Katalyst's Opening Range BreakoutKatalyst's Opening Range Breakout + No Trade Zone
📜 Overview:
This indicator allows traders to visualize the high and low of the opening range for a user-selected timeframe (e.g., 30s, 1m, 5m, 15m). It features fully customizable lines, labels, and an optional **No Trade Zone** fill to help you identify breakout levels with ease.
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🎯 Key Features:
1. **Customizable Opening Range**:
- Select your preferred opening range duration: **30 seconds, 1 minute, 2 minutes, 5 minutes, 10 minutes, or 15 minutes**.
- The indicator calculates and plots the **high** and **low** of the selected opening range.
2. **Dynamic Line Styling**:
- Choose the **line color**, **transparency**, and **style**: **Solid, Dashed, or Dotted**.
- Lines extend to the right of the chart for clarity.
3. **No Trade Zone** *(Optional / Disabled by default)*:
- When enabled, fills the area between the high and low lines with a customizable **color and transparency**.
- Helps visually identify consolidation areas where trading might be avoided.
4. **Labels for Precision**:
- Clearly displays the **Opening Range High** and **Low** values.
- Labels are color-coded and positioned dynamically for easy interpretation.
5. **Clean and Efficient Updates**:
- The indicator deletes old lines, labels, and fills before creating new ones, ensuring a clutter-free chart.
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⚙️ How to Use:
1. **Select Your Timeframe**:
- From the settings, choose your desired opening range duration: 30s, 1m, 2m, 5m, 10m, or 15m.
2. **Customize the Visuals**:
- Adjust line color, style, and transparency.
- Enable the **No Trade Zone** for a transparent background fill between the high and low lines.
3. **Interpret the Breakout**:
- Watch for price movements above or below the **opening range** to identify potential breakout opportunities.
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🛠 Settings:
Opening Range Duration: Select the timeframe for the opening range (30s, 1m, 2m, 5m, 10m, 15m).
Line Color: Set the color of the range lines.
Line Transparency: Adjust the transparency of the lines (0 = solid, 100 = invisible).
Line Style: Choose line style: Solid, Dashed, or Dotted.
Label Colors: Customize the label colors for the high and low values.
Enable No Trade Zone: Fill the area between high and low lines with a transparent color.
No Trade Zone Color: Set the fill color for the no trade zone.
No Trade Zone Transparency: Adjust the transparency of the no trade zone fill.
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📈 Ideal For
Day traders and scalpers looking to trade **breakouts**.
Traders who want to identify areas of consolidation visually.
Anyone who relies on the **opening range** for their trading strategy.
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🔍 Example Usage:
Set the opening range to **5 minutes** and enable the **No Trade Zone** with a light red fill.
Watch for price to break above or below the high/low lines to signal potential trade opportunities.
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✨ Why Use This Indicator?
This script simplifies your breakout strategy by providing a clear, visually appealing representation of the opening range. The flexible customization options and the optional **No Trade Zone** make it a powerful tool for identifying high-probability trades.
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Let me know if you need any additional tweaks or clarifications for this description. It's all set to help traders understand and use your powerful script! 🚀📈
Indicator
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. Indicator
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Variety MA Cluster Filter Crosses [Loxx]What is a Cluster Filter?
One of the approaches to determining a useful signal (trend) in stream data. Small filtering (smoothing) tests applied to market quotes demonstrate the potential for creating non-lagging digital filters (indicators) that are not redrawn on the last bars.
Standard Approach
This approach is based on classical time series smoothing methods. There are lots of articles devoted to this subject both on this and other websites. The results are also classical:
1. The changes in trends are displayed with latency;
2. Better indicator (digital filter) response achieved at the expense of smoothing quality decrease;
3. Attempts to implement non-lagging indicators lead to redrawing on the last samples (bars).
And whereas traders have learned to cope with these things using persistence of economic processes and other tricks, this would be unacceptable in evaluating real-time experimental data, e.g. when testing aerostructures.
The Main Problem
It is a known fact that the majority of trading systems stop performing with the course of time, and that the indicators are only indicative over certain intervals. This can easily be explained: market quotes are not stationary. The definition of a stationary process is available in Wikipedia:
A stationary process is a stochastic process whose joint probability distribution does not change when shifted in time.
Judging by this definition, methods of analysis of stationary time series are not applicable in technical analysis. And this is understandable. A skillful market-maker entering the market will mess up all the calculations we may have made prior to that with regard to parameters of a known series of market quotes.
Even though this seems obvious, a lot of indicators are based on the theory of stationary time series analysis. Examples of such indicators are moving averages and their modifications. However, there are some attempts to create adaptive indicators. They are supposed to take into account non-stationarity of market quotes to some extent, yet they do not seem to work wonders. The attempts to "punish" the market-maker using the currently known methods of analysis of non-stationary series (wavelets, empirical modes and others) are not successful either. It looks like a certain key factor is constantly being ignored or unidentified.
The main reason for this is that the methods used are not designed for working with stream data. All (or almost all) of them were developed for analysis of the already known or, speaking in terms of technical analysis, historical data. These methods are convenient, e.g., in geophysics: you feel the earthquake, get a seismogram and then analyze it for few months. In other words, these methods are appropriate where uncertainties arising at the ends of a time series in the course of filtering affect the end result.
When analyzing experimental stream data or market quotes, we are focused on the most recent data received, rather than history. These are data that cannot be dealt with using classical algorithms.
Cluster Filter
Cluster filter is a set of digital filters approximating the initial sequence. Cluster filters should not be confused with cluster indicators.
Cluster filters are convenient when analyzing non-stationary time series in real time, in other words, stream data. It means that these filters are of principal interest not for smoothing the already known time series values, but for getting the most probable smoothed values of the new data received in real time.
Unlike various decomposition methods or simply filters of desired frequency, cluster filters create a composition or a fan of probable values of initial series which are further analyzed for approximation of the initial sequence. The input sequence acts more as a reference than the target of the analysis. The main analysis concerns values calculated by a set of filters after processing the data received.
In the general case, every filter included in the cluster has its own individual characteristics and is not related to others in any way. These filters are sometimes customized for the analysis of a stationary time series of their own which describes individual properties of the initial non-stationary time series. In the simplest case, if the initial non-stationary series changes its parameters, the filters "switch" over. Thus, a cluster filter tracks real time changes in characteristics.
Cluster Filter Design Procedure
Any cluster filter can be designed in three steps:
1. The first step is usually the most difficult one but this is where probabilistic models of stream data received are formed. The number of these models can be arbitrary large. They are not always related to physical processes that affect the approximable data. The more precisely models describe the approximable sequence, the higher the probability to get a non-lagging cluster filter.
2. At the second step, one or more digital filters are created for each model. The most general condition for joining filters together in a cluster is that they belong to the models describing the approximable sequence.
3. So, we can have one or more filters in a cluster. Consequently, with each new sample we have the sample value and one or more filter values. Thus, with each sample we have a vector or artificial noise made up of several (minimum two) values. All we need to do now is to select the most appropriate value.
An Example of a Simple Cluster Filter
For illustration, we will implement a simple cluster filter corresponding to the above diagram, using market quotes as input sequence. You can simply use closing prices of any time frame.
1. Model description. We will proceed on the assumption that:
The aproximate sequence is non-stationary, i.e. its characteristics tend to change with the course of time.
The closing price of a bar is not the actual bar price. In other words, the registered closing price of a bar is one of the noise movements, like other price movements on that bar.
The actual price or the actual value of the approximable sequence is between the closing price of the current bar and the closing price of the previous bar.
The approximable sequence tends to maintain its direction. That is, if it was growing on the previous bar, it will tend to keep on growing on the current bar.
2. Selecting digital filters. For the sake of simplicity, we take two filters:
The first filter will be a variety filter calculated based on the last closing prices using the slow period. I believe this fits well in the third assumption we specified for our model.
Since we have a non-stationary filter, we will try to also use an additional filter that will hopefully facilitate to identify changes in characteristics of the time series. I've chosen a variety filter using the fast period.
3. Selecting the appropriate value for the cluster filter.
So, with each new sample we will have the sample value (closing price), as well as the value of MA and fast filter. The closing price will be ignored according to the second assumption specified for our model. Further, we select the МА or ЕМА value based on the last assumption, i.e. maintaining trend direction:
For an uptrend, i.e. CF(i-1)>CF(i-2), we select one of the following four variants:
if CF(i-1)fastfilter(i), then CF(i)=slowfilter(i);
if CF(i-1)>slowfilter(i) and CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i)).
For a downtrend, i.e. CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i));
if CF(i-1)>slowfilter(i) and CF(i-1)fastfilter(i), then CF(i)=fastfilter(i);
if CF(i-1) Indicator
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CHOP Zone Entry Strategy + DMI/PSAR ExitThis is a Strategy with associated visual indicators and Long/Short and Reverse/Close Position Alerts for the Choppiness Index (CHOP) . It is used to determine if the market is choppy (trading sideways) or not choppy (trading within a trend in either direction). CHOP is not directional, so a DMI script was ported into this strategy to allow for trend confirmation and direction determination; it consists of an Average Directional Index (ADX) , Plus Directional Indicator (+DI) and Minus Directional Indicator (-DI) . In addition, a Parabolic SAR is also included to act as a trailing stop during any strong trends.
Development Notes
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This indicator, and most of the descriptions below, were derived largely from the PulseWire reference manual. Feedback and suggestions for improvement are more than welcome, as well are recommended Input settings and best practices for use.
www.pulsewire.com
www.pulsewire.com
www.pulsewire.com
Recommend using the below DMI and PSAR indicators in conjunction with this script to fully visualize and understand how entry and exit conditions are chosen. Variable inputs should correlate between the scripts for uniformity and visual compatibility.
THANKS to LazyBear and his Momentum Squeeze script for helping me quickly develop a momentum state model for coloring the Chop line by trend.
Strategy Description
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CHOP produces values that determine whether the market is choppy or trending . The closer the value is to 100 , the higher the choppiness levels , while the closer it is to 0 , the stronger the market is trending . Territories for both levels, and their associated upper and lower thresholds, are popularly defined using the Fibonacci Retracements, 61.8 and 38.2.
Basic Use
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CHOP is often used to confirm the market condition to help you stay out of sideways markets and only enter when there is movement or imminent explosions. When readings are above the upper threshold, continued sideways movement may be expected, while readings below the lower threshold are typically indicative of a continuing trend. It is also used to anticipate upcoming trendiness changes, with the general belief that extended periods of consolidation (sideways movement) are followed by extended periods of strong, trending, directional movement, and vice versa.
One limitation in this index is that you must be cautious in deciding whether the range or trend will likely continue, or if it will reverse.
Confidence in price action and trend is higher when two or more indicators are in agreement -- while this strategy combines CHOP with both DMI and PSAR, we would still recommend pairing with other indicators to determine entry or exit trade opportunities.
Recommend also choosing 'Once Per Bar Close' when creating alerts.
Inputs
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Strategy Direction - an option to only trade Short, Long, Both, or only in the direction of the Trend (Follow Trend is the Default).
Sensitivity - an incremental variable to test whether the past n candles are in the same trend state before triggering a delayed long or short alert (1 is the Default). Can help filter out noise and reduces active alerts.
Show Chop Index - two visual styles are provided for user preference, a visible Chop line with a background overlay, or a compact column and label only view.
Chop Lookback Period - the time period to be used in calculating CHOP (14 is the Default).
Chop Offset - changing this number will move the CHOP either forwards or backwards relative to the current market (0 is the Default).
Smooth Chop Line and Length - if enabled, the entered time period will be used in calculating a smooth average of the index (Enabled and 4 are the Defaults).
Color Line to Trend Direction - toggles whether the index line is colored to visually depict the current trend direction (Enabled is the Default).
Color Background - toggles the visibility of a background color based on the index state (Enabled is the Default).
Enable DMI Option - if enabled, then entry will be confirmed by and dependent on the ADX Key Level, with any close or reversal confirmed by both ADX and +/-DI to determine whether there is a strong trend present or not (Enabled is the Default).
ADX Smoothing - the time period to be used in calculating the ADX which has a smoothing component (14 is the Default).
DI Length - the time period to be used in calculating the DI (14 is the Default).
ADX Key Level - any trade with the ADX above the key level is a strong indicator that it is trending (23 to 25 is the suggested setting).
Enable PSAR Option - enables trailing stop loss orders (Enabled is the Default).
PSAR Start - the starting value for the Acceleration Force (0.015 is our chosen Default, 0.02 is more common).
PSAR Increment - the increment in which the Acceleration Force will move (0.001 is our chosen Default, 0.02 is more common).
PSAR Max Value - the maximum value of the Acceleration Factor (0.2 is the Default).
Color Candles Option - an option to transpose the CHOP condition levels to the main candle bars. Note that the outer red and green border will still be distinguished by whether each individual candle is bearish or bullish during the specified timeframe.
Note too that if both DMI and PSAR are deselected, then close determinations will default to a CHOP reversal strategy (e.g., close long when below 38.2 and close short when above 61.8). Though if either DMI or PSAR are enabled, then the CHOP reversal for close determination will automatically be disabled.
Indicator Visuals
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For the candle colors, black indicates tight chop (45 to 55), yellow is loose chop (38.2 to 45 and 55 to 61.8), dark purple is trending down (< 38.2), and dark blue is trending up (> 61.8).
The background color has additional shades to differentiate a wider range of more levels…
• < 30 is dark purple
• 30 to 38.2 is purple
• 38.2 to 45 is light purple
• 45 to 55 is black
• 55 to 61.8 is light blue
• 61.8 to 70 is blue
• > 70 is dark blue
Long, Short, Close, and Reverse labels are plotted on the Chop line, which itself can be colored based on the trend. The chop line can also be hidden for a clean and compact, columnar view, which is my preferred option (see example image below).
Visual cues are intended to improve analysis and decrease interpretation time during trading, as well as to aid in understanding the purpose of this strategy and how its inclusion can benefit a comprehensive trading plan.
DMI and Trend Strength
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To analyze trend strength, the focus should be on the ADX line and not the +DI or -DI lines. An ADX reading above 25 indicates a strong trend , while a reading below 20 indicates a weak or non-existent trend . A reading between those two values would be considered indeterminable. Though what is truly a strong trend or a weak trend depends on the financial instrument being examined; historical analysis can assist in determining appropriate values.
DMI exits trade when ADX is below the user selected key level (e.g., default is 25) and when the +/- DI lines cross (e.g., -DI > +DI exits long position and +DI > -DI exits short position).
PSAR and Trailing Stop
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PSAR is a time and price based indicator that excels at measuring direction and duration, though not the actual strength of a trend, which is why we use this in conjunction with DMI. It is also included in this script as a trailing stop option to maximize gains during strong trends and to mitigate any false ADX strengthening signals.
This creates a parabola that is located below the candle during a Bullish trend and above during a Bearish trend. A buy or reversal is signaled when the price crosses above or below the Parabolic SAR.
Long/Short Entry
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1. CHOP must be over 61.8 (long) or under 38.2 (short).
2. If DMI is enabled, then the ADX signal line must be above the user selected Key Level (default is 25).
3. If Sensitivity is selected, then that past candle must meet the criteria in step 1, as well as all the intermediate candles in between.
4. If "Follow Trend" is selected and PSAR is enabled, then a long position can only open when the momentum and PSAR are in an uptrend, or short when both are in a downtrend, to include all intermediate candles if the Sensitivity option is set on a past candle.
Close/Reverse
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1. If DMI is enabled, then a close flag will be raised when the ADX signal drops below the Key Level (of 25), and -DI crosses over +DI (if long), or +DI crosses over -DI (if short).
2. If PSAR is enabled, then a close flag will be raised when the current trend state is opposite the last state.
3. If both DMI and PSAR are disabled, then a close flag will be raised if the Chop line drops under 38.2 (if long) or goes over 61.8 (if short).
4. If a Long or Short Entry is triggered on the same candle as any of the above close flags, then the position will be reversed, else the position will be closed.
Strategy Alerts
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1. Long Entry
2. Short Entry
3. Reverse
4. Close
The provided backtest result is based on a position sizing of 10% equity with 100k initial capital. When testing SPX, disabling the DMI performed the best, but EURUSD performed poorly without it enabled, and TSLA had a small reduction in net profit. Timeframe likewise differed between commodities with TSLA performing best at 30M, SPX at 15M, and EURUSD at 4H. I do not plan on using this as a standalone strategy, but I also was expecting better results with the inclusion of EMI and PSAR to compliment the CHOP. Key elements of this script will likely be included in future, more holistic strategies.
Disclaimer
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Past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script are not intended to provide any financial advice. Trade at your own risk.
No known repainting, though there may be if an offset is introduced in the Inputs. I did my best not to code any other variables that repaint, but cannot fully attest to this fact.
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