Nadaraya-Watson Envelope (Non-Repainting) Logarithmic ScaleIn the fast-paced world of trading, having a reliable and accurate indicator can make all the difference. Enter the Nadaraya-Watson Envelope Indicator, a cutting-edge tool designed to provide traders with valuable insights into market trends and potential price movements. In this article, we'll explore the advantages of this non-repainting indicator and how it can empower traders to make informed decisions with confidence.
Accurate Price Analysis:
The Nadaraya-Watson Envelope Indicator operates in a logarithmic scale, allowing for more accurate price analysis. By considering the logarithmic nature of price movements, this indicator captures the subtle nuances of market dynamics, providing a comprehensive view of price action. Traders can leverage this advantage to identify key support and resistance levels, spot potential breakouts, and anticipate trend reversals.
Non-Repainting Reliability:
One of the most significant advantages of the Nadaraya-Watson Envelope Indicator is its non-repainting nature. Repainting indicators can mislead traders by changing historical signals, making it difficult to evaluate past performance accurately. With the non-repainting characteristic of this indicator, traders can have confidence in the reliability and consistency of the signals generated, ensuring more accurate backtesting and decision-making.
Customizable Parameters:
Every trader has unique preferences and trading styles. The Nadaraya-Watson Envelope Indicator offers a range of customizable parameters, allowing traders to fine-tune the indicator to their specific needs. From adjusting the lookback window and relative weighting to defining the start of regression, traders have the flexibility to adapt the indicator to different timeframes and trading strategies, enhancing its effectiveness and versatility.
Envelope Bounds and Estimation:
The Nadaraya-Watson Envelope Indicator calculates upper and lower bounds based on the Average True Range (ATR) and specified factors. These envelope bounds act as dynamic support and resistance levels, providing traders with valuable reference points for potential price targets and stop-loss levels. Additionally, the indicator generates an estimation plot, visually representing the projected price movement, enabling traders to anticipate market trends and make well-informed trading decisions.
Visual Clarity with Plots and Fills:
Clear visualization is crucial for effective technical analysis. The Nadaraya-Watson Envelope Indicator offers plots and fills to enhance visual clarity and ease of interpretation. The upper and lower boundaries are plotted, along with the estimation line, allowing traders to quickly assess price trends and volatility. Fills between the boundaries provide a visual representation of different price regions, aiding in identifying potential trading opportunities and risk management.
Conclusion:
The Nadaraya-Watson Envelope Indicator is a powerful tool for traders seeking accurate and reliable insights into market trends and price movements. With its logarithmic scale, non-repainting nature, customizable parameters, and visual clarity, this indicator equips traders with a competitive edge in the financial markets. By harnessing the advantages offered by the Nadaraya-Watson Envelope Indicator, traders can navigate the complexities of trading with confidence and precision. Unlock the potential of this advanced indicator and elevate your trading strategy to new heights.
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Volume Pressure Based Buy and Sell SignalsThis script uses a volume pressure indicator to generate buy and sell signals. The volume pressure indicator is calculated by taking the sum of the product of volume and price change over a specified period of time, and then dividing that sum by the total volume over the same period. This gives a measure of the amount of buying pressure or selling pressure in the market.
The script then compares the volume pressure indicator to a moving average of the volume pressure indicator. When the volume pressure indicator crosses above the moving average, a buy signal is generated. When the volume pressure indicator crosses below the moving average, a sell signal is generated.
This script is beneficial to traders because it can help them to identify potential trend reversals. When the volume pressure indicator crosses above the moving average, it indicates that there is a growing amount of buying pressure in the market. This could be a sign that the trend is about to reverse from a downtrend to an uptrend. Conversely, when the volume pressure indicator crosses below the moving average, it indicates that there is a growing amount of selling pressure in the market. This could be a sign that the trend is about to reverse from an uptrend to a downtrend.
Market Smith IndicatorsMarket Smith has a collection of tools that are useful for identifying stocks. On their charts they have a 21/50/200 day moving averages, high and low pivot points, a relative strength line, and a relative strength rating. This script contains indicators for the following:
21/50/200 Day Moving Averages
High and Low pivot points
A Relative Strength line
A Relative Strength rating
21/50/200 Day Moving Averages
The 21/50/200 Day moving averages are simple moving averages. They are visible in any chart increment but to use them properly you need to set you charts to be by day. Labels will appear on the right of the lines to show that they are representative of 21/50/200 day moving averages.
High and Low pivot points
The High and Low pivot points are green for high pivot points and red for low points. They are show in the Market Smith style with the numbers simply above the pivot points.
Relative Strength line
The Relative Strength line is a line that shows the strength of the stock compared to the S&P 500. In this case we utilize the SPX ticker to compare the stock to. This line is almost identical to the Market Smith tool and is an excellent tool to determine how a stock is doing compared to the market. When movements in the stock and shown with sideways trending of the RS line that means that the stock is following the market. When a stock is outperforming the market the RS line will follow.
Relative Strength rating
Thank you to ©Fred6724 for the RS Rating inspiration. They wrote excellent open source code for a RS Rating comparable to Market Smith. As the RS Rating in Market Smith is not open source it is difficult to know exactly how it is being calculated. After simplifying Fred's code and building upon a few ideas I had I compared the RS Rating to multiple Market Smith Ratings. The rating is close but often off by multiple points. If there is anyone who has a better idea on how to get this rating or how to improve on the code please send me a PM or fork this project. This rating is a good indicator to see how a certain stock compares to other stocks in the market. In Market Smith they are able to utilize their database to compare it to all other stocks. Since we do not have access to the same tools we are only able to compare it to the percentage of stocks above the 200, 150, 100, 50, and 20 day moving average.
Using these tools together are a small fraction what make people like Bill O'neill and Jim Roppel so successful. I plan on updating the RS Rating as I continue to work on this project so if there is anyone who has ideas then please send me a PM. Ultimately the goal of this project is to have a solution that is identical to Market Smith.
DrNon_NASDAQ10Title: NASDAQ 10 Index with TOP 10 Securities
Introduction:
TradingView offers traders and investors a powerful platform for technical analysis and trading. One of its notable features is the ability to create custom indices based on the values of multiple individual securities. In this blog post, we will explore how to build a custom index with 10 securities in TradingView using Pine Script, the platform's proprietary programming language.
Description:
Custom indices allow market participants to track the performance of a specific group of securities, providing valuable insights into the collective performance of the chosen assets. By leveraging Pine Script, traders can easily develop and deploy custom indicators and strategies to build their own indices.
The script provided focuses on creating a custom index with 10 securities. The selected securities include popular stocks such as AAPL (Apple Inc.), MSFT (Microsoft Corporation), GOOG (Alphabet Inc.), AMZN (Amazon.com Inc.), NVDA (NVIDIA Corporation), TSLA (Tesla Inc.), META (Facebook, Inc.), AVGO (Broadcom Inc.), PEP (PepsiCo, Inc.), and COST (Costco Wholesale Corporation).
Using the security() function in Pine Script, we retrieve the closing prices of each individual security to ensure accurate data for the index calculation.
The index value is then calculated by summing the closing prices of the 10 securities. This simple arithmetic operation captures the overall performance of the custom index.
To visualize the index, we use the plot() function to display the index value on the chart. Traders can observe the custom index alongside other technical indicators or price action, aiding in decision-making and market analysis.
By building a custom index with 10 securities in TradingView, traders gain a consolidated view of the performance of these chosen assets. This allows for easier tracking of sector trends, evaluation of specific strategies, and the ability to compare the performance of individual portfolios against the broader market.
Conclusion:
TradingView's Pine Script provides traders and investors with a flexible solution to build custom indices. By defining the 10 individual securities, calculating the index value, and plotting it on the chart, traders can monitor the collective performance of these chosen assets. Custom indices offer insights into sector performance, enable the evaluation of specific strategies, and provide a benchmark for comparing portfolio performance. By harnessing the power of custom indices in TradingView, traders can enhance their decision-making process and gain a competitive edge in the market.
HILOCLOP AnalysisThe "HILOCLOP Analysis" indicator is designed to analyze price data based on different conditions and provide insights into market trends and patterns. Let's break down its features and understand its potential usefulness in trading:
Sample Length: The indicator allows the user to specify the sample length, which determines the number of bars or periods considered for the analysis. This parameter can be adjusted to capture short-term or long-term trends and patterns in the market.
Raw Up/Down Analysis: The indicator calculates the number of occurrences where the current price values (high, low, open, close) are higher or lower than their previous values. It provides separate counts for each price component. By visualizing these counts on the chart, traders can identify periods of upward or downward movement in the price data.
HICLOP Analysis: The indicator offers a color scheme option called "HICLOP," which determines the color of the plotted results. If the HICLOP analysis is enabled, the plots representing raw up/down counts will have different colors based on whether the current count is higher or lower than the previous count. This color coding helps traders quickly identify changes in price trends.
Unchecking this Box will Show the general trend.
Raw HICLOP Color Scheme
Trend Color Scheme
Analysis Up vs. Down: The indicator provides an option to analyze instances where all four price components (high, low, open, close) are higher or lower than their respective previous values. This analysis helps traders identify periods of strong upward or downward movement in the market.
Analysis High vs. Low: The indicator compares the number of occurrences where the current high is higher than the previous high and the current low is higher than the previous low. It provides insights into whether the market is experiencing higher highs or higher lows, which can help traders determine the strength of an upward or downward trend.
Analysis Open vs. Close: The indicator compares the number of occurrences where the current close is higher than the previous close and the current open is higher than the previous open. This analysis helps traders assess the relationship between opening and closing prices, providing insights into the strength of buying or selling pressure in the market.
The usefulness of the "HILOCLOP Analysis" indicator in trading depends on the specific trading strategy and the trader's preferences. Here are a few potential use cases:
Trend Identification: By analyzing the raw up/down counts and the HICLOP color scheme, traders can identify trends and changes in price momentum. Increasing raw up counts and corresponding color changes to positive values may indicate an upward trend, while increasing raw down counts and negative color changes may suggest a downward trend.
Confirmation of Breakouts: Traders often look for confirmation of breakouts from key levels or chart patterns. The "Analysis Up V Dn" feature can help identify instances where all four price components simultaneously confirm a breakout, indicating a potentially significant move in the market.
Trend Reversals: The "Analysis High V Low" and "Analysis Open V Close" features can provide insights into potential trend reversals. For example, if there are more higher highs than higher lows, it may indicate a weakening trend, potentially signaling a reversal or a correction.
Disparity IndexThe Disparity Index is a technical momentum indicator that measures the relative position of the most recent closing price to a selected moving average. It calculates the percentage difference between the closing price and the moving average, providing insights into price momentum and potential reversals.
The formula for the Disparity Index is: * 100, where Close is the most recent closing price and n-period MA is the chosen moving average over n periods.
The Disparity Index can be used in various ways:
Trend Identification: The Disparity Index helps identify the relationship between the price and a chosen moving average. A positive value indicates that the price is above the moving average, suggesting bullish momentum, while a negative value suggests bearish momentum.
Overbought and Oversold Conditions: The Disparity Index can be used to identify potential overbought and oversold conditions. When the index reaches an extremely high value, it may indicate an overbought condition, implying a possible price correction. Conversely, an extremely low value can signal an oversold condition, indicating a potential price rebound.
Divergence: Traders can use the Disparity Index to identify divergence between the price and the indicator. Divergence occurs when the price and the Disparity Index move in opposite directions, potentially signaling an upcoming price reversal.
Personal Strategy: When the Disparity Index generates a green background, it suggests a potential bullish signal. This occurs when the Disparity Index crosses above the oversold threshold or exhibits a bullish reversal pattern. The green background signifies an area where buyers may have gained control, indicating a favorable environment for initiating long positions. This approach allows you to capitalize on potential upward price movements and join the uptrend.
On the other hand, when the Disparity Index generates a red background, it implies a potential bearish signal. This occurs when the Disparity Index crosses below the overbought threshold or exhibits a bearish reversal pattern. The red background highlights a zone where sellers might dominate, indicating a higher likelihood of downward price movements. By considering selling opportunities in these zones, you can position yourself to profit from potential downside moves and align with the prevailing downtrend.
The Disparity Index can be customized by using different types of moving averages such as simple moving averages (SMAs), exponential moving averages (EMAs), or weighted moving averages (WMAs). Additionally, it can be smoothed using another moving average to reduce noise and generate smoother signals, improving trend identification.
In trending markets, the Disparity Index is particularly effective as a trend indicator due to its ability to quickly capture price changes. It can provide early indications of trend strength and potential reversals, allowing traders to enter or exit positions in a timely manner. This advantage over traditional moving averages makes the Disparity Index a valuable tool for trend-following strategies.
Enjoy!
Webby's Tight IndicatorWebby's Tight Indicator is used to measure a securities volatility relative to itself over time. This is achieved by taking the average of three short term ATR's (average true range) and creating a ratio versus three longer term ATR's.
Mike Webster recently stated he is using the 3,5,8 for the short term ATR's and the 55,89,144 for the long term ATR's. All of the ATR lengths are part of the Fibonacci sequence.
The ratio of the ATR's is then calculated and plotted as a histogram with 0 representing the ATR's being equal. As a stocks short term ATR contracts the histogram will rise above 0 meaning volatility in the short term is contracting relative to long term volatility. On the other hand if the short ATR's are expanding versus the long term ATR's the histogram will fall below 0 and turn red, signifying short term volatility is greater than long term volatility.
The easy visualization of this indicator allows you to quickly see when a stock is in a tight range and could be ready for a potential breakout to the long side or breakdown to the short side.
In this example we see tight price action with a blue histogram followed by volatility to the upside coinciding with a breakout.
In this example we see volatility expanding as a stock continues to fall.
To help differentiate between trending contraction or expansion and just short term blips 5-day exponential moving average of the ratio is also plotted on the histogram and dynamically changes colors as it rises and falls.
Indicator options include:
Change histogram colors
Choose ema line width
Webby's RS LineThe Relative Strength (RS) line is something many investors are familiar with. It is used to measure a stocks performance versus the S&P 500 and is typically calculated by dividing the closing price of the stock by the closing price of the S&P. This means if a stock moves up and the S&P moves down or the stock moves up more than the S&P the RS line will increase, if the stock moves down while the S&P moves up the line will decrease.
While the standard RS line is a powerful tool, Mike Webster recently discussed how he has made changes to the standard RS line and also uses a 21 exponential moving average of the RS line to help guide his decision making. This script puts those new twists on the standard RS line, by first calculating the RS line using the low of both the security and the S&P rather than the closing prices. Next it measures the 21-day exponential moving average of the RS line and plots the distance between the two as a histogram.
A strong trending stock that is out performing the market will see an extended period of a positive blue histogram signifying the RS line is above the 21-ema.
While on the other hand a stock in a downtrend that is underperforming will see a negative red histogram a red histogram signifying the RS line is below the 21-ema.
On top of all of that, the indicator also keeps 3 & 13 exponential moving average of the distance between the RS line and the 21 ema to help identify shorter term relative strength and capture more immediate shifts in momentum. Both of those are plotted on the histogram as well and will change color as they rise and fall making it easy to spot the direction.
Indicator options include:
Choose symbol to measure performance against
Change histogram colors
Choose ema line width
* Note this indicator does not plot the actual RS line, it is the histogram representing the distance between the RS line calculated using the lows and the 21 ema, as well as the two ema's of the relationship.
Webby's RSI 2.0Webby's RSI (Really Simple Indicator) 2.0 or version 5.150 as Mike himself calls it, builds upon the original Webby RSI by changing the way we measure extension from the 21-day exponential moving average.
Instead using the percentage of the low versus the 21-day exponential moving average, version 2 uses a multiple of the securities 50 day ATR (average true range) to determine the extension.
Version 2.0 also comes with some new additions, such as measuring the high vs 21-day exponential moving average when a security is below it, as well as an ATR extension from the 10-day simple moving average that Mike looks to as a guide to take partials.
Sector MomentumThis indicator shows the momentum of a market sector. Under the hood, it's the MACD of the number of stocks above their 20 SMA in a specific sectors. The best insight it gives is to tell if the market is doing a sector rotation or having a full blown correction.
Users have the options to choose a specific sector out of the 11 sectors:
XLB, XLC, XLE, XLF, XLI, XLK, XLP, XLRE, XLU, XLV, XLY or show all them them by adding multiple indicators.
Use this indicator similar to MACD to look for momentum acceleration, deceleration and turn in a sector. More importantly, users can open up the indicator for all sectors and then compare between each.
Examples:
1. When we see momentum slows down in XLP and turn of XLK, it's a sign of sector rotation from consumer staple to tech. Money is going from defensive to riskier assets. Market is leaning towards risk-on mode. Stocks in tech have higher probability to outperform those in consumer staple.
2. When we see momentum subside across all sectors all at once or one by one, particularly both XLP, XLK/XLY, we'd expect market breadth is taking a hit across all sectors. This is not a sector rotation. A short to mid term market correction or drawdown is very likely.
Trend Reversal PredictorTrend Reversal Predictor - An Indicator for Identifying Potential Trend Reversals
This indicator is designed to help traders identify potential trend reversals in the financial markets. It combines multiple criteria including trend identification, volume analysis, average net price movement, and RSI (Relative Strength Index) crossing its moving average to highlight potential danger zones where a trend reversal may occur.
How it Works:
1. Trend Identification: The script uses the Hull Moving Average (HMA) and Parabolic SAR to determine the prevailing trend. The HMA is a smoothing indicator that reduces lag and provides a clear representation of the trend direction.
2. Danger Zone Identification: The script analyzes volume-related metrics and average net price movement to identify potential danger zones where trend reversals might occur. It calculates the rate of change of buying and selling volume and compares it to their respective averages. Additionally, it considers the average net price movement over a specified period.
3. RSI Integration: The script incorporates the RSI, a momentum oscillator, to evaluate overbought and oversold conditions. It calculates the RSI based on user-defined length and source inputs. It also calculates the RSI's moving average using different types of moving averages (SMA, EMA, etc.) specified by the user.
4. Trend Ending Prediction: By combining the conditions of trend identification, volume analysis, average net price movement, and RSI crossing its moving average, the script identifies potential trend reversal points or danger zones. These danger zones are highlighted on the chart using different colors to represent potential uptrend and downtrend reversals.
How to Use:
2. Danger Zone Highlighting: The script highlights potential danger zones on the chart using orange color for uptrend danger zones and blue color for downtrend danger zones. These danger zones suggest areas where a trend reversal may occur.
3. Additional Analysis: Traders can further analyze the danger zones based on their trading strategy and risk management. Consider other technical indicators, price action, and fundamental factors to make informed trading decisions.
Please note that this script provides potential signals for trend reversals but does not guarantee their occurrence. It is important to use this indicator in conjunction with other technical analysis tools and risk management techniques to make well-informed trading decisions.
By understanding the underlying concepts and using the provided visual cues, traders can leverage the Trend Reversal Predictor to potentially identify potential trend reversals in the markets.
Dynamic Trend RipperThe "Dynamic Trend Ripper" indicator is designed to identify dynamic support and resistance levels based on exponential moving averages (EMA) and the average true range (ATR). It aims to assist traders in identifying potential trading opportunities by visualizing dynamic support and resistance areas on the price chart. Think of it as more of overbought or oversold areas then true support and resistance,
The indicator calculates two sets of EMAs: two for the top cloud and two for the bottom cloud. The lengths of these EMAs are determined by user-defined input parameters. Additionally, the indicator uses the ATR to adjust the EMAs, enhancing their effectiveness as dynamic support and resistance levels.
The top cloud is formed by adding the ATR to the top fast EMA and subtracting the ATR from the top slow EMA. The bottom cloud is formed by subtracting the ATR from the bottom fast EMA and adding the ATR to the bottom slow EMA.
The indicator plots the dynamic OB (Overbought) level, which is the top fast EMA plus the ATR multiplied by the OBOS multiplier. It also plots the dynamic OS (Oversold) level, which is the top slow EMA minus the ATR multiplied by the OBOS multiplier. These levels are visualized using colored lines on the chart.
The top fast EMA, top slow EMA, bottom fast EMA, and bottom slow EMA are also plotted on the chart. The area between the top slow EMA and top fast EMA is filled with a color, forming the top cloud. The area between the bottom fast EMA and bottom slow EMA is filled with another color, forming the bottom cloud. The color of the clouds changes based on the relationship between the top fast EMA and top slow EMA. If the Regular Fast EMA is greater than the Regular slow EMA, indicating a bullish trend, the clouds are displayed in green. Otherwise, if the top fast EMA is less than the top slow EMA, indicating a bearish trend, the clouds are displayed in red.
The indicator can be used to identify potential support and resistance zones where the price may encounter obstacles or reverse its direction. Traders can look for price interactions with the dynamic support and resistance levels, as well as the OB and OS levels, to make trading decisions. For example, a trader might consider entering a short trade when the price approaches the top cloud, or a long trade when the price bounces off the bottom cloud.
By incorporating the ATR, which measures volatility, the indicator adjusts the EMAs to adapt to changing market conditions. Traders can watch for price reactions or reversals near these levels to gauge potential overextension or exhaustion in the price movement. I'm not going to claim this as my own idea, but I will say that I came up with this version myself. I haven't seen anyone else take this approach which is why I think it can be revolutionary to trading.
EXTREME OVERBOUGHT/SOLD BANDS
ATR-ADJUSTED EMA'S
IKH Cloud V1.0 (nextSignals)The IKH Cloud V1.0 (nextSignals) is an Ichomoku-type indicator that can be used for various trading strategies. It's based on a ThinkScript study from @stephenharlinmd (aka nextSignals) that uses an instantaneous moving average as the base MA, and a custom trailing stop. Both of these components form the cloud.
Indicator Components and Calculation
The indicator comprises two key components:
Instantaneous Moving Average (IMA) : This is a type of moving average that places a greater weight on the most recent data points, and is based on Ehler's book "Rocket Science for Traders". This is slightly different from the Doc's original, but is very approximate.
Trailing Stop : This component helps determine the stop loss level that moves along with the price. The trailing stop is based on the highest high and the lowest low of the last 5 bars, as well as the simple moving averages of the low and high of the previous bar. The trailing stop is calculated separately for each condition: when the bar index is greater than 1 and when the previous 'a' variable is either 1 or 0.
These two components are used to create a filled area on the chart, also known as the 'cloud'. The color of the cloud and the candlesticks change based on the relative positions of the IMA and the trailing stop.
How to Use the Indicator
The following are just ideas on how to use this indicator, and is not financial advice in any form:
Trend Identification: When the IMA is above the trailing stop (cloud), it indicates an uptrend, and when it's below, it indicates a downtrend.
Entry/Exit Signals: Traders can consider going long when the candlesticks move above the cloud and short when they move below the cloud.
Stop Loss Level: The trailing stop line (the cloud's edge) can serve as a dynamic stop loss level.
Please don't use just this indicator on its own. Please use this in conjunction with other analysis tools, indicators, and systems you already have in place. Always consider the overall market context and use appropriate risk management strategies.
Trend Correlation HeatmapHello everyone!
I am excited to release my trend correlation heatmap, or trend heatmap for short.
Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory!
The theory:
So what is a correlation?
Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation).
This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks.
What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted.
So what is correlation to time and what does it tell us?
Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is.
As such, correlation to time tells us two very important things. These are:
a) The direction of the stock; and
b) The strength of the trend.
Let's take a look at an example:
Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are:
1. What is the likelihood QQQ breaks down from this trendline?
2. What is the likelihood QQQ continues up?
3. What is the likelihood QQQ does a false breakdown?
There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance).
But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied:
If we look at the indicator we can see some pivotal things. These are:
1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period.
2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80.
3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles).
4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth).
With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out:
We continued up, had one test and then bounced.
Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock.
What are some tangible applications of the indicator?
For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading:
1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator.
2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this:
This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This:
The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation.
Components of the indicator:
Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options:
We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change.
Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening.
If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples:
Final Thoughts:
And that is the indicator and the theory behind the indicator.
In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses.
As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes!
That's it my friends, I hope you find it useful!
Safe trades and leave your questions, comments and feedback below!
Autocorrelation OscillatorReleasing the autocorrelation oscillator.
NOTE! Please be sure to read the description. This is a theoretical indicator and its important to understand the theory behind its use.
About the indicator:
Before getting into the indicator and its functionality, its important to discuss the theoretical underpinnings of the indicator.
The autocorrelation oscillator operates on two theories of market behaviour that go hand in hand. Those theories are the market efficiency theory and the random walk theory (or hypothesis ).
Market efficiency theory: The market efficiency theory or "Efficient Market Hypothesis (EMH)" postulates that all available information is reflected in a ticker's price almost instantaneously and thus it is impossible for an investor or trader to get ahead of the market because we cannot respond to the speed that the market responds. Of course, there are many holes in this theory, the most notable being that the market is a function of humans. Absent humans and their technological integrations into the market, the market would cease to react at all. But that's besides the point. This is a widely accepted theory and one in which I can mathematically observe through statistical tests. The truth behind this theory is the market is efficient for responding to evolving economic and financial information, likely owning to huge amounts of computer and algorithmic integration into trading, and thus the market is more efficient than the average person is capable (absent computerized algorithms and integration) of ascertaining nuanced financial and economic circumstances. By the time we the people can appraise information, the market has already acted on it. And that is the main premise of the EMH.
The next theory is the Random Walk Theory or Hypothesis (RWH). This builds on the EMH and essentially postulates that the market reacts so quickly to price in current circumstances that it is too random for people to truly exploit and benefit from.
The result of these two theories is two-fold and can be summarized as such:
a) The market behaves in a chaotic fashion that is seemingly random and is incapable of being predicted effectively; and
b) The market is more efficient than a person in incorporating key fundamental information, contributing to the high degree of seemingly random behaviour.
So, how does this help us?
It is said, because of the EMH and the RWH, the only way to truly exploit the market for profit is by:
a) Buying and holding and investing under the bias that stocks will eventually rise in value; or
b) For short term trading, exploiting the pricing anomalies within the data.
So how do we exploit pricing anomalies within the data?
Well, in my own research on market efficiency and behaviour, I have identified many ways of figuring out some anomalies. One of the most effective ways is by looking at simple correlation of lagged values, or autocorrelation for short.
What is autocorrelation and how to use it in relation to EMH and RWH?
Autocorrelation refers to the correlative relationship among the values in a series. Put simply, its the relationship of the same variable over time. For example, if we wanted to look at the auto-correlation of a ticker's high price, we would take, say, 5 to 7 previous high prices and correlate them with the current high price in a series dataset. If the EMH and RWH are true, the correlation among all the variables should have an average less than 0.5 or greater than -0.5. This would indicate true randomness in the dataset and thus an efficient market.
However, if the average of all of the sum's of these correlations are greater than or equal to 0.5 or less than or equal to -0.5, that indicates there is a high degree of autocorrelation and thus the EMH ad RWH is being invalidated as the market is not operating efficiently. This is an anomaly and this anomaly can be exploited.
So how do we exploit it?
Well, when the EMH and RWH hypothesis is being invalidated, we can expect what I coin as a "Regression to Chaos" i.e. the market will revert back to an efficient equilibrium state. So if we have a high correlation of the lagged variables and a strong uptrend or downtrend correlation, we can expect an inefficient market to correct back to an efficient market (i.e. have a reversal from the current trend).
So how does the indicator work?
The indicator measures the lagged correlation of the previous 5 highs and lows of a ticker. A high correlation among all of the highs and lows that exceeds 0.8 would be an invalidation of the EMH and RWH and thus signal a correction to come (i.e. a Regression to Chaos).
The indicator will display this by changing colour. Red for a bearish reversal and green for a bullish. Let's take a look below using the ticker MSFT:
Above we can see the indicator identifying observed inefficiencies within the MSFT ticker on the 1 minute timeframe. The green vertical lines correspond to potential bullish reversals as a result of bearish inefficiencies, the red correspond to bearish reversals as a result of bullish inefficiencies.
You can see these lead to reversals within the ticker.
Components of the indicator:
In the chart above we see the following that are being indicated by arrows:
Red Arrows: Show the identified inefficiencies. Red for bullish inefficiencies (i.e. bearish reversal), green for bearish inefficiencies (i.e. bullish reversal)
Yellow Arrow: The lagged variable chart. This will display the current correlation among all the lagged variables the indicator is assessing.
Teal arrow: Displays the current strength of the trend by correlating the trend to time. A strong negative value (i.e. a value less than or equal to -0.5) indicates a strong downtrend, a strong positive value indicates the inverse.
You can unselect the data-tables in the settings menu if you just want to view the correlation line itself. This part of the indicator is customizable. You can also define the lookback period; however, it is strongly recommended to leave it at 14 as this maintains the use of this indicator as an oscillator.
And that is the indicator! Let me know your comments, questions and feedback below.
Safe trades everyone!
Anchored VWAP (Auto High & Low)OVERVIEW
This script plots, and auto-updates, 3 separate VWAPs: a traditional VWAP, a VWAP anchored to a trends high, and another anchored to a trends low.
VWAP and Anchored VWAPs are commonly used by institutions responsible for the majority of market volume on a given day. Citadel Trading, for example, accounts for approximately 35% of all U.S. listed retail volume , largely executed through program trades over the course of a day, week, or month.
Because VWAP is a prominent market maker tool for executing large trades, day traders can use it to better anticipate trends, mean reversion, and breakouts.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (1 hour or greater) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
The size, color, and visibility of 6 different plots (VWAP, High Anchor, Low Anchor, Average of Anchors, Quarter Values, Interim Bands)
How smooth the average displays
INSPIRATION
1. "How To Measure Anything" by Douglas W. Hubbard
2. "Maximum Trading Gains With Anchored VWAP" by Brian Shannon
Better understanding probability and how to analyze risk (first book), as well as the tools market makers use (second book), has completely reframed how I approach day trading.
Trendilo LSMA Band ExampleThe "Trendilo LSMA Example" indicator is a technical analysis tool that combines two moving averages, the Linear Regression Moving Average (LSMA) and the Hull Moving Average (HMA), to provide insights into market trends.
The indicator plots a line on the price chart, which represents the combined values of the LSMA and HMA. This line changes color based on the direction of the trend. When the line is green, it suggests an upward trend, indicating that prices may continue to rise. Conversely, when the line is red, it suggests a downward trend, indicating that prices may continue to fall. If the line is yellow, it suggests a neutral or sideways trend, indicating that prices may be moving within a range without a clear trend.
Traders can customize the indicator by adjusting the input parameters. The "LSMAlen" parameter determines the length of the LSMA, the "LSMA Offset" parameter sets the offset for the LSMA, and the "LSMA Smoother" parameter controls the smoothing factor. Additionally, the "HMAlen" parameter determines the length of the HMA.
By using the Trendilo LSMA Example indicator, traders can get a visual representation of the market trend and use it to make informed trading decisions. Green indicates a potential buying opportunity, red suggests a potential selling opportunity, and yellow suggests a period of uncertainty where it may be prudent to wait for a clearer trend signal.
% Stocks Above MABreadth indicator showing % stocks above various moving averages. Histogram is positive (blue) when % stocks above selected MA is greater than 50%. Histogram is negative (red) when % of stocks above selected MA is less than 50%. Data manipulation causes the actual % value in y-axis to be incorrect but enhances visualization. Actual %'s are simply the displayed values + 50.
Improvements / suggestions welcome.
Trendilo (OPEN-SOURCE)The provided code is a custom indicator called "Trendilo" in TradingView. It helps traders identify trends in price data. The indicator calculates the percentage change of the chosen price source and applies smoothing to it. Then, it calculates the Arnaud Legoux Moving Average (ALMA) of the smoothed percentage change. The ALMA is compared to a root mean square (RMS) band, which represents the expected range of the ALMA values. Based on this comparison, the indicator determines whether the trend is up, down, or sideways. The indicator line is plotted in a color corresponding to the trend direction. The indicator also provides the option to fill the area between the indicator line and the RMS band. Additionally, users can choose to color the bars of the chart based on the trend direction. Overall, the "Trendilo" indicator helps traders visually identify trends and potential reversals in the price data.
Positive Volatility and Volume GaugeThis is my first published script. It is a real volatility gauge that allows the user to see the real volatility of a given candle on the 15-min time frame. It also has the SMA of real volatility and volume available.
It provides the user to identify high volatility points that can lead to reversals back to the mid-point of said high volatility.
You can change the threshold of the signal line. For the 15-min time frame, I suggest that the 1.5-2.5 threshold be used for the best view.
Good luck and let me know if you have any questions or suggestions. I'm always open to learning.
Thank you!
Fibonacci Levels on Any Indicator [By MUQWISHI]▋ INTRODUCTION :
A “Fibonacci Levels on Any Indicator” can be applied to any indicator to draw Fibonacci levels based on provided conditions of two price points to produce a sequence of horizontal line levels starting from 0% to 100% in addition to extension levels. The 0% level is measured as the start of retracement, while the 100% level is the beginning of the extension levels. This tool was developed to be easy to add to any indicator, and it could be valuable to some traders in terms of managing trades by setting targets and reducing risk in the trend direction.
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▋ USAGE:
➤ NEEDS TO IDENTIFY 4 ELEMENTS:
1. Starting Point. What’re the conditions / When will the drawing of the Fibonacci levels begin?
2. Ending Point. What’re the conditions / When will the drawing of the Fibonacci levels end?
3. High Point. What is the price for a 100% Fibonacci level (0% for the downside)?
4. Low Point. What is the price for a 0% Fibonacci level (100% for the downside)?
➤ STARTING & ENDING POINTS CONDITIONS:
Need to specify the condition when the drawing of Fibonacci levels starts and ends, and the indicator shows different prepared conditions.
New Phase: Import a value (plot) from an existing indicator, where its status changes from NaN to a real number.
Crosses Above/Below: Import a value(1) (plot) from an existing indicator, where it crosses above/below value(2).
Reversal Up/Down: Import a value(1) (plot) from an existing indicator, where it rises/decreases than the previous value(1).
First/Last Bar: Useful to draw stationary Fibonacci levels.
➤ UPPER & LOWER PIVOTS (0% & 100%):
Need to specify the two price points representing 0% & 100% Fibonacci levels to expose the sequence of Fibonacci lines.
Upper Pivot. By default, the ATR Upper Band. It’s possible to import a custom value from an existing indicator.
Lower Pivot. By default, the ATR Lower Band. It’s possible to import a custom value from an existing indicator.
➤ FIBONACCI STYLING OPTIONS:
Ability to customize line & label style, color, reverse, and hide/show levels.
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▋ IMPLEMENTATION:
Here are some examples of implementing the indicator.
Note: All presented examples below are for demonstration purposes, and they're not trading suggestions.
＃ Example 1: (Reversal Up/Down)
We want to implement Fibonacci levels on the Hull MA by mohamed982 . Our requirements are as follows:
Fibonacci levels start when the Hull MA reverses up.
Fibonacci levels end when the Hull MA reverses down.
Upper Pivot is the ATR Upper Band.
Lower Pivot is the ATR Lower Band.
After adding the required indicator (Hull MA), here’re the implementation and results
＃ Example 2: (Crosses Above/Below)
We want to implement Fibonacci Level on the Squeeze Momentum by LazyBear . Our requirements are as follows:
Fibonacci levels start when the Squeeze Momentum histogram crosses above 0.
Fibonacci levels end when the Squeeze Momentum histogram crosses below 0.
Upper Pivot is the Bollinger Upper Band.
Lower Pivot is the Bollinger Lower Band.
After adding the required indicators (Squeeze Momentum & Bollinger Band), here’re the implementation and results
＃ Example 3: (Crosses Above/Below)
We want to implement Fibonacci Level on the Crossing Moving Averages. Our requirements are as follows:
Fibonacci levels start when the 20-EMA crosses above 100-MA.
Fibonacci levels end when the 20-EMA crosses below 100-MA.
Upper Pivot is the ATR Upper Band.
Lower Pivot is the ATR Lower Band.
After adding the required indicators (20-EMA & 100-MA), here’re the implementation and results
＃ Example 4: (New Phase: When the previous value is NaN, and the current value is a real number.)
We want to implement Fibonacci Level on the Supertrend. Our requirements are as follows:
Fibonacci levels start when an up-Supertrend (green) line shows up.
Fibonacci levels end when a down-Supertrend (red) line shows up.
Upper Pivot is the down-Supertrend.
Lower Pivot is the up-Supertrend.
After adding the required indicator (Supertrend), here’re the implementation and results
＃ Example 5: (First/Last Bar)
We want to implement Fibonacci Level between two points, 330 & 300. Our requirements are as follows:
Fibonacci levels start at first bar on the chart.
Fibonacci levels end at last bar on the chart.
Upper Pivot is 330.
Lower Pivot is 300.
Here’re the implementation and results.
To customize the number of bars back (like 50 bars)
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▋ Final Comments:
The “Fibonacci Levels on Any Indicator” is made to apply on other indicators for planning Fibonacci Levels.
It can be implemented in different ways, along with presented examples.
This indicator does not work with plots that were developed by drawing classes.
Please let me know if you have any questions.
Thank you.
Visible Range Linear Regression Channel [vnhilton](OVERVIEW)
This indicator calculates the linear regression channel for the visible bars shown on the chart instead of the traditional fixed length linear regression channel TradingView provides (and is more accurate I believe). Inspired by TradingView's Linear Regression Channel and Visible Average Price indicator, and the DAS Trader linear regression indicator.
(FEATURES)
- Ability to extend lines to the right
- Show/hide individual lines
- Adjust standard deviation of bands
- Adjust line style and width of basis and band lines
- Change individual line colours and plot fills between the lines
(DIFFERENCES)
If you compare this indicator to TradingView's Linear Regression Channel, you will notice some differences (as of 11th June, 2023). Differences and reasons are:
1) The intercept is wrong. The formula TradingView uses to calculate the intercept includes the addition of the gradient, which I believe is incorrect. Difference #2 is also why the intercept is wrong. This indicator omits that addition. This was verified by comparing the gradient calculated in this indicator with the gradient determined by Excel with the same data.
2) The gradient is "wrong". In quotations as essentially TradingView's code attempts to find the line of best fit, with the y-axis on the most recent bar instead of the oldest bar. This leads to the gradient being the opposite to the gradient found in this indicator, which isn't wrong, but the later formula used to calculate the intercept doesn't take this into account, resulting in an incorrect intercept value. The gradient and intercept values in this indicator matches those found in Excel.
3) Standard deviation bands of both indicators. I believe the code TradingView uses to calculate standard deviation is incorrect (basing this just through visuals). This indicator uses the array.stdev function to find the correct value (verified with Excel numbers).
Z-Score Retracement Indicator Releasing the Z-Score Retracement Indicator
What it does:
The Z-Score retracement indicator operates similarly to Fibonacci retracements. It calculates the average, standard deviation and Z-Scores of a user defined period and will plot out the various Standard Deviation levels and price targets based on the period under analysis.
It will visually display the distance from the mean and which price targets correspond to which standard deviation. It is intended to aid traders in determining where the mean is and to calculate the probability of price targets and the probability of a regression to the mean.
How do you use it?
When you launch the indicator, it will ask you to identify the start period. I always try to identify periods where the most recent uptrend or downtrend has started, and then start the analysis from that point. When you plot it, the indicator will display the current strength of the trend in the same way that a regression or log-linear regression indicator would, by displaying the Pearson Correlation Coefficient:
Unlike with linear regression or log-linear regression, you don't necessarily need to have a strong up or downtrend to use the indicator, however it is ideal to find an area with a clear trend.
From there, you can clearly see the standard deviation zones:
The indicator will also display the current Standard Deviation of the last close price.
The centre line (a Z-Score of 0) corresponds to absolute neutrality and would be a regression to the mean. The price target for this area is also listed.
If you want to calculate the price of a specific Standard Deviation, you can! Launch the settings and select the input you would like:
Simply select whether you want to convert a Standard Deviation Z-Score to price or price to Z-Score. Then input the variable into the appropriate field. The indicator will then display the results in a table at the top right of the chart:
In the above image, you can see that a Z-Score of 0 (indicating absolute neutrality) on QQQ is equivalent to a price of 299.
Calculating Probability:
You can calculate probability by reference a Z-Score Table. I have discussed this in my previous Z-Score based indicators, but essentially, the rule of thumb is this:
Anything over + 2 standard deviations corresponds with roughly less than a 5 to 10% chance of continuation higher. I encourage you to check out the writeup on my Z-Score Probability Indicator for more information on the price use of Z-Score for probability determinations.
Concluding remarks:
And that is the indicator! Its pretty straight forward and its intended to be an added tool for regression and log-linear regression based traders to help visualize the actual distance from the mean a ticker is currently trading at.
Another thing to keep in mind is you can use this on the very small time frames as well. I have used this for day trading on the 5 and 1 minute timeframe to determine "regressions to the mean" on a much smaller level. Like here:
That's the indicator!
Hope you enjoy, leave your questions, comments and suggestions below, safe trades everyone!
