Moving Average Crossover MonitorMoving Average Crossover Monitor: Gain Insight into Market Trends
The Moving Average Crossover Monitor is a specialized tool crafted for traders seeking to understand and predict market trends more effectively. This indicator's primary focus lies in analyzing consecutive candle movements above or below specified moving averages and providing predictive estimates based on historical data.
Key Features:
1. Consecutive Candle Tracking: The indicator meticulously counts and tracks the number of consecutive candles that close above or below a selected moving average (MA1). This tracking offers a tangible measure of trend persistence over time.
2. Historical Analysis for Future Prediction: By analyzing past trends, the indicator provides insights into potential future movements. It estimates the likelihood of upcoming candles continuing above or below the moving average based on historical patterns.
3. Dynamic Visualization: Moving averages (SMA, WMA, EMA) are dynamically plotted on the chart, clearly displaying crossover points and trend transitions.
How It Works:
1. Moving Average Calculation: Select your preferred moving average type (SMA, WMA, EMA) and define short and long periods. The indicator computes two moving averages (MA1 and MA2) based on these parameters.
2. Consecutive Candle Analysis:
- Above MA1: Tracks and counts consecutive candles closing above MA1, indicating potential bullish momentum.
- Below MA1: Tracks and counts consecutive candles closing below MA1, suggesting potential bearish sentiment.
3. Future Trend Prediction: Based on historical data of consecutive candle movements, the indicator estimates the likelihood of the next candle continuing in the same direction (above or below MA1).
Advantages for Traders:
1. Quantitative Insights: Use numerical data on consecutive candles to gauge trend strength and durability.
2. Predictive Analytics: Leverage historical patterns to anticipate future market movements and adjust trading strategies accordingly.
3. Decision Support Tool: Gain clarity on trend transitions, empowering timely and informed trading decisions.
Disclaimer:
This indicator is provided for educational purposes only and should not be considered as financial advice. Trading involves risks, and past performance is not indicative of future results. Traders should conduct their own analysis and exercise caution when making trading decisions based on any indicator or tool. Always consider risk management strategies and consult with a qualified financial advisor if needed.
Moving_average
NSE Percentage of stocks above Moving AveragesThis indicator displays the percentage of NSE (India) stocks trading above key moving averages.
Market breadth measures the degree of participation & the conviction in the overall mood of the underlying index. A positive market breadth is said to happen when more stocks are advancing than are declining. Among many ways to measure this, one simple way is the % of stocks trading above a certain moving average. When most of the stocks are trading above a specific moving average, the market breadth is termed strong.
This script uses 10-day & 20-day EMA for short-term timeframes, & 50-day & 200-day EMA for medium to long-term timeframes.
Default Mode
We have a bullish bias when >50% of stocks are above their 50-day and 200-day MAs. We have a bearish bias when <50% of stocks are above their 50-day and 200-day MAs.
We also look at short-term timeframes (10 & 20 MA) for overbought and oversold levels. Values above 80% are considered overbought and readings below 20% are deemed oversold .
Individual Moving averages, & the table also, can be turned off.
Oversold/overbrought market breadth does not necessarily indicate reversal, but rather an exhaustion. This can get resolved by either a price correction or a time correction. The breadth can remain in overbought zones for a long time while the price is in a strong uptrend — and equally so at oversold zones during a strong downtrend.
Moving Average of Market Breadth
Turning-on the MA of breadth displays the 50-day Moving Average of the % of stocks above the 50-day Moving Average.
This is another way to visualise a smoothed version of the market breadth. If the % of stocks above the 50-day Moving Average is above its own 50-day Moving Average, then we can say that the breadth is strong.
Mini Mode
Turning on the mini-mode converts the table into a 4-color block, with the blocks reflecting the status of 10, 20, 50 & 200 MAs respectively, from top to bottom.
Text Mode
Turning on the text-mode converts the percentage numbers in the table into 1-word text descriptions.
Dependency:
The script uses the Pine Seeds service to import custom data hosted in a GitHub repository and accesses it via TradingView as the frontend. So, the number of bars appearing on charts is fully dependent on the amount of historical data available. Any error or omission, if there, is a reflection of the hosted data, & not that of TradingView.
Limitations:
Such data has some limitations, like it can only be updated at EOD (End-of-Day), & only daily-based timeframes can be applied to such data. Irrespective of the intraday changes, only the last saved value on the chart is seen. So, it's best to use this script as EOD, rather than intraday.
At the time of publication of this script, historical data was available till the year 2004.
The universe of stocks chosen for the data is all stocks with latest Close >= 1 and Market Cap > 10.
Credits:
NSE Market Breadth data is from Chhirag_Kedia , & the Pine seeds are courtesy of EquityCraze
Coiled Moving AveragesThis indicator detects when 3 moving averages converge and become coiled. This indicates volatility contraction which often leads to volatility expansion, i.e. large price movements.
Moving averages are considered coiled when the percent difference from each moving average to the others is less than the Coil Tolerance % input value.
This indicator is unique in that it detects when moving averages converge within a specified percent range. This is in contrast to other indicators that only detect moving average crossovers, or the distance between price and a moving average.
This indicator includes options such as:
- % difference between the MAs to be considered coiled
- type and length of MAs
- background color to indicate when the MAs are coiled
- arrows to indicate if price is above or below the MAs when they become coiled
While coiling predicts an increased probability for volatility expansion, it does not necessarily predict the direction of expansion. However, the arrows which indicate whether price is above or below the moving average coil may increase the odds of a move in that direction. Bullish alignment of the moving averages (faster MAs above the slower MAs) may also increase the odds of a bullish break, while bearish alignment may increase the odds of a bearish break.
Note that mean reversion back to the MA coil is common after initial volatility expansion. This can present an entry opportunity for traders, as mean reversion may be followed by continuation in the direction of the initial break.
Experiment with different settings and timeframes to see how coiled MAs can help predict the onset of volatility.
On Chart Reverse PMARPIntroducing the On Chart Reverse PMARP
Concept
The PMAR/PMARP is an indicator which calculates :
The ratio between a chosen source price and a user defined moving average ( Price Moving Average Ratio ).
The percentile of the PMAR over an adjustable lookback period ( Price Moving Average Ratio Percentile ).
Here I have 'reverse engineered' the PMAR / PMARP formulas to derive several functions.
These functions calculate the chart price at which the PMARP will cross a particular PMARP level.
I have employed those functions here to give the "crossover" price levels for :
Scale high level
High alert level
High test level
Mid-Line
Low test level
Low alert level
Scale low level
Knowing the price at which these various user defined PMARP levels will be crossed can be useful in setting price levels that trigger components of various strategies.
For example: A trader can use the reverse engineered upper high alert price level, to set a take profit limit order on a long trade, which was entered when PMARP was low.
This 'On Chart' RPMARP indicator displays these 'reverse engineered' price levels as plotted lines on the chart.
This allows the user to see directly on the chart the interplay between the various crossover levels and price action.
This allows for more intuitive Technical Analysis, and allows traders to precisely plan entries, exits and stops for their PMARP based trades.
It optionally plots the user defined moving average from which the PMARP is derived.
It also optionally plots the 'Reverse engineered' midline, test level lines, visual alert level lines, scale max. and min. level lines, and background alert signal bars.
Main Properties :
Price Source :- Choice of price values or external value from another indicator ( default *Close ).
PMAR Length :- User defined time period to be used in calculating the Moving Average for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *21 ).
MA Type :- User defined type of Moving Average which creates the MA for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *EMA ).
Checkbox and color selection box for the optionally plotted Moving Average line.
Price Moving Average Ratio Percentile Properties :
PMARP Length :- The lookback period to be used in calculating the Price Moving Average Ratio Percentile ( default *350 ).
PMARP Level Settings :
Scale High :- Scale high level ( Locked at 100 ).
Hi Alert :- High alert level ( default *99 ).
Hi Test :- High test level ( default *70 ).
Lid Line :- Mid line level ( Locked at 50 ).
Lo Test :- Low test level ( default *30 ).
Lo Alert :- Low alert level ( default *1 ).
Scale Low :- Scale low level ( Locked at 0 ).
Checkboxes and color selection boxes for each of the optionally plotted lines.
PMARP MA Settings :
Checkbox to optionally plot 'reverse engineered' PMARP MA line.
PMARP MA Length :- The time period to be used in calculating the signal Moving Average for the Line Plot ( default *20 ).
PMARP MA Type :- The type of Moving Average which creates the signal Moving Average for the Line Plot ( default *EMA ).
Color Type :- User choice from dropdown between "single" or "dual" line color ( default *dual ).
Single Color :- Color selection box.
Dual Color :- Color selection box. Note: Defines the color of the signal MA when the MA is falling in "dual" line coloring mode.
Signal Bar Settings :
Signal Bars Transparency :- Sets the transparency of the vertical signal bars ( default *70 ).
Checkboxes and color selection boxes for Upper/Lower alert signal bars.
Moving point of controlLibrary "moving_poc"
method getMovingPoc(averagePriceByVolumeHistory, ltfVolumeSerie, ltfPriceSerie, nbBarsToLookback)
Volume point of control (PoC) extracted from lower time frame data and previous time period
Namespace types: array
Parameters:
averagePriceByVolumeHistory (array) : An array of float to record previous PoC average
ltfVolumeSerie (array) : Source of volume for the lower timeframe (ltf)
ltfPriceSerie (array) : Source of price for the lower timeframe
nbBarsToLookback (int) : A number of bars determining the lookback period of this PoC
Returns: Serie of PoC
Johnny's Moving Average RibbonProps to Madrid for creating the original script: Madrid Moving Average Ribbon.
All I did was upgrade it to pinescript v5 and added a few changes to the script.
Features and Functionality
Moving Average Types: The indicator offers a choice between exponential moving averages (EMAs) and simple moving averages (SMAs), allowing users to select the type that best fits their trading strategy.
Dynamic Color Coding: Each moving average line within the ribbon changes color based on its direction and position relative to a reference moving average, providing visual cues for market sentiment and trend strength.
Lime Green: Indicates an uptrend and potential long positions, shown when a moving average is rising and above the longer-term reference MA.
Maroon: Suggests caution for long positions or potential short reentry points, displayed when a moving average is rising but below the reference MA.
Ruby Red: Represents a downtrend, suitable for short positions, shown when a moving average is falling and below the reference MA.
Green: Signals potential reentry points for downtrends or warnings for uptrend reversals, displayed when a moving average is falling but above the reference MA.
Usage and Application
Trend Identification: Traders can quickly ascertain the market's direction at a glance by observing the predominant color of the ribbon and its orientation.
Trade Entry and Exit Points: The color transitions within the ribbon can signal potential entry or exit points, with changes from green to lime or red to maroon indicating shifts in market momentum.
Customization: Users have the flexibility to toggle between exponential and simple moving averages, allowing for a tailored analytical approach that aligns with their individual trading preferences.
Technical Specifications
The ribbon consists of multiple moving averages calculated over different periods, typically ranging from shorter to longer-term intervals to capture various aspects of market behavior.
The color dynamics are determined by comparing each moving average to a reference point, often a longer-term moving average within the ribbon, to assess the relative trend strength and direction.
Trend: SMA with ATR Bands and EMA [Oxyge]Brief introduction:
Easy to use trend indicator to help find entry positions
How it works:
1, short-term trend judgment: EMA is greatly influenced by short-term trends, so it is very good to use it as a tool for judging short-term trends. At the same time, the filtering function has been added:
Long: green
Short: red
No direction: blue
2, the general trend judgment: the use of 30SMA as the default trend line, while increasing the ATR band to increase the scope of judgment.
How do I use (assuming it is now a period of long market):
1, first look at the 30SMA and ATR band, if the slope is positive (> 45 °), then ready to go long!
2. When price comes to the ATR band, the ATR band is my point of interest
3. Wait for a test of the ATR band: the EMA turns green, which means that the short-term trend is already nice and long.
4. Stop Loss Placement: Stop Loss is placed at the most recent low.
Closing
Enjoy it!
——————————————
简单介绍：
简单易用的趋势指标，帮助寻找进场位置
它怎么工作：
1、短期趋势判断：EMA受短期趋势影响很大，因此把它作为判断短期趋势的工具非常好用。同时增加了过滤功能：
多头：绿色
空头：红色
无方向：蓝色
2、大趋势判断：使用30SMA作为默认趋势线，同时增加ATR带增加判断范围。
我是如何使用的（假设是现在是一段多头行情）：
1、先看30SMA和ATR带，如果斜率为正（>45°），那么准备做多
2、当价格来到ATR带时，ATR带是我的感兴趣的点
3、等待一次对于ATR带的测试：EMA变成绿色，代表短期已经是不错的多头趋势
4、止损放置：止损放置在最近的低点
结束
请享受它
ChartRage - ELMAELMA - Exponential Logarithmic Moving Average
This is a new kind of moving average that is using exponential normalization of a logarithmic formula. The exponential function is used to average the weight on the moving average while the logarithmic function is used to calculate the overall price effect.
Features and Settings:
◻️ Following rate of change instead of absolute levels
◻️ Choose input source of the data
◻️ Real time signals through price interaction
◻️ Change ELMA length
◻️ Change the exponential decay rate
◻️ Customize base color and signal color
Equation of the ELMA:
This formula calculates a weighted average of the logarithm of prices, where more recent prices have a higher weight. The result is then exponentiated to return the ELMA value. This approach emphasizes the relative changes in price, making the ELMA sensitive to the % rate of change rather than absolute price levels. The decay rate can be adjusted in the settings.
Comparison EMA vs ELMA:
In this image we see the differences to the Exponential Moving Average.
Price Interaction and earlier Signals:
In this image we have added the bars, so we can see that the ELMA provides different signals of resistance and support zones and highlights them, by changing to the color yellow, when prices interact with the ELMA.
Strategy by trading Support and Resistance Zones:
The ELMA helps to evaluate trends and find entry points in bullish market conditions, and exit points in bearish conditions. When prices drop below the ELMA in a bull market, it is considered a buying signal. Conversely, in a bear market, it serves as an exit signal when prices trade above the ELMA.
Volatile Markets:
The ELMA works on all timeframes and markets. In this example we used the default value for Bitcoin. The ELMA clearly shows support and resistance zones. Depending on the asset, the length and the decay rate should be adjusted to provide the best results.
Real Time Signals:
Signals occur not after a candle closes but when price interacts with the ELMA level, providing real time signals by shifting color. (default = yellow)
Disclaimer* All analyses, charts, scripts, strategies, ideas, or indicators developed by us are provided for informational and educational purposes only. We do not guarantee any future results based on the use of these tools or past data. Users should trade at their own risk.
This work is licensed under Attribution-NonCommercial-ShareAlike 4.0 International
creativecommons.org
RWEDT Weighted Moving Average Overview:
The RWEDT MA, which is short for rolling, weighted, exponential, double exponential, and triple exponential, is a group of moving averages that were subjected to a log transformation to deal with the skewness of price, and the weight of each of these moving averages was also used for calculating the standard deviations from the mean.
Clearing a misunderstanding on Standard Deviation Bands and Moving Averages
Bands, such as standard deviation bands, are frequently misinterpreted as indicators of support and resistance levels or as "mean-reverting" indicators." However, this is not their intended purpose. Bands are statistical tools that provide ranges within which price (in this case) movements are expected to occur based on historical data. Deviations beyond these bands suggest a decrease in confidence in the model rather than a reversal back to a moving average or a "support/resistance level."
Example : Assuming you correctly applied a log transformation to your standard deviation bands to remove the right skew, and assuming your data closely resembles a normal distribution or some other type of symmetrical distribution, then the probability of a value being in the 2 standard deviation range is around 95%. This does not mean it will reject or go up, or mean revert. The price won't bounce from -2 STDEV 95% of the time; that is incorrect. It just tells you that around 95% of the values will be within the 2 SD range.
Moving averages, including the ones in this indicator, are often misinterpreted as signals of trend reversals or levels of "bouncing." What moving averages actually tell you is what the expected value is. It does not show where you expect the price to be in the future; it tells you that based on the lookback, the expected value is in the center, and the confidence you have in the estimate is the confidence interval or the standard deviation range.
Example: Let's say you enter a trade with a positive expected value (expecting the price to drift up), and we have the limits set at 95%. What it tells you is that as long as the price stays within the limits, you can be 95% certain the model isn't completely random. As the price moves further away from the average, or expected value, it tells you that the model is less likely to be correct.
RWEDT MA
This indicator comes with 5 moving averages, each log transformed to reduce the skewness and asymmetry of price as much as possible
Rolling
Weighted
Exponential
Double Exponential
Triple Exponential
The band standard deviation can be adjusted, and the standard deviations have the weight of all of the moving averages that are present in the indicator. The weight is not customizable.
Why this indicator is useful:
This indicator can tell you what the expected value is. Above the moving average signifies a positive expected value, and below the moving average signifies a negative expected value. As previously stated above, the price moving further from the expected value lets you know that you should have less confidence that the model is "correct," and you could see this as taking profits as the price deviates further from the expected value.
The importance of log-transforming prices for standard deviations and moving averages.
Symmetry: Logarithmic transformations can help achieve symmetry in the distribution of price data. Stock prices, for example, exhibit some type of right-skewed distribution, where large positive price movements are more common than large negative movements. Price also can't go below 0 but can go towards positive infinity, so having a right-skew makes sense; all the outliers will be towards infinity, while all the average occurrences are "near" 0.
Stabilizing Variance: Price data typically exhibit heteroscedasticity, meaning that the variance of price movements changes over time. Log transformations can stabilize the variance and make it more consistent across different price levels. This is important for ensuring that the variability in price moves is not disproportionately influenced by extreme values.
Statistical Assumptions: Many retail indicators like Bollinger Bands use the standard deviation and moving average models of a normal distribution to attempt to model price, whose distribution more closely resembles some type of right-skew distribution. Even with the log-transformation, it still won't always resemble a perfect symmetrical distribution, and you still should not use it for mean reversion. You can still use it to understand the expected value and whether or not you should have confidence in your model.
The OG Outback [TTF]The Outback indicator
After a major overhaul of our Outback strategy, we decided that we would make our original version available for anyone to use.
The fundamental element of this indicator is based on price action relative to a slow moving average. That said, given that price will always tend towards a moving average, we have also implemented a method for helping filter out false signals leveraging a "consolidation cloud" and fast moving average. This, coupled with references to a customized version of the Relative Strength Index (RSI), has enabled us to provide significantly higher quality signals relating to price crossing a moving average.
Note: For this version, we have only prepared a single set of conditions and alerts (as noted by the 🦘 symbols). However it's worth noting there are several variations that can be done with some fundamental technical analysis and referencing additional indicators that can take this foundation and build upon it for a substantial increase in risk/reward and profit targets.
Leading T3Hello Fellas,
Here, I applied a special technique of John F. Ehlers to make lagging indicators leading. The T3 itself is usually not realling the classic lagging indicator, so it is not really needed, but I still publish this indicator to demonstrate this technique of Ehlers applied on a simple indicator.
The indicator does not repaint.
In the following picture you can see a comparison of normal T3 (purple) compared to a 2-bar "leading" T3 (gradient):
The range of the gradient is:
Bottom Value: the lowest slope of the last 100 bars -> green
Top Value: the highest slope of the last 100 bars -> purple
Ehlers Special Technique
John Ehlers did develop methods to make lagging indicators leading or predictive. One of these methods is the Predictive Moving Average, which he introduced in his book “Rocket Science for Traders”. The concept is to take a difference of a lagging line from the original function to produce a leading function.
The idea is to extend this concept to moving averages. If you take a 7-bar Weighted Moving Average (WMA) of prices, that average lags the prices by 2 bars. If you take a 7-bar WMA of the first average, this second average is delayed another 2 bars. If you take the difference between the two averages and add that difference to the first average, the result should be a smoothed line of the original price function with no lag.
T3
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Thanks for checking this out and give a boost, if you enjoyed the content.
Best regards,
simwai
---
Credits to @loxx
Normalised Gaussian MACD Heikin Ashi [AlgoAlpha]🌟🚀Introducing the Normalised Gaussian MACD Heikin Ashi by AlgoAlpha !
Elevate your trading game with this multipurpose indicator, crafted to pinpoint trend continuation opportunities while highlighting volatility and oversold/overbought conditions. Whether you're embarking on your trading journey or you're a seasoned market navigator, this tool is equipped with intuitive visual cues to amplify your decision-making prowess and enrich your market analysis toolkit. Let's dive into the key features, utilization strategies, and the innovative logic underpinning this indispensable trading asset.
Key Features:
🔧 Enhanced Customization : Tailor your experience with adjustable parameters including Fast Length, Slow Length, Source, Macd Smoothing Length, Signal Smoothing, and more.
🖌️ Visual Enhancements : Opt for Heikin Ashi Candles display and choose to show or hide MACD and Signal lines for a clutter-free chart.
🌈 Color Customization : Personalize your chart with selectable primary and secondary up and down colors to suit your visual preferences.
🔔 Advanced Alert System : Stay ahead with comprehensive alert conditions for market movements, including trend reversals, bullish and bearish swings.
How to Use:
Configure the Inputs : Start by customizing the indicator’s settings to match your trading style. Adjust the length parameters, source selection, and smoothing lengths to fine-tune the indicator’s sensitivity.
Interpret the Candles and Colors : Keep an eye on the Heikin Ashi Candles (if enabled) and the color shifts within the MACD Line Candles and Histogram. These visual cues are pivotal for identifying market trends.
Analyze with Flexibility : Make use of the option to display or hide the MACD and Signal lines based on your analysis requirements. This can help in focusing on the essential information without overcrowding your chart.
Utilize Alerts for Timely Decisions : Leverage the extensive alert system to get notified about potential market movements. These alerts can help you capture the right moment to enter or exit trades.
Basic Logic:
The Normalised Gaussian MACD Heikin Ashi by AlgoAlpha integrates Gaussian filters to elevate the traditional MACD indicator's efficiency, providing a more detailed analysis of market trends and momentum. This sophisticated approach reduces noise and enhances signal speed, which is crucial for identifying momentum trading opportunities.
Gaussian Filter Implementation : The core innovation lies in applying a Gaussian filter to the input price series. This mathematical technique smooths the price data, significantly reducing market noise and making trend signals clearer and more reliable. The Gaussian filter calculates a smoothed value for each data point by weighting nearby data points, with the weights decreasing as the distance from the current data point increases.
Refined MACD Calculation : The Gaussian MACD is derived from the difference between two Gaussian smoothed moving averages (fast and slow), which are then normalized to account for market volatility. This normalization process involves dividing the difference by a measure of market range (such as the high minus the low), and multiplying by a factor (usually 100) to scale the indicator appropriately.
🔑 This script is a versatile tool designed to aid in the identification of momentum and reversals, helping traders to make informed decisions based on technical analysis. Its customization options allow for a tailored analysis experience, fitting the unique needs and strategies of each trader.
(CF|360) Caruso Financial DashboardThe Caruso Financial 360 Dashboard (CF|360) revolutionizes your TradingView charts by seamlessly integrating comprehensive Fundamental, Statistical, Technical, Performance, and Event information into an intuitively organized dashboard. This empowers users to make informed investment decisions effortlessly, eliminating the need to switch between pages or applications.
The dashboard is strategically divided into five distinct sections, each color-coded for user-friendly navigation. A quick glance at the dark blue "Fundamentals" table reveals two years of quarterly EPS and Sales data, YoY % change, and Surprise %, complete with report dates. Users can explore eight years of annual data and choose between Non-GAAP EPS, Diluted EPS, and Basic EPS for versatile analysis. Opting for Non-GAAP EPS also unveils next quarter estimates. The Fundamentals section further encompasses P/E and P/S data, alongside TTM dividend and dividend yield information.
In the yellow "Extended Fundamentals" section, users gain insights into Gross, EBITDA, and Net margins for easy profitability comparisons within the same industry group. Return on Equity data and Free Cashflow per share provide perspectives on profitability, efficiency, and financial flexibility.
The light blue "Statistics" section furnishes essential statistical measures for a rapid grasp of a company's trading characteristics. Metrics such as Market Cap, Average Volume per day (Shares and $ value), VWAP, Up/Down volume ratio, ATR%, Alpha, Beta, Shares Outstanding & Float, 52-week High/Low, and % distance from the 52-week high are presented. Additionally, market breadth is depicted through Nasdaq and NYSE 52-week high/low data.
The purple "Technical & Performance" section seamlessly integrates both Technical Analysis data and Performance statistics, enabling users to assess the stock's technical context and performance against the market over different periods. Technical indicators, including three customizable moving average types, RSI, ADX, Bollinger Band, Keltner Band, and daily and weekly closing ranges, are featured.
The grey top "Events" section offers a quick overview of the next earnings release date, countdown, and associated color changes as the date approaches. Company name, sector, and industry details are also presented.
To enhance information visibility, record EPS and Sales data are highlighted, emphasizing new records, along with highlights for new 52-week highs and lows.
The CF|360 offers customization options , including three display styles for Desktops, Desktop Slim, and Mobile devices.
Users can also tailor the lengths of technical indicators to suit their preferences. International market enthusiasts will appreciate that the CF|360 provides financial and market data for various regions, including the US, EU, Canada, and beyond.
88 Metrics Included:
Fundamentals Section (Dark Blue Group)
EPS (Adjusted Non-GAAP, Diluted, Basic)
- Quarterly, YoY % Chg, Surprise, Report Date, Next Quarter Estimate (Adjusted EPS only)
- Annual, YoY % Chg
Sales
- Quarterly, YoY % Chg, Surprise, Report Date, Next Quarter Estimate
- Annual, YoY % Chg
P/E ratio
P/S ratio
Dividend TTM
Dividend TTM Yield
Fundamentals Extended (Yellow Group)
Gross Margin
EBITDA Margin
Net Margin
Return on Equity (ROE)
Free Cashflow per Share (FCFPS)
Debt to Equity (Debt)
Effective Interest Rate (Int Rate)
Statistics (Light Blue Group)
Market Cap
Average Daily Volume (Shares)
Average Daily Volume (Dollar Value)
VWAP (Daily)
Average True Range Percent
Shares Outstanding
Shares in Float
Percentage of Share in Float
52-Week High
52-Week Low
% off of 52-Week High
Up / Down Volume Ratio
Beta
Alpha
Nasdaq Net 52-Week High/Lows
Nasdaq 52-Week Highs
Nasdaq 52-Week Lows
NYSE Net 52-Week High/Lows
NYSE 52-Week Highs
NYSE 52-Week Lows
Technical & Performance (Purple Group)
Moving Average Value (3 different averages)
Distance from Moving Average (3 different averages)
Relative Strength Index (RSI)
Average Directional Index (ADX)
Bollinger Band Value (Upper/Lower)
%b
Keltner Band Value (Upper/Lower)
%k
Percentage Changes Since Today’s Open
Daily Closing Range (DCR)
Weekly Closing Range (WCR)
Current Week % Change
1 Month % Change
3 Month % Change
6 Month % Change
1 Year % Change
3 Year % Change
YTD % Change
S&P 500 YTD % Change
Name, Group, & Events (Grey Section)
Company Name
Sector
Industry
Next Earnings Date
Days Until Next Earnings Date
Event Highlights
Record EPS (Quarterly/Annual)
Record Sales (Quarterly/Annual)
52-Week High
52-Week Low
Layout Types
Desktop
Get the full experience with the Desktop view.
Desktop Slim
Save screen real estate with a slim version of the dashboard.
Mobile
Take the most vital metrics with you on your mobile device. For the best experience, view in landscape mode.
series_collectionLibrary "series_collection"
A personal collection of commonly used series types like moving averages that are supported directly by
the pinescript library ('ALMA', 'DEMA', 'EMA', 'HMA', 'RMA', 'SMA', 'SWMA', 'VWMA', 'WMA'), highest and lowest source,
median and pivots. One single function (with overloads) that can be configured easily by the user input and can be
used as a core piece of functionality for many user cases. This library was created to abstract away and re-use this
commonly used functionality in my "Two MA Signal Indicator" script and the "Template Trailing Strategy" script. Both
of them use the "two_ma_logic" for defining entry and exit signals. While this piece of work does not contain any
novel mathematical expressions and just adds a convinient (and configurable) way to do things, I hope that might add
value to other scripts as well and future projects.
cust_series(length, seriesType, source)
cust_series - Calculate the custom series of the given source for the given length and type
Parameters:
length (simple int) : - The length of the custom series
seriesType (simple string) : - The type of the custom series
source (float) : - The source of the values
Returns: - The resulting value of the calculations of the custom series
cust_series(length, seriesType, source)
cust_series - Calculate the custom series of the given source for the given length and type
Parameters:
length (simple float) : - The length of the custom series (ceiled)
seriesType (simple string) : - The type of the custom series
source (float) : - The source of the values
Returns: - The resulting value of the calculations of the custom series
EMA + Lower Timeframe EMA (correct display in Replay Mode)This indicator shows
one EMA for the current timeframe
one EMA for a lower timeframe
Unlike the built-in Tradingview EMA indicator, this indicator shows the correct values for the lower timeframe EMA during Replay Mode.
Liquidity Weighted Moving Averages [AlgoAlpha]Description:
The Liquidity Weighted Moving Averages by AlgoAlpha is a unique approach to identifying underlying trends in the market by looking at candle bars with the highest level of liquidity. This script offers a modified version of the classical MA crossover indicator that aims to be less noisy by using liquidity to determine the true fair value of price and where it should place more emphasis on when calculating the average.
Rationale:
It is common knowledge that liquidity makes it harder for market participants to move the price of assets, using this logic, we can determine the coincident liquidity of each bar by looking at the volume divided by the distance between the opening and closing price of that bar. If there is a higher volume but the opening and closing prices are near each other, this means that there was a high level of liquidity in that bar. We then use standard deviations to filter out high spikes of liquidity and record the closing prices on those bars. An average is then applied to these recorded prices only instead of taking the average of every single bar to avoid including outliers in the data processing.
Key features:
Customizable:
Fast Length - the period of the fast-moving average
Slow Length - the period of the slow-moving average
Outlier Threshold Length - the period of the outlier processing algorithm to detect spikes in liquidity
Significant Noise reduction from outliers:
Blockunity Excess Index (BEI)Identify excess zones resulting in market reversals by visualizing price deviations from an average.
The Excess Index (BEI) is designed to identify excess zones resulting in reversals, based on price deviations from a moving average. This moving average is fully customizable (type, period to be taken into account, etc.). This indicator also multiplies the moving average with a configurable coefficient, to give dynamic support and resistance levels. Finally, the BEI also provides reversal signals to alert you to any risk of trend change, on any asset.
The Idea
The goal is to provide the community with a visual and customizable tool for analyzing large price deviations from an average.
How to Use
Very simple to use, this indicator plots colored zones according to the price's deviation from the moving average. Moving average extensions also provide dynamic support and resistance. Finally, signals alert you to potential reversal points.
Elements
The Moving Average
The Moving Average, which defaults to a gray line over 200 periods, serves as a stable reference point. It is accompanied by an Index, whose color varies from yellow to orange to red, offering an overview of market conditions.
Extensions
These dynamic lines can be used to determine effective supports and resistances.
Signals
Green and red triangles serve as clear indicators for buy and sell signals.
Settings
Mainly, the type of moving average is configurable. The default is an SMA.
A Simple Moving Average (SMA) calculates the average of a selected range of prices by the number of periods in that range.
But you can also, for example, switch the mode to EMA.
The Exponential Moving Average (EMA) is a moving average that places a greater weight and significance on the most recent data points:
You also have WMA.
A Weighted Moving Average (WMA) gives more weight on recent data and less on past data:
And finally, the possibility of having a PCMA.
PCMA takes into account the highest and lowest points in the lookback period and divides this by two to obtain an average:
You can change other parameters such as lookback periods, as well as the coefficient used to define extension lines.
You can refer to the tooltips directly in the indicator parameters.
For those who prefer a minimalist display, you can activate a "Bar Color" in the settings (You must also uncheck "Borders" and "Wick" in your Chart Settings), and deactivate all other elements as you wish:
Finally, you can customize all the different colors, as well as the parameters of the table that indicates the Index value and the asset trend.
How it Works
The Index is calculated using the following method:
abs_distance = math.abs(close - base_ma)
bei = (abs_distance - ta.lowest(abs_distance, lookback_norm)) / (ta.highest(abs_distance, lookback_norm) - ta.lowest(abs_distance, lookback_norm)) * 100
Signals are triggered according to the following conditions:
A Long (buy) signal is triggered when the Index falls below 100, when the closing price is lower than 5 periods ago, and when the price is under the moving average.
A Short (sell) signal is triggered when the Index falls below 100, when the closing price is greater than 5 periods ago, and when the price is above the moving average.
BTC Halving [YinYangAlgorithms]This Indicator not only estimates what it thinks may be the PRICE for the Start, High and Low of the Halving, but likewise estimates WHEN the Start, High and Low of Halving may be. It then creates Trend Lines based on these predictions so that you may get an evaluation towards if the Price is currently Overbought or Oversold. These Trend Lines may be very useful for seeing the Slope in which the Price may move if it is to reach the estimated Price by the estimated Date. By evaluating the Prices location based on these Trend Lines we may determine if the Price is currently Overbought or Oversold.
These Trend Lines likewise may help identify locations of Support and Resistance. If the Price is much higher than its current Trend Line it is Overbought. There is a chance it will Consolidate back to the Trend Line or it may even correct with a dump all the way back to it; the opposite is true if it is much lower than its current Trend Line.
Trend Lines and Estimates are not all that is featured within this Indicator however. There are also Price Zones which may help identify if the price is currently:
Very Overbought (Red)
Slightly Overbought (Orange)
Neutral (Yellow)
Slightly Oversold (Teal)
Very Oversold (Green)
These zones may help give you an idea of how the price is currently fairing and its potential for movement. Likewise, it may help define where Support and Resistance may be found.
The trend line estimates are done with an algorithm created to evaluate the difference between price and % change that has occurred between the Start, High and Low of all the halvings over how many days between each data type. This may allow us to make an educated estimate towards what Price and Date the Start, High and Low will occur at.
Our Zones are created by evaluating the current Market Cap and circulating supply vs Max Supply of BTC. This may help give us an evaluation of what Price may be considered to be Overbought and Oversold; and likewise may help with estimations of where there may be Support and Resistance based on these Zones.
Tutorial:
In the example above we’re displaying the Halving Start Trend Line, our Information Tables and our Estimated Halving Vertical Marker. This Trend Line may help to display not only the trajectory and slope the Price needs to take to reach the Estimated Halving Price by the Estimated Halving Date; but it may also help to show if the price is Overvalued or Undervalued based on its position above or below this Trend Line.
Based on the Trajectory of the Estimated High Upward Trend Line (Green Line) in the photo above and from the ‘High Date’ estimated in the Information tables; we may attempt to estimate the location the ATH of this Bull Market will create and the price slope it may follow in doing so. This Trajectory may be very useful for understanding the price action that may occur for it to reach the High estimated Price by the High estimated Date.
We currently allow for two different types of zones within our Settings, one called ‘Fast’ displayed in the example above; and the other called ‘Slow’ displayed in the example below.
Our Fast Zone aims to move the Zone Levels Faster in an attempt to move with volatility and parabolic movement. This may help to keep the Very Overbought (Red) and Very OverSold (Green) Levels more accurate by attempting to keep the price within them. By doing so, we may aim to keep all of the Slightly Overbought, Slightly Oversold and Neutral Levels more accurate as well.
The Levels within these zones are defined by the Bright (less transparent) Lines. Whereas the Darker (more transparent) lines represent the Basis Lines between two different levels. These Basis lines may likewise act as a Support and Resistance Location too, but generally hold less weight than the actual Levels themselves.
What you may see is that during the Bull Market, the price is within the very Overbought Zones and even touches again the Very Overbought Level a few times. Likewise, during the Bear Market, the price is within the very Oversold Zones and even slightly drops below the Very Oversold Level. This may be expected and likewise may help to give estimates at potential for growth and decay within the Price based on which condition the Market is within.
Slow Zones move a little slower than Fast Zones, however they may still be accurate. Likewise, it is up to you to decide which Zone works better for your specific Trading Style; however, by default, the Zone type is set to Fast.
If you refer to both the Fast and Slow examples above, you may notice in the Fast the Price is only slightly above the ‘Slightly Oversold’ (Teal) line. Also, In the Fast, the Price where the ‘Very Overbought’ Level is 100k. This is one of the many reasons we’ve opted for ‘Fast’ as the default, and it is because it allows more room for movement; and in our opinion, potentially accuracy as well.
If you refer to the Slow example, you’ll see that the price is currently facing the Neutral Level as a Resistance location. However, if you refer to the price residing at the Slows ‘Very Overbought’ Level, it is only 81.5k, compared to the 100k of Fast.
The BTC Halving is a major event that takes place roughly every 4 years. It historically has a major impact on the market, and some may even say it signifies the Start, or close to start of the Bull Market. Therefore, since historically there may be cycles that BTC and potentially crypto itself follows, we’ve developed this Indicator in hopes that it may solve one of the biggest questions traders face. What Date will the Start, High and Low of the Halving occur and also at what Price.
Hopefully this Tutorial has given you some guidance as to how this Indicator may be used to help identify some of these key levels; including the slope at which the price may have to move if it is to reach its projection Price by its projected Date.
Settings:
1. Show Prediction Trend Lines:
- Options:
All
Start + High
Start + Low
High + Low
Start
High
Low
None
- Description:
Prediction Trend Lines may be an important way to see the Slope the Price needs to take to reach the Predicted Price by the Predicted Date. This may be useful for identifying if the Price is currently Overbought or Oversold.
2. Zone Type:
- Options:
Fast
Slow
- Description:
Zone types change the way the Zones expand.
3. Show Zones:
- Options:
All
Zones
Basis
None
- Description:
Zones are a way of seeing Overbought and Oversold Price locations based on Market Cap and Circulating Supply vs Max Supply.
4. Vertical Markers:
- Options:
All
Line
Label
None
- Description:
Vertical Markers display where the Halving has occurred with a Vertical Line and Label.
5. Show Tables:
Tables may be useful for seeing the Price and Date for when the Start, High and Low of the Halving may occur.
6. Fill Zones:
Filling in Zones may help to identify which Zone the Price is currently in.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
WPO Modified [BackQuant]The Wave Period Oscillator (WPO), developed by Akram El Sherbini, is a sophisticated technical analysis tool that offers traders a dynamic way to interpret market cycles. Its design is inspired by the natural ebb and flow of markets, which often follow cyclical patterns driven by underlying economic, political, and psychological factors. The oscillator's unique contribution to market analysis lies in its ability to smooth out the "noise" inherent in daily price movements, thus providing a clearer view of the market's rhythmic fluctuations over time.
-----> Time Cycle Oscillators' in the IFTA Journal 2018 (page 66 - 77), as found below:
ifta.org
El Sherbini's WPO is grounded in the concept of wave period analysis, which suggests that financial markets move in waves or cycles. The oscillator translates these movements into a visual tool that oscillates above and below a central zero line. Peaks and troughs on the oscillator correspond to the crests and troughs of market price waves, providing a visual representation of the market's heartbeat.
The WPO is not merely a tool for identifying trends but also for detecting shifts in market momentum. It does this through a mathematical model that measures divergence—when the direction of the oscillator deviates from the direction of price movement. Such divergences can be precursors to potential reversals or continuations in the market, offering traders advance notice of significant changes in price direction.
Further refining its utility, the WPO incorporates methods for calculating divergence that are sensitive to the unique conditions of different markets and securities. This includes adjusting for volatility and market velocity, allowing the oscillator to provide relevant signals regardless of the market environment.
In practical terms, traders use the WPO to time their entries and exits with greater precision. When the oscillator shows a high peak or a deep trough, it can signal that a market is potentially overbought or oversold, respectively. The WPO's smoothing property ensures that these signals are not just reactionary to short-term price spikes or drops, but indicative of more substantial, sustained movements.
By providing a more measured and smoothed analysis of market cycles, the WPO helps to filter out insignificant price movements and focus on the ones that matter—those that indicate a significant wave of buying or selling pressure. This can be particularly valuable in the cryptocurrency markets, where volatility is high, and traditional indicators may struggle to provide clear signals.
For traders and analysts alike, the Wave Period Oscillator represents a convergence of technical precision and market psychology. By focusing on the periodic nature of market movements, it aligns traders with the rhythm of the markets, potentially leading to more harmonious trading decisions that are in step with the market's natural waves.
Please see the backtest here:
For more simple terms:
You can use this indicator as a the oscillator
Above 0 for long
Below 0 for short
OR
WPO MA
Above 0 for long
Below 0 for short
Machine Learning: STDEV Oscillator [YinYangAlgorithms]This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from its standard movement. This Indicator may help display both when the price is Overbought or Underbought, and likewise, where the price may face Support and Resistance. The reason for this is that rather than simply plotting a Machine Learning Standard Deviation (STDEV), we instead create a High and a Low variant of STDEV, and then use its Highest and Lowest values calculated within another Deviation to create Deviation Zones. These zones may help to display these Support and Resistance locations; and likewise may help to show if the price is Overbought or Oversold based on its placement within these zones. This Oscillator may also help display Momentum when the High and/or Low STDEV crosses the midline (0). Lastly, this Oscillator may also be useful for seeing the spacing between the High and Low of the STDEV; large spacing may represent volatility within the STDEV which may be helpful for seeing when there is Momentum in the form of volatility.
Tutorial:
Above is an example of how this Indicator looks on BTC/USDT 1 Day. As you may see, when the price has parabolic movement, so does the STDEV. This is due to this price movement deviating from the mean of the data. Therefore when these parabolic movements occur, we create the Deviation Zones accordingly, in hopes that it may help to project future Support and Resistance locations as well as helping to display when the price is Overbought and Oversold.
If we zoom in a little bit, you may notice that the Support Zone (Blue) is smaller than the Resistance Zone (Orange). This is simply because during the last Bull Market there was more parabolic price deviation than there was during the Bear Market. You may see this if you refer to their values; the Resistance Zone goes to ~18k whereas the Support Zone is ~10.5k. This is completely normal and the way it is supposed to work. Due to the nature of how STDEV works, this Oscillator doesn’t use a 1:1 ratio and instead can develop and expand as exponential price action occurs.
The Neutral (0) line may also act as a Support and Resistance location. In the example above we can see how when the STDEV is below it, it acts as Resistance; and when it’s above it, it acts as Support.
This Neutral line may also provide us with insight as towards the momentum within the market and when it has shifted. When the STDEV is below the Neutral line, the market may be considered Bearish. When the STDEV is above the Neutral line, the market may be considered Bullish.
The Red Line represents the STDEV’s High and the Green Line represents the STDEV’s Low. When the STDEV’s High and Low get tight and close together, this may represent there is currently Low Volatility in the market. Low Volatility may cause consolidation to occur, however it also leaves room for expansion.
However, when the STDEV’s High and Low are quite spaced apart, this may represent High levels of Volatility in the market. This may mean the market is more prone to parabolic movements and expansion.
We will conclude our Tutorial here. Hopefully this has given you some insight into how applying Machine Learning to a High and Low STDEV then creating Deviation Zones based on it may help project when the Momentum of the Market is Bullish or Bearish; likewise when the price is Overbought or Oversold; and lastly where the price may face Support and Resistance in the form of STDEV.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
ATR Based Stoploss - TakeProfit [CharmyDexter]
This script combines the power of Average True Range (ATR) and a Moving Average (MA) to dynamically set stop-loss and take-profit levels. It introduces a volatility surge condition and includes a risk management table for comprehensive trade insights.
1) **Originality:**
- This script is original in its approach to combining Average True Range (ATR) with a Moving Average (MA) to create a dynamic stop-loss and take-profit strategy. The addition of a volatility surge condition and the inclusion of a risk management table further contribute to its uniqueness.
2) **Functionality:**
- The script aims to provide traders with a dynamic stop-loss and take-profit strategy based on ATR, incorporating a volatility surge condition and a moving average. The risk management table displays crucial information, including the fund size, potential profit/loss, ATR values, and risk.
3) **Operation:**
- The script uses ATR to calculate volatility, identifying surges in volatility. It adjusts the stop-loss and take-profit levels based on the average of ATR during these surge periods. The moving average acts as a trend indicator, and the script dynamically adjusts stop-loss and take-profit levels accordingly.
4) **Usage:**
- Traders can use this script by applying it to their preferred financial instrument's chart. The script automatically plots the moving average and dynamically adjusts stop-loss and take-profit levels based on ATR and volatility surges. Users can observe the levels on the chart for potential trade management.
5) **Concepts:**
- The script employs concepts of ATR for volatility, moving average for trend identification, and a dynamic adjustment mechanism during volatility surges. Risk management is incorporated by calculating potential profit/loss percentages based on user-defined risk.
6) **Mashup Explanation:**
- The script combines ATR, moving average, and volatility conditions to create a comprehensive strategy. ATR determines the market's volatility, the moving average serves as a trend indicator, and volatility surges trigger dynamic adjustments to stop-loss and take-profit levels. The risk management table enhances the script's utility.
7) **Line Descriptions:**
- Blue Line (Moving Average): Indicates the trend direction.
- Lime Line (Long Take Profit): Represents the level for taking profit in a long position.
- Maroon Line (Short Take Profit): Represents the level for taking profit in a short position.
- Fuchsia Line (Short Stop Loss): Represents the level for setting a stop loss in a short position.
- Orange Line (Long Stop Loss): Represents the level for setting a stop loss in a long position.
8) **Line Usage:**
- Use the blue line for trend identification.
- When taking long positions, the close should be above the blue line.
- For long positions, the lime line is a potential take-profit level, and the orange line is a potential stop-loss level.
- For short positions, the maroon line is a potential take-profit level, and the fuchsia line is a potential stop-loss level.
- The risk management table provides insights into fund size, potential profit/loss, ATR values, and risk.
Note: The profit/loss calculations in this script may not be entirely accurate due to factors like market execution. Market execution may not always occur at the exact levels specified by the script due to slippage or delays in order processing. This can impact the realized profit or loss compared to the calculated levels.
It is crucial to note that this ATR Based Stop-loss - Take-Profit indicator is merely one tool among many that traders can employ to establish trading targets. Additional technical indicators are essential for taking trades and making informed decisions.
Commented-out sections for alerts and shape plotting are provided, allowing for visual and auditory notifications if desired.
It's crucial for traders to be aware of these factors and use the script as a tool within a broader trading strategy. Additionally, regular monitoring and adjustments based on real-time market conditions are recommended to enhance the accuracy of profit/loss assessments.
SMA Cross with a Price FilterA moving average strategy generates an entry (buy) signal when the price goes above the moving average, and an exit (sell) signal when the price goes below the moving average. But it gives lots of whipsaws and noise depends on the moving average we use. A fast moving average gives more whipsaws and a slow moving average gives less whipsaws. To reduce the noise/whipsaws, we can add a filter on a fast/slow moving average. It will improve entry/exit performance significantly specially for those who don't want to watch the market actively.
I created this indicator with a price filter. This means the price of an underlying asset must be at least a specific percentage above its moving average to generate a buy signal and a specific percentage below its moving average to generate a sell signal. This price filter can also be a confirmation after the price crosses above/below its SMA. I couldn't find any indicator yet based on this idea. So I wrote this indicator and publishing it so it helps those who are interested.
I use 200 SMA and 3% price filter as default and using SPY as an example. So,
ENTRY signal when the closing price of SPY is 3% above its 200 SMA.
EXIT signal when the closing price of SPY is 3% below its 200 SMA.
Enjoy and let me know if it works.
** This chart only generates entry (buy) and exit (sell) signals. Please, do your own diligence to make any investment or trading decisions.
Trend-based Price Action StrategyThis is a strategy script that combines trend-based price action analysis with the Relative Strength Index (RSI) and Exponential Moving Averages (EMA) as trend filters. Here's a summary of the key components and logic:
Price Action Candlestick Patterns:
Bullish patterns: Engulfing candle and Morning Star.
Bearish patterns: Engulfing candle and Evening Star.
RSI Integration:
RSI is used to identify overbought and oversold conditions.
EMA Trend Filter:
Three EMAs with different periods: Fast , Medium and Slow.
Long trend condition occur when the fast EMA is above the medium and the medium is above the slow EMA.
Short trend condition occur when the slow EMA is above the medium and the medium is above the fast EMA.
Long entry conditions: RSI is oversold, RSI is decreasing, bullish candlestick pattern, and EMA trend filter conditions are met.
Short entry conditions: RSI is overbought, RSI is decreasing, bearish candlestick pattern, and EMA trend filter conditions are met.
Exit conditions:
Take profit or stop loss is reached.
Plotting:
Signals are plotted on the chart when entry conditions are met.
EMAs are plotted when the EMA trend filter is enabled.
This script aims to capture potential trend reversal points based on a combination of candlestick patterns, RSI, and EMA trend analysis.
Traders can use this script as a starting point for further customization or as a reference for developing their own trading strategies. It's important to note that past performance is not indicative of future results, and thorough testing and validation are recommended before deploying any trading strategy.
