Relative Strength, not RSIThe Smoothed Relative Strength Indicator (not RSI) with Multi-Timeframe Support is a custom indicator that combines the concepts of Relative Strength (not RSI) and Money Flow Index (MFI) to create a smoothed trend-following tool. It works on any timeframe and adapts to different market conditions.
Key Features:
Multi-timeframe support: [ The script uses the request.security function to fetch data from other timeframes, allowing users to analyze the trend on different timeframes simultaneously.
Relative Strength calculation: The script calculates the Relative Strength (not RSI) by averaging the gains and losses over a user-defined period (len).
Money Flow Index calculation: The script calculates the Money Flow Index (MFI) by considering both price and volume data. The MFI is an oscillator that ranges between 0 and 100, and it helps identify overbought or oversold conditions in the market.
Combination of Relative Strength and MFI:The indicator calculates the average of Relative Strength and MFI values to create the Trend Reversal Strength (TRS) line.
Smoothing the TRS line: The TRS line is smoothed using a Simple Moving Average (SMA) with a user-defined smoothing length (smoothLen). This helps to reduce noise and make the trend more readable.
Trend color determination: The script determines the trend color based on the slope of the smoothed TRS line. If the current value of the smoothed TRS line is higher than the previous one, the line is colored green (uptrend). If the current value is lower than the previous one, the line is colored red (downtrend).
Visual representation of trend changes: The indicator plots small circles at points where the trend color changes, making it easier to identify potential trend reversal points.
Zero line: The script draws a horizontal line at the zero level to help users gauge the market's strength or weakness relative to this level.
Usage:
This indicator can be used as a trend-following tool to identify potential entry and exit points in the market. When the smoothed TRS line is green and rising, it suggests a bullish trend, and traders may consider entering long positions. Conversely, when the smoothed TRS line is red and falling, it indicates a bearish trend, and traders may consider short positions or exiting long trades.
Please note that this indicator should be used in conjunction with other technical analysis tools and proper risk management techniques to improve the accuracy of your trading decisions.
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Key Levels (Open, Premarket, & Yesterday)OVERVIEW
This indicator automatically identifies and draws recent high-probability support and resistance levels (recent key levels). Specifically, yesterdays highs / lows, premarket highs / lows, as well as yesterdays end of day Volume Weighted Average Price and trader specified Moving Average.
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 (greater than 1 hour) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
Line size, style, and colors
Label colors
Which key levels you want to see
Moving Average Parameters
Market Hours and Time Zone
DEV NOTES
This script illustrates:
A method for iterative management of more complex data objects (not just discrete values) with loops and arrays.
Central Bank LiquidityCentral Bank Liquidity = Total value of the assets of all Federal Reserve Banks - Overnight Reverse Repurchase Agreements (RRP) - The Treasury General Account (TGA)
TradingView ticker arithmetic: FRED:WALCL-FRED:WTREGEN-FRED:RRPONTSYD
Dynamic Trendlines Multi-TimeframeThe Dynamic Trendlines indicator is a useful tool for traders to identify potential support and resistance levels in the market. By analyzing price volatility and drawing trendlines based on high volatility candles, it helps traders visualize key price levels that may influence future price action. This indicator uses the Average True Range (ATR) as a measure of price volatility to determine the threshold for high volatility candles. This indicator can be used on multiple time frames, so just choose which one works best for you!
The underlying concept of this indicator revolves around the calculation of the True Range and Average True Range. The True Range is the maximum value among the difference between the current high and low, the absolute value of the difference between the current high and previous close, and the absolute value of the difference between the current low and previous close. The ATR is then calculated as the simple moving average of the True Range over a user-defined period (default is 14). The threshold for high volatility candles is determined by multiplying the ATR by a user-defined multiplier (default is 1.5).
The indicator identifies high volatility candles when the closing price is greater than the previous closing price plus the threshold. Based on the price action, trendlines are drawn connecting the high or low of high volatility candles. The initial color and style of the trendline are determined by whether the price is moving up or down. Green solid lines represent upward price movement, while red solid lines represent downward price movement.
As the price crosses the trendlines, the indicator tracks the number of crosses and updates the line's style accordingly. If the price crosses a trendline twice, the line style is changed to dashed, indicating the potential weakening of the support or resistance level.
This indicator works best with trading methods that focus on capturing price breakouts or reversals. Traders can use the trendlines to identify potential entry or exit points, stop-loss levels, or take-profit targets. It's important to note that this indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the Dynamic Trendlines indicator on TradingView, users can customize the ATR length, threshold multiplier, and the number of recent trendlines displayed on the chart. Additionally, small triangles are plotted below high volatility candles, with their color based on the trendline it starts, providing a quick visual reference for traders.
In summary, the Dynamic Trendlines indicator is a valuable tool for identifying potential support and resistance levels in the market by analyzing price volatility and drawing trendlines based on high volatility candles. It is best suited for breakout and reversal trading strategies and should be used in conjunction with other technical analysis tools for optimal results.
EMA/SMA Cross with LevelsThe EMA/SMA Cross indicator is a valuable trading tool designed to assist traders in identifying potential trend reversals or entry and exit points in the market. By plotting two moving averages, one based on the Exponential Moving Average (EMA) and the other on the Simple Moving Average (SMA), this indicator highlights the points at which these averages cross, signaling a potential change in the market trend. This straightforward yet powerful indicator follows the core principles of technical analysis, allowing traders to visualize key price levels that may influence future price action.
The underlying concept of this indicator revolves around the calculation and comparison of the short-term EMA and the long-term SMA. The EMA is a type of weighted moving average that gives more importance to recent price data, making it more responsive to new information. In contrast, the SMA assigns equal weight to all data points within a specified period, providing a smoother representation of price trends. By comparing these two averages, traders can gain insights into potential shifts in market sentiment and momentum.
When the short-term EMA crosses above the long-term SMA, it signals a possible bullish trend reversal, indicating that the recent price momentum is gaining strength. Conversely, when the short-term EMA crosses below the long-term SMA, it suggests a bearish trend reversal, implying that the recent price momentum is weakening. Traders can use these crossing points as potential entry or exit signals, depending on their trading strategy and risk tolerance.
A unique feature of this indicator is its ability to plot the crossing levels on the chart. When the short-term EMA crosses the long-term SMA, a dashed line is drawn horizontally at the level of the cross, emphasizing the significance of the price level. This line serves as a reference point for traders, helping them to identify potential support or resistance levels that may influence future price movements.
By plotting the crossing levels, the EMA/SMA Cross indicator offers traders an additional layer of information that can be used in their decision-making process. These levels can act as crucial points for stop-loss or take-profit orders, depending on the trader's strategy and risk tolerance. Additionally, they can serve as a basis for further technical analysis, such as the identification of chart patterns or the application of other technical indicators.
This indicator works best with trading methods that focus on capturing price reversals or breakouts. It is particularly useful for traders who employ trend-following or momentum-based strategies, as it helps them identify the optimal moments to enter or exit a trade. However, it's important to note that the EMA/SMA Cross indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the EMA/SMA Cross indicator on TradingView, users can customize the time frame, source, and length for both the short-term EMA and long-term SMA, as well as the number of recent crossing lines displayed on the chart. This flexibility allows traders to tailor the indicator to their specific trading style and preferences.
In summary, the EMA/SMA Cross indicator is an essential tool for traders looking to identify potential trend reversals or entry and exit points in the market. By comparing the short-term EMA and long-term SMA, this indicator provides valuable insights into shifts in market sentiment and momentum. It is best suited for trend-following and momentum-based trading strategies and should be used in combination with other technical analysis tools for optimal results.
Z-Score Probability IndicatorThis is the Z-Score Probability indicator. As many people like my original Z-Score indicator and have expressed more interest in the powers of the Z, I decided to make this indicator which shows additional powers of the Z-Score.
Z-Score is not only useful for measuring a ticker or any other variable’s distance from the mean, it is also useful to calculate general probability in a normal distribution set. Not only can it calculate probability in a dataset, but it can also calculate the variables within said dataset by using the Standard Deviation and the Mean of the dataset.
Using these 2 aspects of the Z-Score, you can, In principle, have an indicator that operates similar to Fibonacci retracement levels with the added bonus of being able to actually ascertain the realistic probability of said retracement.
Let’s take a look at an example:
This is a chart showing SPY on the daily timeframe. If we look at the current Z-Score level, we can see that SPY is pushing into the 2 to 3 Z-Score range. We can see two things from this:
1. We can see that a retracement to a Z-Score of 2 would correspond to a price of 425.26 based on the current dataset. And
2. We can see that the probability that SPY retraces to a Z-Score of 2 is around 0.9800 or 98%.
To take it one step further, we can look at the various other variables in the distribution. If we were to bet on SPY retracing back to -1 SDs, that would correspond to a price of around 397.15, with a probability of around 0.1600 or 16% (see image below):
Let’s say, we thought SPY would go to $440. Well, we can see that the probability SPY goes to 434.64 currently is pretty low. How do we know? Because the Z-Score table shows us the probability of values falling BELOW that Z-score level in the current distribution. So if we look at this example below:
We can see that 0.9998 or roughly 99% of values in the current SPY distribution will fall below 434.64. Thus, it may be unrealistic, at this point in time, to target said value.
So what is a Z-Score Table?
Well, I need to disclose/clarify that the Z-Score Table being displayed in this indicator does Z-Score probability a HUGE injustice. However, with the constraints what is realistic to fit into an indicator, I had to make it far more succinct. Let’s take a look at an actual Z-Score Table below:
Above is a look an the actual Z-Score table. How it works is you first identify you’re Z-Score and then find the corresponding value that relates to your score. The number displayed in the dataset represents the number of variables in the dataset/density distribution that fall BELOW that particular Z-score.
So, for example, if we have a Z-Score of -2.31, we can consult that table, go to the -2.3 then scroll across to the 0.01 to represent -2.31. We would see that this Z-Score corresponds to a 0.0104 probability zone (or essentially 1%) indicating that the majority of the variables in the distribution fall below that mean Z-score. In terms of tickers and stocks, that would mean it would theoretically be “overbought”.
So what does the indicator Z-Table tell us?
I have averaged out the data for the purposes of this indicator. However, you can also reference a manual Z-Table to get the exact probability for the current precise Z-Score. However, the reality is it doesn’t necessarily matter to be exact when it comes to tickers. The reason being, ticker’s are in constant flux, and by the time you identify that probability, the ticker will already be at a different level. So generalizations are okay in these circumstances, you just need to get the “gist” of where the distribution lies.
So how do I use the indicator?
Using the indicator is pretty straightforward. Once launched, you will see the current Z-Score of the ticker, the current levels based on the distribution and the summarized Z-Table.
The Z-Table will turn gray to indicate the zone the ticker is currently in. In this case, we can see that SPY currently is in the 2 SD Zone, meaning that 0.98 or 98% of the current dataset being shown falls below the price we are at:
When we launch the settings, we can see a few inputs.
Lookback Length: This determines the number of candles back we want to calculate the distribution for. It is defaulted to 75, but you can adjust it to whichever length you want.
SMA Length: The SMA is optional but defaults to on. If you want to see the smoothed trend of the Z-Score, this will do the trick. It does not need to be set to the same
length as the Z-Score lookback. Thus, if you want a more or less responsive SMA with, say, a larger dataset, then you can reduce the SMA length yourself.
Distribution Probability Fills: This simply colour codes the distribution zones / probability zones on the indicator.
Show Z-Table: This will display the summarized Z-Table.
Show SMA: As I indicated, the SMA is optional, you can toggle it on or off to see the overall Z-Score trend.
Concluding Remarks:
And that my friends is the Z-Score Probability Indicator.
I hope you all enjoy it and find it helpful. As always leave your comments, questions and suggestions below.
Safe trades to all and take care!
Cumulative TICK [Pt]Cumulative TICK Indicator, shown as the bottom indicator, is a robust tool designed to provide traders with insights into market trends using TICK data. This indicator visualizes the cumulative TICK trend in the form of colored columns on a separate chart below the main price chart.
Here's an overview of the key features of the Cumulative TICK Indicator:
1. Selectable TICK Source 🔄: The indicator allows users to choose from four different TICK data sources, namely USI:TICK , USI:TICKQ , USI:TICKI , and $USI:TICKA.
2. TICK Data Type Selection 🎚️: Users can select the type of TICK data to be used. The options include: Close, Open, hl2, ohlc4, hlc3.
3. Optional Simple Moving Average (SMA) 📊: The indicator offers an option to apply an SMA to the Cumulative TICK values, with a customizable length.
4. After-hour Background Color 🌙: The background color changes during after-hours to provide a clear distinction between regular and after-hour trading sessions.
🛠️ How it Works:
The Cumulative TICK Indicator uses TICK data accumulated during the regular market hours (9:30-16:00) as per the New York time zone. At the start of a new session or at the end of the regular session, this cumulative TICK value is reset.
The calculated Cumulative TICK is plotted in a column-style graph. If the SMA is applied, the SMA values are used for the column plots instead. The columns are colored green when the Cumulative TICK is positive and red when it is negative. The shades of green and red vary based on whether the Cumulative TICK is increasing or decreasing compared to the previous value.
This is a simple yet powerful tool to track market sentiment throughout the day using TICK data. Please note that this indicator is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.
Leveraged Share VolumeHello everyone,
Did this quick reference indicator and figured I would share it as nothing like it exists that I could find.
What this does is it pulls leveraged share data and displays the bull share and bear share volume.
There are 5 pre-programmed shares. These include:
SPY
Pulls bull share data from: SPXL and UPRO
Pulls bear share data from: SPXU and SPXS
IWM
Pulls bull share data from: TNA
Pulls bear share data from: TZA
DIA
Pulls bull share data from: UDOW
Pulls bear share data from: SDOW
QQQ
Pulls bull share data from: TQQQ
Pulls bear share data from: SQQQ
XLE
Pulls bull share data from: ERX
Pulls bear share data from: ERY
As there continues to be more leveraged shares available (for example, AAPU, APPD, MSFT, TSLA, etc.) there is also the option to use these manual tickers as these shares become available. The image below shows the data input screen:
The indicator will default to show the data as a ratio. The ratio is calculated by the total bear shares over the total bull shares (sell to buy ratio). If you unselect the Ratio option (displayed in the image above), it will show the raw volume.
When data is displayed as a ratio, you will see the white SMA line. This will show you the average ratio over a 14 period lookback. This is customizeable under the SMA Length input (shown in the image above).
Indicator's purpose:
The aim of the indicator is to provide context as to where the current sentiment is. Its similar in concept to a put to call ratio. The idea is, the more bearish people are, the more inverse shares are being bought, the higher the ratio or raw volume for bear shares and vice versa for bullish situations.
If you would like some more contextual information about the powers of tracking this type of data for trading purposes, you can check out this idea I published about the relationship between leveraged shares and market sentiment/behaviour:
Otherwise, the indicator is pretty straight forward!
Its not meant to be anything but a reference indicator to help give you context of the current market positioning.
If you have any questions or suggestions, please feel free to leave them below.
Thank you for reading and checking out the indicator!
Safe trades everyone!
Monthly Strategy Performance TableWhat Is This?
This script code adds a Monthly Strategy Performance Table to your Pine Script strategy scripts so you can see a month-by-month and year-by-year breakdown of your P&L as a percentage of your account balance.
The table is based on realized equity rather than open equity, so it only updates the metrics when a trade is closed.
That's why some numbers will not match the Strategy Tester metrics (such as max drawdown), as the Strategy Tester bases metrics like max drawdown on open trade equity and not realized equity (closed trades).
The script is still a work-in-progress, so make sure to read the disclaimer below. But I think it's ready to release the code for others to play around with.
How To Use It
The script code includes one of my strategies as an example strategy. You need to replace my strategy code with your own. To do that just copy the source code below into a blank script, delete lines 11 -> 60 and paste your strategy code in there instead of mine. The script should work with most systems, but make sure to read the disclaimer below.
It works best with a significant amount of historical data, so it may not work very effectively on intraday timeframes as there is a severe limitation of available bars on TradingView. I recommend using it on 4HR timeframes and above, as anything less will produce very little usable data. Having a premium TradingView plan will also help boost the number of available bars.
You can hover your mouse over a table cell to get more information in the form of tooltips (such as the Long and Short win rate if you hover over your total return cell).
Credit
The code in this script is based on open-source code originally written by QuantNomad, I've made significant changes and additions to the original script but all credit for the idea and especially the display table code goes to them - I just built on top of it:
Why Did I Make This?
None of this is trading or investment advice, just my personal opinion based on my experience as a trader and systems developer these past 6+ years:
The TradingView Strategy Tester is severely limited in some important ways. And unless you use complex Excel formulas on exported test data, you can't see a granular perspective of your system's historical performance.
There is much more to creating profitable and tradeable systems than developing a strategy with a good win rate and a good return with a reasonable drawdown.
Some additional questions we need to ask ourselves are:
What did the system's worst drawdown look like?
How long did it last?
How often do drawdowns occur, and how quickly are they typically recovered?
How often do we have a break-even or losing month or year?
What is our expected compounded annual growth rate, and how does that growth rate compare to our max drawdown?
And many more questions that are too long to list and take a lifetime of trading experience to answer.
Without answering these kinds of questions, we run the risk of developing systems that look good on paper, but when it comes to live trading, we are uncomfortable or incapable of enduring the system's granular characteristics.
This Monthly Performance Table script code is intended to help bridge some of that gap with the Strategy Tester's limited default performance data.
Disclaimer
I've done my best to ensure the numbers this code outputs are accurate, and according to my testing with my personal strategy scripts it appears to work fine. But there is always a good chance I've missed something, or that this code will not work with your particular system.
The majority of my TradingView systems are extremely simple single-target systems that operate on a closed-candle basis to minimize many of the data reliability issues with the Strategy Tester, so I was unable to do much testing with multiple targets and pyramiding etc.
I've included a Debug option in the script that will display important data and information on a label each time a trade is closed. I recommend using the Debug option to confirm that the numbers you see in the table are accurate and match what your strategy is actually doing.
Always do your own due diligence, verify all claims as best you can, and never take anyone's word for anything.
Take care, and best of luck with your trading :)
Kind regards,
Matt.
PS. If you're interested in learning how this script works, I have a free hour-long video lesson breaking down the source code - just check out the links below this script or in my profile.
Hobbiecode - RSI + Close previous dayThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. If RSI(2) is less than 15, then enter at the close.
2. Exit on close if today’s close is higher than yesterday’s high.
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
AlphaTrend - ScreenerScreener version of AlphaTrend indicator:
BUY / LONG when AlphaTrend line crosses above its 2 bars offsetted line, and there would be a green filling between them
SELL / SHORT when AlphaTrend line crosses below its 2 bars offsetted line, and filling would be red then.
Default values:
Coefficient: 1, which is the factor of the trailing ATR value
Common Period: 14, which is the length of ATR MFI and RSI
AlphaTrend default uses MFI in the calculation, and MFI (Money Flow Index) needs the volume data of the chart.
If your chart doesn't have the volume data, please select the "Change Calculation" option to use RSI instead of MFI.
Screener Panel:
You can explore 20 different and user-defined tickers, which can be changed from the SETTINGS (shares, crypto, commodities...) on this screener version.
The screener panel shows up right after the bars on the right side of the chart.
Tickers seen in green are the ones that are in an uptrend, according to AlphaTrend.
The ones that appear in red are those in the SELL signal, in a downtrend.
The numbers in front of each Ticker indicate how many bars passed after the last BUY or SELL signal of AlphaTrend.
For example, according to the indicator, when BTCUSDT appears in (3) and in GREEN, Bitcoin switched to BUY signal 3 bars ago.
Hui-Heubel Liquidity RatioThe Hui-Heubel Liquidity Ratio (lhh) is a measurement of market resiliency and liquidity. Higher values indicate a more liquid and resilient market, lower values indicate a more fragile market susceptible to volatile moves. It does not work on all tickers (for example, if something does not report volume).
Generally, you will see lhh rise when stocks sell off and fall when they are bought. Occasionally you will see scenarios where price will go up while lhh does as well, often this is a symptom of short covering.
Includes two configurable SMAs and a configurable lookback window.
Chilllax Moving Averages with Qullamaggie colors// Display 2 Moving Averages. Default is 10d sma and 20d sma. You can choose any length. Choose sma, or ema. Choose ma of Open, High, Low, or Close
// Color code is based on Qullamaggie's idea:
// Dark green = 10d ma > 20d ma, and both trending up
// Light green = 10d ma > 20d ma, but only 10d ma trending up
// Yellow = 10d ma > 20d ma, but neither trending up
// You can change the color
// You can hide the colors, then it will simply show 2 moving averages of your choice
// Trend is comparing the ma from X trendlen days ago. Default to 5 days ago. So, if today's ma is > 5 days ago, it is trending up
ATR Daily BandThis indicator draws an upper and lower band for each day. It uses the Average True Range calculation (with configurable lookback) and places the band at 1ATR above and 1ATR below the daily open.
I use this indicator as a simple gauge to tell how significant price movement is, and get a feel for the daily volatility. Due to the fractal nature of price action, it can be difficult to determine if a price movement is significant while zoomed in on a single intraday chart. Using this indicator, I can tell if the price action is approaching the ATR or if it's just staying within the band.
Strategies: Useful for both mean reversion and momentum strategies. It's up to you to decide how this metric will fit into your trading strategy. I currently use this indicator to look for mean reversion setups, but that is due to the current market conditions and my personal trading style.
[TTI] NDR 63-Day QQQ-QQEW ROC% SpreadWelcome to the NDR 63-Day QQQ-QQEW ROC% Spread script! This script is a powerful tool that calculates and visualizes the 63-day Rate of Change (ROC%) spread between the QQQ and QQEW tickers. This script is based on the research conducted by Ned Davis Research (NDR), a renowned name in the field of investment strategy.
⚙️ Key Features:
👉Rate of Change Calculation: The script calculates the 63-day Rate of Change (ROC%) for both QQQ and QQEW tickers. The ROC% is a momentum oscillator that measures the percentage price change over a given time period.
👉Spread Calculation: The script calculates the spread between the ROC% of QQQ and QQEW. This spread can be used to identify potential trading opportunities.
👉Visual Representation: The script plots the spread on the chart, providing a visual representation of the ROC% spread. This can help traders to easily identify trends and patterns.
👉Warning Lines: The script includes warning lines at +600 and -600 levels. These lines can be used as potential thresholds for trading decisions.
Usage:
To use this script, simply add it to your TradingView chart. The script will automatically calculate the ROC% for QQQ and QQEW and plot the spread on the chart. You can use this information to inform your trading decisions.
🚨 Disclaimer:
This script is provided for educational purposes only and is not intended as investment advice. Trading involves risk and is not suitable for all investors. Please consult with a financial advisor before making any investment decisions.
🎖️ Credits:
This script is based on the research conducted by Ned Davis Research (NDR). All credit for the underlying methodology and concept goes to NDR.
Time Series Model IndicatorHello,
I am releasing this time series modelling indicator.
Brief overview of the indicator's functionality:
The Time Series Model indicator is a technical analysis tool that calculates and visualizes a linear regression line based on historical price data. It assesses the trend direction and provides an outer band around the regression line to indicate potential support and resistance levels. The indicator also detects outliers in the price data and calculates correlations between the time variable and the closing price. It offers various customization options such as input length, user-defined hours in advance, display settings for tables and fills, and the ability to show variable correlations. Overall, this indicator aims to help traders identify trends, potential reversals, and price extremes in a given time series.
Specific Functions:
Slope Calculations: The indicator calculates the slope and intercept of the regression line using the specified length of assessment (user defined). It also computes the residuals, standard error of the regression, and the upper and lower bounds of the standard error region. Additionally, it calculates multiple standard deviation bands around the regression line. The slope will change to green if the stock is in an uptrend and to red if the stock is in a downtrend.
Outliers: This feature detects extreme positive and negative outliers based on the z-score calculated from the price data. It highlights the outliers with a red background color to red if this option is selected.
Correlation to Time Assessments: This feature performs trend assessments based on the correlation between time and price data. It identifies uptrends, downtrends, falling trends, rising trends, etc.
Outerband Plots: This feature plots the regression line, standard error bands, and multiple standard deviation bands around the regression line. It also fills the areas between these lines.
Trend Assessment: This feature further assesses the trend based on the strength of the correlation. It identifies strong up or down trends, moderate trends, weak trends, no trend, etc.
Linear Regression Time Data: This section retrieves price data (close, high, low, open) for the specified timeframe and stores them in arrays for a linear regression analysis.
Define LinReg Variables: This section calculates linear regression lines and their upper and lower control limits for the close, low and high prices. It also calculates the correlation between close price and time.
Manual assessments: This feature allows for the manual assessment of time series data. The user can input a look forward for hours in the future and get the predicted price range based on the current time relationship. See image below:
Calculating model "fit": The indicator will display the amount of time the stock closes within and outside its respective bands to ascertain the degree of "fit" (see image below):
Explanations:
The outer cloud: The outer, tealish green cloud represents the regression line + 1.5 standard deviations from the regression line.
The inner cloud: The inner, white coloured cloud represents the immediate time series range calculated through regression of the open, high and low price of the ticker.
Correlations:
The ability of the indicator to calculate correlations on both the smaller and larger timeframes are its strongest feature. You can see the formation of trends by tracking the correlation over the length of the time series model's assessment. You can also track the degree of change. The image below shows the correlation table:
In this image, we can see that the stock is in a moderate downtrend manifested by a correlation of -0.73 (purple arrow).
This downtrend is weakening as manifested by a positive change of 0.05 on the shorter timeframe.
If we scroll down on the table and see the Close, High and Low, we can see that the larger trend over time is a downtrend and that this downtrend is actually strengthening. We know this by the negative change (negative change = significant inverse relationship to time is increasing. i.e. as time increases, the stock price decreases proportionately).
So what does negative correlation to time mean?
If a stock's price exhibits a negative correlation to time, it implies that there is a systematic relationship between the passage of time and the stock's price movement in the opposite direction. This finding could have several potential implications for traders and investors. Firstly, it suggests that the stock's price tends to decrease as time progresses, indicating a downward trend or bearish sentiment. This information might be useful for traders looking to capitalize on short-selling or hedging strategies. Secondly, it could indicate a potential opportunity to predict future price movements based on the timing of negative correlations. By understanding the relationship between time and price, investors may be able to make more informed decisions about when to buy or sell the stock. Lastly, a negative correlation to time may also suggest the influence of external factors or market conditions that systematically impact the stock's performance over time. Therefore, monitoring this correlation can provide insights into broader market dynamics and help investors better understand the stock's behavior.
What about a positive correlation to time?
If a stock's price demonstrates a positive correlation to time, it means that there is a consistent relationship between the passage of time and the stock's price movement in the same direction. This positive correlation to time can have significant implications for traders and investors. Firstly, it indicates a potential upward trend or bullish sentiment, suggesting that the stock's price tends to increase as time progresses. This information can be valuable for investors seeking long-term growth opportunities or looking to capitalize on upward price movements. Secondly, a positive correlation to time may provide insights into the stock's historical performance patterns and help identify potential buying or selling opportunities based on the timing of positive correlations. Additionally, understanding this correlation can aid in assessing the stock's overall trajectory and identifying potential market trends. It's important to note that positive correlation to time does not guarantee future performance, but it can offer valuable information to inform investment decisions.
Because this indicator is pretty big, I have done an overview and tutorial video which I will link below:
As always, please leave your comments and suggestions below.
I thank you for taking the time to read and check out this indicator.
Safe trades everyone and enjoy your weekend!
Cumulative TICK Trend[Pt]Cumulative TICK Trend indicator is a comprehensive trading tool that uses TICK data to define the market's cumulative trend. Trend is shown on ATR EMA bands, which is overlaid on the price chart. Cumulative TICK shown on the bottom pane is for reference only.
Main features of the Cumulative TICK Trend Indicator include:
Selectable TICK Source: You have the flexibility to choose your preferred TICK source from the following options, depending on the market you trade: USI:TICK, USI:TICKQ, USI:TICKI, and USI:TICKA.
TICK Data Type: Select the type of TICK data to use, options include: Close, Open, hl2, ohlc4, hlc3.
Simple Moving Average (SMA): You can choose to apply an SMA on the calculated Cumulative TICK values with a customizable length.
Average True Range (ATR) Bands: It provides the option to display ATR bands with adjustable settings. This includes the ATR period, EMA period, source for the ATR calculation, and the ATR multiplier for the upper band.
Trend Color Customization: You can customize the color of the bull and bear trends according to your preference.
Smooth Line Option: This setting allows you to smooth the ATR Bands with a customizable length.
How it Works:
This indicator accumulates TICK data during market hours (9:30-16:00) as per the New York time zone and resets at the start of a new session or the end of the regular session. This cumulative TICK value is then used to determine the trend.
The trend is defined as bullish if the SMA of cumulative TICK is equal to or greater than zero and bearish if it's less than zero. Additionally, this indicator plots the ATR bands, which can be used as volatility measures. The Upper ATR Band and Lower ATR Band can be made smoother using the SMA, according to the trader's preference.
The plot includes two parts for each trend: a stronger color (Red for bear, Green for bull) when the trend is ongoing, and a lighter color when the trend seems to be changing.
Remember, this tool is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.
Strongest TrendlineUnleashing the Power of Trendlines with the "Strongest Trendline" Indicator.
Trendlines are an invaluable tool in technical analysis, providing traders with insights into price movements and market trends. The "Strongest Trendline" indicator offers a powerful approach to identifying robust trendlines based on various parameters and technical analysis metrics.
When using the "Strongest Trendline" indicator, it is recommended to utilize a logarithmic scale . This scale accurately represents percentage changes in price, allowing for a more comprehensive visualization of trends. Logarithmic scales highlight the proportional relationship between prices, ensuring that both large and small price movements are given due consideration.
One of the notable advantages of logarithmic scales is their ability to balance price movements on a chart. This prevents larger price changes from dominating the visual representation, providing a more balanced perspective on the overall trend. Logarithmic scales are particularly useful when analyzing assets with significant price fluctuations.
In some cases, traders may need to scroll back on the chart to view the trendlines generated by the "Strongest Trendline" indicator. By scrolling back, traders ensure they have a sufficient historical context to accurately assess the strength and reliability of the trendline. This comprehensive analysis allows for the identification of trendline patterns and correlations between historical price movements and current market conditions.
The "Strongest Trendline" indicator calculates trendlines based on historical data, requiring an adequate number of data points to identify the strongest trend. By scrolling back and considering historical patterns, traders can make more informed trading decisions and identify potential entry or exit points.
When using the "Strongest Trendline" indicator, a higher Pearson's R value signifies a stronger trendline. The closer the Pearson's R value is to 1, the more reliable and robust the trendline is considered to be.
In conclusion, the "Strongest Trendline" indicator offers traders a robust method for identifying trendlines with significant predictive power. By utilizing a logarithmic scale and considering historical data, traders can unleash the full potential of this indicator and gain valuable insights into price trends. Trendlines, when used in conjunction with other technical analysis tools, can help traders make more informed decisions in the dynamic world of financial markets.
Autoregressive CloudHello,
I am releasing this indicator called the Autoregressive Cloud Indicator.
What it does:
The indicator performs an autoregression analysis on 3 price variables of a ticker, those being the High, the Low and the Close. It uses a 1-lag system and looks back at the previous close, high and low’s effect on the proceeding high, low and close. It then plots out the anticipated range for the ticker based on the autoregression analysis, as well as displays the lag-correlation (autocorrelation) in a table.
What is Autoregression analysis?
Autoregression is a modelling technique used to describe a time series based on its own past values. It assumes that the current value of a variable is a linear combination of its previous values and a random error term.
And what is autocorrelation?
Autocorrelation measures the correlation between a time series and its lagged values. It quantifies the degree to which the current value of a series is related to its past values at different lags, indicating any patterns or dependencies in the data over time. Autoregression and autocorrelation are closely related concepts used to analyze and model time series data.
So how does it work?
The indicator calculates autoregressive values for the close, high, and low prices of a security based on the specified lookback length (which is defaulted to 50). It then plots three sets of clouds representing the smoothed autoregressive values for each price component (done using the SMA function). The transparency of the clouds can be adjusted using the "Transparency" input. Additionally, the code includes a correlation table that displays the correlation coefficients between the lagged values of the close, high, and low prices. The table's position can be customized using the "Position" input.
The indicator defaults to the chart timeframe; however, you can manually adjust the indicator to display the range for whatever timeframe you would like. You can view the 30 minute, 15 or even hourly range on the 1 minute or 5 minute chart if you want.
The indicator will show the anticipated “true trading range” of the stock based on the autoregression and autocorrelation of all 3 variables:
Above is SPY on the 5 minute timeframe with 15 minute levels overlayed. Here, you can see the anticipated trading range for that 15 minute time period.
Using the Correlation Table:
The correlation table displays the Pearson Coefficient for all 3 autoregressions.
A positive correlation: A positive autocorrelation indicates a positive relationship between past and current values of a time series variable. It suggests that when the variable has a high value at a certain time, it is more likely to have a high value in the future, and when it has a low value, it is more likely to have a low value in the future. This positive autocorrelation can imply persistence or trend in the data, indicating that past values can provide useful information for predicting future values. The rule of thumb is anything over 0.5 is considered significant.
A positive correlation among all 3 variables also indicates an uptrend. If you see a strong positive (i.e. the values are all greater than 0.8), it indicates an incredibly decisive and strong uptrend.
A negative correlation: A negative autocorrelation indicates an inverse relationship between past and current values of a time series variable. It suggests that when the variable has a high value at a certain time, it is more likely to have a low value in the future, and vice versa. This negative autocorrelation can imply mean reversion or oscillatory behavior in the data, where extreme values tend to be followed by values closer to the average. It indicates that past values can provide useful information for predicting future values by anticipating a reversal in the direction of the variable. The rule of thumb is anything below or equal to -0.5 is considered significant.
A negative correlation among all 3 variables also indicates a downtrend. If you see a strong negative (i.e. the values are all less than or equal to -0.8), it indicates an incredibly decisive and strong downtrend.
Uses of the Indicator:
The indicator can be used for the following functions:
1. Day trading and scalping within an expected range;
2. Determining the strength or weakness of an uptrend or downtrend on various timeframes;
3. Determining the relationship between previous values and past performance and its effect on future performance;
4. Can alert to changes in trend direction in advance (you may see high, low or close turn negative before others, signifying that weakness is beginning to materialize in an uptrend, or inverse in a downtrend (value changes positive)).
Customizability:
SMA: The autoregression data is smoothed by a 3 period lookback. You can change this if you want, but in order for the indicator to present the true trading range, it is recommended to leave it at <= 3.
Lookback Length: This is the length of the lookback period for the autoregression and autocorrelation functions.
Transparency settings: You can adjust the transparency of the clouds manually.
Timeframe: You can adjust the timeframe, as explained above, to display the timeframe of interest. When you adjust the timeframe, the data will all reflect that timeframe and not necessarily the current TF you have open (i.e. you select 30 minutes while viewing it on the 5 minute, it will show the data for the 30 minute TF period).
Video Tutorial:
I have prepared a video outlining the indicator and also explaining the theory of autoregression/correlation. You can find it below:
Let me know any comments, questions or suggestions below.
Thank you for taking the time to read/watch and check out this indicator.
Safe trades everyone!
Exponential ADR with Price TargetsThis script is designed to help you analyze price movements in the financial markets by calculating the Average Daily Range (ADR), adjusting it based on exponentiality and generating price targets based on that range.
The ADR represents the average range between the highest and lowest prices of a trading instrument during a specific period. It gives you an idea of how much the price typically moves in a day. In this script, we calculate the ADR using Simple Moving Averages (SMA) of the high and low prices over a certain length of time. You can customize this length according to your preference.
To make the ADR smoother and more responsive to recent price changes, we apply an Exponential Moving Average (EMA) to the ADR values. The EMA places more weight on recent data, giving you a more up-to-date measure of the ADR. The length of the EMA is also adjustable.
Once we have the Exponential ADR, we can generate price targets based on it. Price targets are potential levels where the price may reach in the future. We calculate these targets by adding or subtracting a certain multiple of the Exponential ADR from the current closing price. The multiple is determined by a parameter called the "Target Multiplier." You can adjust this value to control the distance of the price targets from the closing price.
In addition to plotting the Exponential ADR as a histogram on the chart, we create a table that displays the price targets. The table shows three bullish (positive) targets and three bearish (negative) targets. The targets are labeled as "Bull Target" or "Bear Target" followed by a number indicating the target's order. For each target, we display the corresponding price level.
To estimate the potential price levels, we used a formula that takes into account the current closing price and a value called the Exponential Average Daily Range (Exponential ADR). The Exponential ADR represents the average range of price movement over a specific period.
To calculate the price targets, we multiplied the Exponential ADR by a user-defined value called the target multiplier. This target multiplier allows traders to control the distance of the price targets from the current price. The resulting value indicates the desired distance from the current price for each target level.
For bullish targets, we added the calculated value to the current closing price. This suggests potential upward movement in the price. On the other hand, for bearish targets, we subtracted the calculated value from the current closing price. This indicates potential downward movement in the price.
By providing multiple target levels, such as level 1, level 2, and level 3, traders can assess different scenarios and potential price outcomes. These target levels help traders identify possible price levels where they might consider taking profit or adjusting their trading positions.
It's important to note that these price targets are not guaranteed to be reached, but they serve as reference points based on historical price behavior and the Exponential ADR. Traders can use them as part of their overall trading strategy and decision-making process.
Adjust the input parameters according to your desired settings, such as the ADR length, EMA length, target multiplier, table position, and table style. The indicator will then calculate and display the Exponential ADR and price targets on the chart, helping you identify potential levels of support and resistance for your trading decisions.
Advanced Trend Detection StrategyThe Advanced Trend Detection Strategy is a sophisticated trading algorithm based on the indicator "Percent Levels From Previous Close".
This strategy is based on calculating the Pearson's correlation coefficient of logarithmic-scale linear regression channels across a range of lengths from 50 to 1000. It then selects the highest value to determine the length for the channel used in the strategy, as well as for the computation of the Simple Moving Average (SMA) that is incorporated into the strategy.
In this methodology, a script is applied to an equity in which multiple length inputs are taken into consideration. For each of these lengths, the slope, average, and intercept are calculated using logarithmic values. Deviation, the Pearson's correlation coefficient, and upper and lower deviations are also computed for each length.
The strategy then selects the length with the highest Pearson's correlation coefficient. This selected length is used in the channel of the strategy and also for the calculation of the SMA. The chosen length is ultimately the one that best fits the logarithmic regression line, as indicated by the highest Pearson's correlation coefficient.
In short, this strategy leverages the power of Pearson's correlation coefficient in a logarithmic scale linear regression framework to identify optimal trend channels across a broad range of lengths, assisting traders in making more informed decisions.
Rate of DeviationThe Rate of Deviation indicator calculates and displays the amount the current price varies above or below the average price over Length bars. A deviation value greater than the base level indicates that the current price is higher than the price average while a deviation less than the base level indicates that the current price is lower than the price average.
StatBox📊 StatBox: A Comprehensive Trading Indicator for RSI, Volume Percent, and ADD 📈💼
Introducing StatBox, the ultimate trading indicator designed to provide traders with a powerful analytical toolset for making informed trading decisions. With StatBox, you gain access to real-time data on Relative Strength Index (RSI), Volume Percent, and ADD (Advance/Decline Differential). This dynamic combination of indicators empowers you to navigate the market with greater precision and confidence. 📊🔍
Key Features of StatBox:
1️⃣ RSI (Relative Strength Index): RSI is a widely recognized momentum oscillator that measures the speed and change of price movements. StatBox displays RSI as a numerical value, ranging from 0 to 100, allowing you to quickly assess whether a security is overbought or oversold. This information is invaluable for identifying potential reversal points and optimizing entry or exit strategies.
2️⃣ Volume Percent: StatBox provides a visual representation of the Volume Percent, which reflects the relative trading volume compared to a specified period. By monitoring volume dynamics, you gain insights into market sentiment and potential price trends. A higher volume percentage often indicates stronger market participation, suggesting increased interest in a particular security.
3️⃣ ADD (Advance/Decline Differential): ADD is a breadth indicator that calculates the difference between advancing (upward moving) and declining (downward moving) securities. StatBox presents ADD as a histogram, enabling you to assess the overall strength or weakness of the market. Positive values indicate bullish sentiment, while negative values suggest bearish sentiment. By tracking ADD, you can identify potential market reversals or confirm existing trends.
With StatBox, you can:
✅ Quickly gauge the overbought or oversold conditions of a security using RSI.
✅ Monitor volume dynamics to assess market sentiment and potential price trends.
✅ Analyze the breadth of the market and identify bullish or bearish signals with ADD.
✅ Make well-informed trading decisions based on a comprehensive view of multiple indicators.
StatBox provides a user-friendly interface, allowing you to seamlessly integrate it into your preferred trading platform or charting software. Its intuitive design and real-time data updates ensure you have the most accurate and up-to-date information at your fingertips.
Upgrade your trading arsenal and unlock the potential of RSI, Volume Percent, and ADD with StatBox. Experience the power of multiple indicators in a single comprehensive tool. Download StatBox today and gain a competitive edge in the dynamic world of trading! 🚀📈
