound market is a market where prices are trading within a specific range, with a clear upper and lower bound.
Choppiness: Choppiness refers to the degree of irregularity in price movements, often seen in sideways or range-bound markets.
Volatility: Volatility refers to the degree of variation in the price of an asset over time. High volatility implies larger price swings, while low volatility implies smaller price swings.
Kalman filter: A Kalman filter is a mathematical algorithm used to estimate an unknown variable from a series of noisy measurements.
In the context of the indicator, the Kalman filter is used to generate an overall estimate of the market by combining the local models.
T3 Six Pole Kalman Filter: The T3 Six Pole Kalman Filter is a specific type of Kalman filter that is used to smooth and filter time-series data, such as the price data of a financial instrument.
Fisher Transform: The Fisher Transform is a mathematical formula used to transform any probability distribution into a Gaussian normal distribution. It is commonly used in technical analysis to transform non-Gaussian indicators into ones that are more suitable for statistical analysis.
By understanding these fundamental concepts, you should have a basic understanding of how the indicator works and how it generates an overall estimate of the market.
Usage
You can use this indicator on every timeframe.
Users can customize the parameters of the T3 Six Pole Kalman Filter (T3 length, alpha, beta, gamma, and delta) using input functions.
Try out different parameter combinations and use the one you like most.
Thank you for checking this out. Leave me a comment or boost the script, when you wanna support me! 👌
--
Credits to:
▪@HPotter - Fisher Transform
▪@loxx - T3
▪ChatGPT - Helped me to make the research for this indicator and helped to build the core algorithm.
Choppy Market EMA IdentificationThis indicator could be used to identify choppy Market Conditions based on the EMA.
It is an EMA that could be configured to only show up, if the last 1..n candles are NOT crossing the EMA in any direction.
I figured out that lower timeframes ( < 30 min) often the price bounces around the 200 EMA and gives lot of false signals using different strategies.
So i decided to write a small indicator to avoid taking trades in those market conditions.
The Indicator could be configured for the length of the EMA and how many crosses must be happened in the defined numbers of candles.
Choppy Market EMA IdentificationThis indicator could be used to identify choppy Market Conditions based on the EMA.
It is an EMA that could be configured to only show up, if the last 1..n candles are NOT crossing the EMA in any direction.
I figured out that lower timeframes ( < 30 min) often the price bounces around the 200 EMA and gives lot of false signals using different strategies.
So i decided to write a small indicator to avoid taking trades in those market conditions.
The Indicator could be configured for the length of the EMA and how many crosses must be happened in the defined numbers of candles.
Choppy Market EMA IdentificationThis indicator could be used to identify choppy Market Conditions based on the EMA.
It is an EMA that could be configured to only show up, if the last 1..n candles are NOT crossing the EMA in any direction.
I figured out that lower timeframes ( < 30 min) often the price bounces around the 200 EMA and gives lot of false signals using different strategies.
So i decided to write a small indicator to avoid taking trades in those market conditions.
The Indicator could be configured for the length of the EMA and how many crosses must be happened in the defined numbers of candles.
RedK Chop & Breakout Scout (C&B_Scout)The RedK Chop & Breakout Scout (C&BS or just CBS) is a centered oscillator that helps traders identify when the price is in a chop zone, where it's recommended to avoid trading or exit existing trades - and helps identify (good & tradeable) price breakouts.
i receive many questions asking for simple ways to identify chops .. Here's one way we can do that.
(This is work in progress - i was exploring with the idea, and wasn't sure how interesting other may find it. )
Quick Intro:
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Quick techno piece: This concept is similar to a Stochastic Oscillator - with the main difference being that we're utilizing units of ATR (instead of a channel width) to calculate the main indicator line - which will then lead to a non-restricted oscillator (rather than a +/- 100%) - given that ATR changes with the underlying and the timeframe, among other variables.
to make this easy, and avoid a lot of technical speak in the next part, :) i created (on the top price panel) the same setup that the C&B Scout represents as a lower-panel indicator.
So as you read below, please look back and compare what C&BS is doing in its lower panel, with how the price is behaving on the price chart.
how this works
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- To identify chops and breakouts, we need to first agree on a definition that we will use for these terms.
- for the sake of this exercise, let's agree that the price is in a chop zone, as long as the price is moving within a certain distance from a "price baseline" of choice ( which we can adjust based on the underlying, the volatility, the timeframe, the trading style..etc)
- when the price moves out of that chop zone, we consider this a breakout
- Now not all breakouts are "good" = they need to at least happen in the direction of the longer term trend. In this case, we can apply a long Moving Average to act as a filter - and consider breakouts to be "good" if they are in the same direction as the filter line
- With the above background in mind, we establish a price baseline (as you see on the top panel, this is based on the midline of a Donchian Channel - but we can use other slow moving averages in future versions)
- we will decide how far above/below that baseline is considered to be "chop zone" - we do this in terms of units of Average True Range (ATR) - using ATR here is valuable for so many reasons, most of all, how it adjusts to timeframe and volatility of underlying.
- The C&B Scout line simply calculates how far the price is above/below the baseline in terms of "ATR units". and shows how that value compares to our own definition of a "chop zone"
- so as long as the price is within the chop zone, the CBS line will be inside the shaded area - and when the price "breaks out" of the chop zone, the CBS line will also breakout (or down) from the chop zone.
- C&B Scout will give a visual clue to help take trades in the direction of the prevailing trend - the chop zone is green when the price is in "long mode", as in, the price is above the filter line - and will be red when we are in "short mode" - so the price is below the filter line. in green mode, we should only consider breakouts to the upside, and ignore breakouts to the downside (or breakdowns) - in red mode, we should only consider breakouts to the downside., and ignore the ones to the upside.
- i added some examples of "key actions" on the chart to help explain the approach here further.
Usage & settings Notes:
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- even though for many traders this will be a basic concept/setup, i still highly suggest you spend time getting used to how it works/reacts and adjusting the settings to suit your own trading style, timeframe, tolerance, what you trade....etc
- for example, if i am a conservative trader, i may consider any price movement within 1 x ATR above and below the baseline to be in "chop" (ATR Channel width = 2 x ATR) - and i want to only take trades when the price moves outside of that range *and* in the direction of the prevailing trend
- An aggressive trader may use a smaller ATR-based value, say 0.5 x ATR above/below the baseline, as their chop zone.
- A swing trader may use a shorter filter line and focus on the CBS line crossing the 0 line.
- .... and so on.
- Also note that the "tradeable" signal is when the CBS line "exits" the chop zone (upward on green background, or downward on red background) - however, an aggressive trader may take the crossing of the CBS line with the 0 line as the signal to open a trade.
- As usual please do not use this indicator "in isolation" and ensure you have other confirming signals from your setups before trading.
conclusion
===========
As i mentioned, this is really a simple concept - and i'm a big fan of those :) -- and there's so much that could be done to expand around it (add more visuals/colors, add alerts, add options for ATR calculation, Filter line calculations, baseline..etc) - but with this v1.0, i wanted to share this initially and see how much interest and how valuable fellow traders find it, before playing any further with it. so please be generous with your comments.
Price density [Measuring Market Noise:Take advantage]$$ Market noise can be problematic to some types of trading strategies yet beneficial to others.
By measuring noise using the 'Price Density' can enable us to improve our
trading edge and turn noise to our advantage.
Robust analysis of noise can inform us when it is best to avoid trend-following
systems (when noise is too high), and vice versa for systems based on a
mean-reverting trading premise (when market noise is low).
__________________________________________________________________________
Using Noise to our advantage
* Two techniques:
-Measure Noise and trade when suitable for the system
~ High noise = avoid trend-following
~ Low noise = avoid mean-reversion
-Match assets to strategies
~ Only trade 'noisy assets' with Mean-reversion Strategies
~ Only trade 'efficient assests' with Trend-following Strategies
## Price density:-
High values = High noise
Low values = Low noise
___________________________________________________________________________
Disclaimer!! Do your own research
Ehlers Squelch Indicator [CC]The Squelch Indicator was created by John Ehlers (Stocks & Commodities V. 18:9 (42-46)) and this indicator is a variation of his Market Mode Indicator and its purpose is the same as in it determines if the market is trending or in a choppy market. If this indicator is at the 1 level then this means the market is trending and if it is at 0 then the market is choppy. I would recommend to adjust the squelch variable to find a setting that works well for you. If you want to avoid more choppy markets then adjust the squelch variable to a lower amount and vice versa. I have included basic buy and sell signals so buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Ehlers Market Mode Indicator [CC]The Market Mode Indicator was created by John Ehlers (Rocket Science For Traders pgs 114-117) and this is a handy tool that will tell you if the market is currently in a cycle or a trend. When the current market is in a cycle or choppy state then the indicator will read 0 and when it is in a trend then it will read 1. He uses some advanced digital signal processing to figure out the current trend and for how long it has been trending. I have included buy and sell signals using the trendline and so buy when the line turns green and sell when it turns red. Let me know if this indicator is useful for you.
Let me know if there are any other indicators you would like to see me publish!
Price Cross Range StrengthPurpose:
This script shows when price is in a range or trending. When the green line rises above the threshold the price is trending. When the green line falls below the threshold it's ranging. You may try adjusting the lookback way far back to find more areas of resistance.
Logic:
It shows how many instances the current price has been crossed in the past measured bars. The logic is that any price area that has been crossed many times is a strong area where ranging occurs.
Ideas:
1. Can be used as a dynamic length to other moving averages.
RSI chop filterThis demonstrates how you might filter your signals using RSI, but the same technique could be applied to Stochastic RSI and any other oscillator that has overbought and oversold conditions.
Use it as a visual indicator to determine when to enter a trade:
Red = Chop zone (no trade)
Bright red = Tight chop (dear god stay away)
Green = Overbought or oversold (signals permitted)
Bright green = Crossing up/down (take the trade)
To apply the filter, simply add 'and not chop' after your conditions as seen in the commented out example.
BERLIN Range Index | Panel versionThe original problem: The choppiness index is great at finding ranging markets, but it is sometimes very slow, which means most of the time it only catches the end of a trend.
This indicator tries to solve this. It uses the choppiness index and filters it using a factor that is based on the standard deviation of the ATR.
The ATR based filter is calculated by first calculating the running standard deviation of the ATR, and then looking at that in relation to its recent low to find a filtering factor to use on the choppiness index. This makes the choppiness index more reactive to trends, but also slightly more likely to missidentify ranges.
This is the panel version of the indicator. It plots the index and min/max values, as well as background colors to tell you when it thinks the market is ranging or trending.
Yellow = Trending
Transparent gray = Ranging
BERLIN Range Index | Bar color versionThe original problem: The choppiness index is great at finding ranging markets, but it is sometimes very slow, which means most of the time it only catches the end of a trend.
This indicator tries to solve this. It uses the choppiness index and filters it using a factor that is based on the standard deviation of the ATR.
The ATR based filter is calculated by first calculating the running standard deviation of the ATR, and then looking at that in relation to its recent low to find a filtering factor to use on the choppiness index. This makes the choppiness index more reactive to trends, but also slightly more likely to missidentify ranges.
This is the bar color version of the indicator. It changes the color of the bars when it it thinks the market is ranging and when it thinks it is trending.
Yellow = Trending
Transparent gray = Ranging
IO_EMA_Delta_OscillatorThis is a EMA Delta Oscillator: An attempt to show ranging markets based on the slope of the EMA.
Green = Bullish Market
Blue = Ranging Market
Red = Bearish Market
The EMA Slope is normalized to make it work like an oscillator with values between 0 and 1.
Bar colors show the oscillator colors, bar borders show the actual candle colors.
- Invsto
(sarangab)
Action Section, Volatility Choppiness Indicator (by ChartArt)Here is a solution to find entry points to trade. This indicator highlights price sections with low choppiness, where both the ADX (Average Directional Index) indicator shows strong movement (up or down!) in the price and a customized Money Flow indicator (which uses only the change of the volume not the change of the price, hence a Volume Flow indicator), also shows volatility is present. Using higher filter values than the default setting of "30" reduces the noise, but also shows less 'action sections'. Vice versa using values lower than "30" increases the amount and duration of action sections which are shown.
The "action section" indicator does not show the direction if the price is going up or down. It shows if there is enough action worthy the time to trade (lower odds of a neutral sideways trend). Therefore in addition a Heikin-Ashi based price change indicator can optionally be plotted, which shows the actual direction of the price.
Action Section, High Volume Volatility & Low Price Choppiness Indicator
This indicator works only on charts which have volume data.
