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
在腳本中搜尋"易方达黄金ETF联接A三点收盘的价格"
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! 🚀📈
Metrics using Alternative Portfolio TheoryLibrary "APT_Metrics"
Portfolio metrics using alternative portfolio theory
metrics(init, cur, start, end, alpha)
Calculates APT metrics
Parameters:
init (float) : Starting Equity (strategy.initial)
cur (float)
start (int) : Start date (UNIX)
end (int) : End Date (UNIX)
alpha (float) : Confidence interval for DaR/CDaR. Defval = 0.05
Returns: Plots table with APT metrics
The metrics are shown in the bottom pane being applied to a buy-and-hold strategy.
PLEASE NOTE: This is the first draft of the library. Some calculations may be incorrect. If you spot any mistakes then please let me know and I will correct them as soon as possible. I am also open to suggestions on how to improve this.
At the moment this only works on the daily timeframe until I can find a way to universally calculate annualized volatility.
Tick Profile HeatmapThis is a market internal TICK heatmap with the intent of displaying areas of price associated to stronger reactions with NYSE TICK (by default).
This code is based off of a variation of a Volume Profile coded originally by colejustice who originally used code from LuxAlgo . The full-width volume bars that colejustice setup were replaced with full-width bars representative of TICK breaking +/- $500, the current cumulative value representing the "heat" is comprised of hlc3 by default but that can be changed. In a future update I may add additional logic here to capture highs and lows in the heatmap specifically, and perhaps additional colors.
As with other traditional profiling studies, this indicators purpose is to visualize correspondence to specific price levels, allowing rapid assessment where the most TICK activity is occurring, and where it hasn't been. This information may provide areas of support and resistance and regions where price may move quickly repeatedly.
All of the same input guidance that colejustice provided is the same for those pre-existing inputs:
Inputs are set up such that you can customize the lookback period, number of rows, and width of rows for most major timeframes individually. Timeframes between those available will use the next lower timeframe settings (e.g., 2m chart will use the 1m settings.)
Zero usage of volume is present in this indicator, only TICK data so please don't confuse it with volume studies.
MACD TrueLevel StrategyThis strategy uses the MACD indicator to determine buy and sell signals. In addition, the strategy employs the use of "TrueLevel Bands," which are essentially envelope bands that are calculated based on the linear regression and standard deviation of the price data over various lengths.
The TrueLevel Bands are calculated for 14 different lengths and are plotted on the chart as lines. The bands are filled with a specified color to make them more visible. The highest upper band and lowest lower band values are stored in variables for easy access.
The user can input the lengths for the TrueLevel Bands and adjust the multiplier for the standard deviation. They can also select the bands they want to use for entry and exit, and enable long and short positions.
The entry conditions for a long position are either a crossover of the MACD line over the signal line or a crossover of the price over the selected entry lower band. The entry conditions for a short position are either a crossunder of the MACD line under the signal line or a crossunder of the price under the selected exit upper band.
The exit conditions for both long and short positions are not specified in the code and are left to the user to define.
Overall, the strategy aims to capture trends by entering long or short positions based on the MACD and TrueLevel Bands, and exiting those positions when the trend reverses.
RSI TrueLevel StrategyThis strategy is a momentum-based strategy that uses the Relative Strength Index (RSI) indicator and a TrueLevel envelope to generate trade signals.
The strategy uses user-defined input parameters to calculate TrueLevel envelopes for 14 different lengths. The TrueLevel envelope is a volatility-based technical indicator that consists of upper and lower bands. The upper band is calculated by adding a multiple of the standard deviation to a linear regression line of the price data, while the lower band is calculated by subtracting a multiple of the standard deviation from the same regression line.
The strategy generates long signals when the RSI crosses above the oversold level or when the price crosses above the selected lower band of the TrueLevel envelope. It generates short signals when the RSI crosses below the overbought level or when the price crosses below the selected upper band of the TrueLevel envelope.
The strategy allows for long and short trades and sets the trade size as a percentage of the account equity. The colors of the bands and fills are also customizable through user-defined input parameters.
In this strategy, the 12th TrueLevel band was chosen due to its ability to capture significant price movements while still providing a reasonable level of noise reduction. The strategy utilizes a total of 14 TrueLevel bands, each with varying lengths. The 12th band, with a length of 2646, strikes a balance between sensitivity to market changes and reducing false signals, making it a suitable choice for this strategy.
RSI Parameters:
In this strategy, the RSI overbought and oversold levels are set at 65 and 40, respectively. These values were chosen to filter out more noise in the market and focus on stronger trends. Traditional RSI overbought and oversold levels are set at 70 and 30, respectively. By raising the oversold level and lowering the overbought level, the strategy aims to identify more significant trend reversals and potential trade opportunities.
Of course, the parameters can be adjusted to suit individual preferences.
[TT] Sectors Dist % From MA- The script shows the distance in percentages from the 200 MA (or any other MA period) , for the 11 SP500 sectors.
- It works based on the current time frames.
Could be useful when working with mean reversion strategies to detect extremes zones and overbought/oversold conditions in the given sectors compared others.
BUY/SELL + ADVANCE DECLINEThis script is a custom trading view indicator that helps to identify potential buy and sell signals based on the RSI (Relative Strength Index) and SMA (Simple Moving Average) indicators. The script also identifies potential reversals using a combination of RSI and price action. It plots buy, sell, and reversal signals on the chart along with an SMA line. Additionally, it provides alerts based on the buy, sell, and reversal conditions.
Changes made to the original script:
Fixed the undeclared identifier 'c' error by calculating the difference between the current closing price and the previous closing price: c = close - close .
Added an "ADD Value Floating Label" to the chart. The label shows the difference between the current and previous closing prices (ADD value) along with a "Bullish" or "Bearish" indicator based on the value of 'c'. The label is positioned at the top right of the visible chart area and remains static.
Here's a summary of the major components of the script:
Input settings: Define the input parameters for RSI and SMA.
Calculation of RSI and SMA: Compute the RSI and SMA values based on the input parameters.
Color definitions: Define colors for different conditions and levels.
Condition definitions: Define various conditions for buy, sell, reversal, and other criteria.
Buy and sell conditions: Determine buy and sell signals based on RSI, SMA, and price action.
Reversal conditions: Identify potential reversals using RSI and price action.
Plot signals: Display buy, sell, and reversal signals on the chart.
Bar colors: Color the bars based on the identified signals.
Plot SMA: Display the SMA line on the chart.
Alert conditions: Set up alerts for buy, sell, and reversal conditions.
ADD Value Floating Label: Add a label to the chart showing the ADD value and a "Bullish" or "Bearish" indicator.
No Code SignalsNo Code Signals is an intuitive user interface for users to generate their own signals based on indicators they already have applied to their chart.
This indicator makes use of the new input.source() limits for importing data from external sources (indicators) into 1 indicator.
You are now able to import ANY number of sources from up to 10 different indicators.
Features:
- Import up to 10 unique values from up to 10 different indicators already on your chart!
- Compare those values against other imported indicator values, or chart ohlc values.
- Option to use a defined level instead of an active source.
- 5 Signal Options (Currently)
- Alerts, Each signal has its own alert condition.
- Labeled Signals, to tell which signal is which.
Potential Future Plans:
- More Signals & Analysis Options
- Possibly more imports
- Combining 2 (or more) signals into 1
Here is a Screenshot of a chart with signals, and the Interface creating the signals.
Enjoy!
52 Week High/Low FibonacciThe primary purpose of this indicator is to calculate and plot the 52-week high and low prices along with the Fibonacci retracement levels on the price chart. Fibonacci levels are commonly used in trading to identify potential support, resistance, and price reversal points.
First, the script initializes the Fibonacci levels and their corresponding colors, which will be used to plot the levels on the chart. Next, it calculates the 52-week high and low prices by finding the highest and lowest prices over the last 252 trading days, approximately equivalent to one year. Then, it identifies the overall trend direction by comparing the number of bars since the highest high and the lowest low. If the highest high is more recent, the trend is considered downwards; if the lowest low is more recent, the trend is upwards.
The script then plots the Fibonacci retracement levels on the chart, using horizontal lines at the respective price levels. It also creates labels for each level, displaying the percentage and the price value. Additionally, it draws a line connecting the 52-week high and low prices, providing a visual representation of the price range during the 52-week period.
Pros of this indicator include:
-Automatic calculation and plotting of Fibonacci levels, saving time for traders
-Clear trend identification based on 52-week high and low prices
-Visually appealing and easy-to-read chart representation with color-coded levels
-Provides insight into potential price reversal areas based on widely used Fibonacci levels
Cons of this indicator include:
-Only works on daily timeframes, limiting its usefulness for intraday and weekly traders
-Assumes that the trend will continue in the same direction, which may not always be accurate in real-world markets
-Does not provide explicit buy or sell signals, leaving the trading decision-making process up to the trader
-Solely relies on Fibonacci levels, which may not always be accurate; it is recommended to use other technical indicators or strategies alongside this indicator for a comprehensive trading approach
In conclusion, the '52 Week High Low Fibonacci' indicator is a valuable tool for traders interested in using Fibonacci levels for identifying potential price reversal points. By automatically calculating and plotting these levels based on 52-week high and low prices, the indicator provides a clear, color-coded visual aid, which can be especially helpful for traders who base their strategies on these levels.
However, it's worth noting that this indicator is limited to daily timeframes and doesn't provide explicit buy or sell signals, requiring traders to incorporate their own analysis and judgement in their decision-making process. The indicator also operates on the assumption of trend continuation, which may not always hold true.
While it's a beneficial tool, relying solely on this indicator for trading decisions may not be advisable. It's best used in conjunction with other indicators and trading strategies, providing a more balanced and comprehensive approach to trading in the financial markets. As always, risk management should be a key part of any trading strategy.
**YOUR INSIGHTFUL FEEDBACK OR SUGGESTIONS FOR REVISIONS TO THIS CODE ARE HIGHLY APPRECIATED. PLEASE FEEL FREE TO SHARE YOUR THOUGHTS TO FOSTER ITS CONTINUAL IMPROVEMENT**
Top12/Bottom88 Weighted Ratio I multiplied the price of each of the top QQQ holdings by their percentage weight, and the bottom 88 holdings for a total of 100. I divide the top 12 weighted price by the bottom 88 weighted price. So I can see when money is flowing in and out of the megacaps. It needs to be updated every quarter, which I may need to do now....
Golden ZoneIntroducing the "Golden Zone" indicator, a powerful tool that simplifies the Fibonacci indicator by creating a clear Golden Zone to identify potential future price movements. The Golden Zone is a supply or demand zone that corresponds to the 61.8% and 50% Fibonacci retracement levels. These levels are important because they often mark zones where the price reacts, making it an essential area for traders to watch.
The script plots the Fibonacci levels in the background, enabling traders to identify potential support and resistance levels quickly. The Golden Zone is highlighted with a yellow filled area, making it easy to spot on the chart. Traders use this zone to identify areas where the stock price may react, either bouncing off the support level or encountering resistance at the resistance level.
For example, if a stock price is moving up and reaches the Golden Zone, a trader may look for signs of resistance and consider selling the stock if the price begins to move back down. Conversely, if a stock price is moving down and reaches the Golden Zone, a trader may look for signs of support and consider buying the stock if the price begins to move back up.
The "Golden Zone" indicator is highly versatile and can be used in all markets, whether you are a swing trader or a day trader. It can be combined with other strategies, such as an EMA crossover strategy or price action, or as an area of confluence.
In summary, the "Golden Zone" indicator is a must-have tool for traders looking to identify potential price movements and locate key support and resistance levels. Its user-friendly inputs and clear display make it a valuable addition to any trading arsenal.
So, the "Golden Zone" indicator is like a magic tool that helps people who trade in the stock market find valuable things to buy or sell. And with its ability to identify key support and resistance levels, it can help traders make better-informed decisions when buying or selling stocks.
I hope you like it!
Tape (Time and Sales)OVERVIEW
This indicator is a synthesized "Tape" (aka. Time and Sales) from real time market data. It's specifically designed to be performant, expediting trading insights and decisions.
The table contains color-coded price action, volume size, and a timestamp data for each chart update. Because chart updates are independent of exchange orders, 1 chart update may combine more than 1 exchange and/or order. Even so, you're able to see very small and fast order flow changes, made possible by measuring real time volume differentials, and correlating them with price action.
Real time volume differentials are required for this indicator to be most useful. This is not ideal for historical analysis or TradingViews Replay feature.
INPUTS
You can can configure:
Table Position and Text Size
The Timestamp (visibility, format, timezone)
The number of lines to print
Volume Parameters (minimum size, large sizes, decimal precision)
Highlighting and Enlarging large sized prints
All the colors
DEV NOTES
This script illustrates:
The complimentary nature of loops and arrays
A method for iterative table management
Zero Lag Moving Average with Gaussian weightsIntroduction
The Zero Lag Moving Average (ZLMA) is a powerful technical indicator that aims to eliminate the lag inherent in traditional moving averages. This post provides a comprehensive exploration of the ZLMA with Gaussian Weights (GWMA) indicator, discussing the concepts, the calculations, and its application in trading.
Concepts
Zero Lag Moving Average (ZLMA): A ZLMA is an advanced moving average designed to reduce the lag in price movements associated with conventional moving averages. This reduction in lag enables traders to make more informed decisions based on the most recent price data.
Gaussian Weights: Gaussian weights are derived from the Gaussian function, which is a mathematical function used to calculate probabilities in a normal distribution. The Gaussian function is smooth, symmetric, and has a bell-shaped curve. In this context, Gaussian weights are used to calculate the weighted average of a series of data points.
Why Gaussian Weights are Beneficial
Gaussian Weights offer several advantages in comparison to traditional moving averages. One of the main reasons for using Gaussian Weights is to address the issue of lag, which is commonly associated with simple and exponential moving averages. By reducing lag, traders can make more informed decisions based on up-to-date information.
Another advantage of Gaussian Weights is their mathematical foundation, which is rooted in the Gaussian function. This function describes the normal distribution in probability theory and statistics. The smooth and symmetric bell-shaped curve of Gaussian Weights enables a more refined approach to handling data points, resulting in a more responsive and accurate moving average.
While exponential moving averages (EMAs) also assign more weight to recent data points, they can still exhibit some lag. Gaussian Weights, on the other hand, offer a smoother and more adaptive solution to different market conditions. By adjusting the smoothing period, traders can tailor the Gaussian Weights to their specific needs, making them a versatile tool for various trading strategies.
In summary, Gaussian Weights provide a valuable alternative to traditional moving averages due to their ability to reduce lag, their strong mathematical foundation, and their adaptability to different market conditions. These benefits make Gaussian Weights a worthwhile consideration for traders looking to enhance their trading strategies.
Calculations
The ZLMA with GWMA consists of two main calculations:
Gaussian Weight Calculation: The Gaussian weight for a given 'k' and 'smooth_per' is calculated using the standard deviation (sigma) and the exponent part of the Gaussian function.
Zero-Lag GWMA Calculation: The zero-lag GWMA is calculated using a source buffer, a Gaussian weighted moving average (gwma1), and an output array. The source buffer stores the input data, the gwma1 array stores the first Gaussian weighted moving average, and the output array stores the final zero-lag moving average.
Application in Trading
The ZLMA with GWMA indicator can be used to identify trends and potential entry/exit points in trading:
Trend Identification: When the ZLMA is above the price, it indicates a bearish trend, and when it is below the price, it indicates a bullish trend.
Entry/Exit Points: Traders can use crossovers between the ZLMA and price to identify potential entry and exit points. A long position could be taken when the price crosses above the ZLMA, and a short position could be taken when the price crosses below the ZLMA.
Conclusion
The Zero Lag Moving Average with Gaussian Weights is a powerful and versatile indicator that can be used in various trading strategies. By minimizing the lag associated with traditional moving averages, the ZLMA with GWMA provides traders with more accurate and timely information about price trends and potential trade opportunities.
