Sector Rotation Hedging With Volatility Index [TradeDots]The "Sector Rotation Hedging Strategy With Volatility Index" is a comprehensive trading indicator developed to optimally leverage the S&P500 volatility index. It is designed to switch between distinct ETF sectors, strategically hedging to moderate risk exposure during harsh market volatility.
HOW DOES IT WORK
The core of this indicator is grounded on the S&P500 volatility index (VIX) close price and its 60-day moving average. This serves to determine whether the prevailing market volatility is above or below the quarterly average.
In periods of elevated market volatility, risk exposure escalates significantly. Traders retaining stocks in sectors with disproportionately high volatility face increased vulnerability to negative returns. To tackle this, our indicator employs a two-pronged approach utilizing two sequential candlestick close prices to confirm if volatility surpasses the average value.
Upon confirming above-average volatility, a hedging table is deployed to spotlight ETFs with low volatility, such as the Utilities Select Sector SPDR Fund (XLU), to derisk the overall portfolio.
Conversely, in low-volatility conditions, sectors yielding higher returns like the Technology Select Sector SPDR Fund (XLK) are preferred. The hedging table is utilized to earmark high-return sector ETFs.
Thus, during highly volatile market periods, the strategy recommends enhancing portfolio allocation to low-volatility ETFs. During low-volatility windows, the portfolio is calibrated towards high-volatility ETFs for heightened returns.
IMPORTANT CONSIDERATION
In real trading, additional considerations encompassing trading commissions, management fees, and ancillary rotation costs should be factored in. False signals may arise, potentially leading to losses from these fees.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Forecasting
Fair ValueThis indicator is designed to provide a valuation perspective based on a specified length and deviations from a base value. This code calculates fair value levels relative to a chosen source (typically closing prices) using simple moving averages (SMA) or exponential moving averages (EMA). Please note that this is purely educational and should not be considered financial advice.
Key Features:
1. Valuation Calculation: The indicator computes a base value using either SMA or EMA, providing a reference point for fair value.
2. Deviation Levels: Additional levels of valuation are defined as deviations from the base value, indicating potential overvalued or undervalued conditions.
3. Currency-Specific Display: It displays valuation levels in different currency symbols based on the asset's trading currency.
4. Visual Representation: The indicator plots fair value lines and shades areas to highlight potential deviations.
5. Line Projection: A projection line shows potential future movement based on the calculated slope. This feature forecasts future price movement using a linear regression line's slope, dynamically projecting the trend forward. It provides traders with valuable insight into potential future price behavior. The implementation involves complex mathematical computations to determine the slope and iterative drawing of projected segments.
Educational Purpose: This indicator is for educational purposes only. It does not guarantee accuracy or suitability for trading decisions.
Please use caution and consider consulting a financial professional before making any investment decisions based on this indicator. Keep in mind that market conditions can change rapidly, and historical performance may not predict future results.
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the TradingView platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Symbol CorrelationThe "Symbol Correlation" indicator calculates and displays the correlation between the chosen symbol's price and another selected source over a specified period. It also includes a moving average (SMA) of this correlation to provide a smoothed view of the relationship.
Why SMA and Table Display ?
The inclusion of SMA (Simple Moving Average) with adjustable length (SMA Length) enhances the indicator's utility by smoothing out short-term fluctuations in correlation, allowing for clearer trend identification. The SMA helps to visualize the underlying trend in correlation, making it easier to spot changes and patterns over time.
The table display of the correlation SMA value offers a concise summary of this trend. By showcasing the current correlation SMA alongside its historical values, traders can quickly gauge the relationship's strength relative to previous periods.
Interpreting the Indicator:
1. Correlation Values: The primary plot shows the raw correlation values between the symbol's price and the specified source. A value of 1 indicates a perfect positive correlation, -1 signifies a perfect negative correlation, and 0 suggests no linear relationship.
2. Correlation SMA: The SMA line represents the average correlation over a defined period (SMA Length). Rising SMA values indicate strengthening correlation trends, while declining values suggest weakening correlations.
3. Choosing SMA Length: Traders can adjust the SMA Length parameter to tailor the moving average to their specific analysis horizon. Shorter SMA lengths react quickly to price changes but may be more volatile, while longer SMA lengths smooth out noise but respond slower to recent changes.
In summary, the "Symbol Correlation" indicator is a valuable tool for assessing the evolving relationship between a symbol's price and an external source. Its use of SMA and tabular presentation facilitates a nuanced understanding of correlation trends, aiding traders in making informed decisions based on market dynamics.
Previous Candle + Inside/OutsideThe script uses the previous candle of the current timeframe to assess the state of the current candle.
1. Previous candle high/low and midpoint are displayed
2. Highlights current bar if INSIDE previous candle
3. Highlights current bar if POTENTIAL OUTSIDE bar. This condition uses the logic that if the previous high/low has been swept and price then reaches previous bar 50%, then an OUTSIDE bar is possible.
4. If current candle breaks previous high/low, a label is added to identify.
5. If above condition is true and current candle color is opposite of previous, then label is highlighted to show possible bull/bear condition.
6. If current candle live price is below previous midpoint, a BEAR label is shown
7. If current candle live price is above previous midpoint, a BULL label is shown
I personally use the indicator on Daily/Weekly/Monthly charts to help with my overall market assessment. However users may find their own use for the indicator...or modify it to their own preferences.
As ever, the indicator should only be used with live trading accounts after thorough backtesting using a large data range.
London Killzone + Deviations[MK]For traders that use the London Killzone session high/low to project possible take profit targets.
The indicator will determine the current day London killzone high and low range and draw a range box to the right of the last candle on the chart. Drawing to the right of the chart keeps the workspace cleaner.
The high/low range is then used to project Standard Deviation levels above and below the London range.
Levels projected are +/- 1, 2, 2.5, 3, 4.
Users of the script should conduct proper backtesting using a large data range before applying to live accounts.
[Sharpe projection SGM]Dynamic Support and Resistance: Traces adjustable support and resistance lines based on historical prices, signaling new market barriers.
Price Projections and Volatility: Calculates future price projections using moving averages and plots annualized standard deviation-based volatility bands to anticipate price dispersion.
Intuitive Coloring: Colors between support and resistance lines show up or down trends, making it easy to analyze quickly.
Analytics Dashboard: Displays key metrics such as the Sharpe Ratio, which measures average ROI adjusted for asset volatility
Volatility Management for Options Trading: The script helps evaluate strike prices and strategies for options, based on support and resistance levels and projected volatility.
Importance of Diversification: It is necessary to diversify investments to reduce risks and stabilize returns.
Disclaimer on Past Performance: Past performance does not guarantee future results, projections should be supplemented with other analyses.
The script settings can be adjusted according to the specific needs of each user.
The mean and standard deviation are two fundamental statistical concepts often represented in a Gaussian curve, or normal distribution. Here's a quick little lesson on these concepts:
Average
The mean (or arithmetic mean) is the result of the sum of all values in a data set divided by the total number of values. In a data distribution, it represents the center of gravity of the data points.
Standard Deviation
The standard deviation measures the dispersion of the data relative to its mean. A low standard deviation indicates that the data is clustered near the mean, while a high standard deviation shows that it is more spread out.
Gaussian curve
The Gaussian curve or normal distribution is a graphical representation showing the probability of distribution of data. It has the shape of a symmetrical bell centered on the middle. The width of the curve is determined by the standard deviation.
68-95-99.7 rule (rule of thumb): Approximately 68% of the data is within one standard deviation of the mean, 95% is within two standard deviations, and 99.7% is within three standard deviations.
In statistics, understanding the mean and standard deviation allows you to infer a lot about the nature of the data and its trends, and the Gaussian curve provides an intuitive visualization of this information.
In finance, it is crucial to remember that data dispersion can be more random and unpredictable than traditional statistical models like the normal distribution suggest. Financial markets are often affected by unforeseen events or changes in investor behavior, which can result in return distributions with wider standard deviations or non-symmetrical distributions.
Tweet/X Post Timestamp - By LeviathanThis script allows you to generate visual timestamps of X/Twitter posts directly on your chart, highlighting the precise moment an X post/tweet was made. All you have to do is copy and paste the post URL.
◽️ Use Cases:
- News Trading: Traders can use this indicator to visually align market price actions with news or announcements made on X (formerly Twitter), aiding in the analysis of news impact on market volatility.
- Behavioral Analysis: Traders studying the influence of social media on price can use the timestamps to track correlations between specific posts and market reactions.
- Proof of Predictions: Traders can use this indicator to timestamp their market forecasts shared on X (formerly Twitter), providing a visual record of their predictions relative to actual market movements. This feature allows for transparent verification of the timing and accuracy of their analyses
◽️ Process of Timestamp Calculation
The calculation of the timestamp from a tweet ID involves the following steps:
Extracting the Post ID:
The script first parses the input URL provided by the user to extract the unique ID of the tweet or X post. This ID is embedded in the URL and is crucial for determining the exact posting time.
Calculating the Timestamp:
The post ID undergoes a mathematical transformation known as a right shift by 22 bits. This operation aligns the ID's timestamp to a base reference time used by the platform.
Adding Base Offset:
The result from the right shift is then added to a base offset timestamp (1288834974657 ms, the epoch used by Twitter/X). This converts the processed ID into a UNIX timestamp reflecting the exact moment the post was made.
Date-Time Conversion:
The UNIX timestamp is further broken down into conventional date and time components (year, month, day, hour, minute, second) using calculations that account for leap years and varying days per month.
Label Placement:
Based on user settings, labels displaying the timestamp, username, and other optional information such as price changes or pivot points are dynamically placed on the chart at the bar corresponding to the timestamp.
Yield Curve SpaghettiDisplays the difference in yield between multiple bond pairs for a given country.
Currently supports US, DE, and GB bonds
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
Mag7 IndexThis is an indicator index based on cumulative market value of the Magnificent 7 (AAPL, MSFT, NVDA, TSLA, META, AMZN, GOOG). Such an indicator for the famous Mag 7, against which your main security can be benchmarked, was missing from the TradingView user library.
The index bar values are calculated by taking the weighted average of the 7 stocks, relative to their market cap. Explicitly, we are multiplying each bar period's total outstanding stock amount by the OHLC of that period for each stock and dividing that value by the combined sum of outstanding stock for the 7 corporations. OHLC is taken for the extended trading session.
The index dynamically adjusts with respect to the chosen main security and the bars/line visible in the chart window; that is, the first close value is normalized to the main security's first close value. It provides recalculation of the performance in that chart window as you scroll (this isn't apparent in the demo chart above this description).
It can be useful for checking market breadth, or benchmarking price performance of the individual stock components that comprise the Magnificent 7. I prefer comparing the indicator to the Nasdaq Composite Index (IXIC) or S&P500 (SPX), but of course you can make comparisons to any security or commodity.
Settings Input Options:
1) Bar vs. Line - view as OHLC colored bars or line chart. Line chart color based on close above or below the previous period close as green or red line respectively.
2) % vs Regular - the final value for the window period as % return for that window or index value
3) Turn on/off - bottom right tile displaying window-period performance
Inspired by the simpler NQ 7 Index script by @RaenonX but with normalization to main security at start of window and additional settings input options.
Please provide feedback for additional features, e.g., if a regular/extended session option is useful.
US CPIIntroducing "US CPI" Indicator
The "US CPI" indicator, based on the Consumer Price Index (CPI) of the United States, is a valuable tool for analyzing inflation trends in the U.S. economy. This indicator is derived from official data provided by the U.S. Bureau of Labor Statistics (BLS) and is widely recognized as a key measure of inflationary pressures.
What is CPI?
The Consumer Price Index (CPI) is a measure that examines the average change in prices paid by consumers for a basket of goods and services over time. It is an essential economic indicator used to gauge inflationary trends and assess changes in the cost of living.
How is "US CPI" Calculated?
The "US CPI" indicator in this script retrieves CPI data from the Federal Reserve Economic Data (FRED) using the FRED:CPIAUCSL symbol. It calculates the rate of change in CPI over a specified period (typically 12 months) and applies technical analysis tools like moving averages (SMA and EMA) for trend analysis and smoothing.
Why Use "US CPI" Indicator?
1. Inflation Analysis: Monitoring CPI trends provides insights into the rate of inflation, which is crucial for understanding the overall economic health and potential impact on monetary policy.
2. Policy Implications: Changes in CPI influence decisions by policymakers, central banks, and investors regarding interest rates, fiscal policies, and asset allocation.
3. Market Sentiment: CPI data often impacts market sentiment, influencing trading strategies across various asset classes including currencies, bonds, and equities.
Key Features:
1. Customizable Smoothing: The indicator allows users to apply exponential moving average (EMA) smoothing to CPI data for clearer trend identification.
2. Visual Representation: The plotted line visually represents the inflation rate based on CPI data, helping traders and analysts assess inflationary pressures at a glance.
Sources and Data Integrity:
The CPI data used in this indicator is sourced directly from FRED, ensuring reliability and accuracy. The script incorporates robust security protocols to handle data requests and maintain data integrity in a trading environment.
In conclusion, the "US CPI" indicator offers a comprehensive view of inflation dynamics in the U.S. economy, providing traders, economists, and policymakers with valuable insights for informed decision-making and risk management.
Disclaimer: This indicator and accompanying analysis are for informational purposes only and should not be construed as financial advice. Users are encouraged to conduct their own research and consult with professional advisors before making investment decisions.
Evolving RThe "Evolving R" script is a script that allows to calculate a dynamic reward-to-risk ratio at any given point of time during the trade. Its fundamentals are based on Tom Dante's concept of an evolving reward-to-risk. The script requires a user to input their preferred stop loss price and the target price for a specific asset, and calculates the ratio between two differences: (a) the absolute difference between the target price and the current price and (b) the absolute difference between the stop loss price and the current price.
The output of the script displays the ratio discussed as a value called "Evolving R" in the table. In order to use it successfully, the user of the script has to input:
(a) Stop loss price for the asset
(b) Target price for the asset
Theoretically, as long as the evolving R value holds above or equal to 0.25, the trade is worth holding. However, if the evolving R value drops below 0.25, the table turns red and signifies that such a trade possesses more risk than there is a reward remaining: this alerts the user to possibly take profits prematurely without risking their unrealized gains for a minor amount of additional gain.
The graphics of the script are represented by green and red areas: the green area indicates the area between the current price and the target price, while the red area shows the distance between the current price and the stop loss price. This visual representation allows users to understand the relative reward-to-risk ratio graphically in addition to the given evolving R value output.
The script is used for any type of trading: whether trend-trading or in a ranging market, it doesn't suggest a user which market conditions they should use.
[KVA] ICT Dealing rangesNaive aproach of Dynamic Detection of Dealing Ranges:
The script dynamically identifies dealing ranges based on sequences of upward or downward price movements. It uses arrays to track the highest highs and lowest lows after detecting two consecutive up or down bars, a fundamental step towards understanding market structure and potential shifts in momentum.
ICT Concept: Order Blocks & Fair Value Gaps. This aspect can be linked to the identification of order blocks (bullish or bearish) and fair value gaps. Order blocks are essentially the last bearish or bullish candle before a significant price move, which this script could approximate by identifying the highs and lows of potential reversal zones.
Red and Green Ranges for Bullish and Bearish Movements:
The script separates these movements into red (bearish) and green (bullish) ranges, effectively categorizing potential areas of selling and buying pressure.
ICT Concept: Liquidity Pools. Red ranges could be indicative of areas where selling might occur, potentially leading to liquidity pools below these ranges. Conversely, green ranges might indicate potential buying pressure, with liquidity pools above. These areas are critical for ICT traders, as they often represent zones where price may return to "hunt" for liquidity.
Horizontal Lines for High and Low Points:
The indicator draws horizontal lines at the high and low points of these ranges, offering visual cues for significant levels.
ICT Concept: Breaker Blocks & Mitigation Sequences. The high and low points of these ranges can be seen as potential breaker blocks or areas for future mitigation sequences. In ICT terms, breaker blocks are areas where institutional orders have overwhelmed retail stop clusters, creating potential entry points for trend continuation or reversal. The high and low points marked by the indicator could serve as references for these sequences, where price might return to retest these levels.
Customizability and Historical Depth:
With inputs like rangePlot and maxBarsBack, the indicator allows for customization of the number of ranges to display and how far back in the chart history it looks to identify these ranges. This flexibility is crucial for tailoring the analysis to different trading strategies and timeframes.
ICT Concept: Market Structure Analysis. The ability to adjust the depth and number of ranges plotted caters to a detailed market structure analysis, an essential component of ICT methodology. Traders can adjust these parameters to better understand the distribution of buying and selling pressure over time and how actions have shaped price movements.
ATR Price Targets w/POC
ATR Price Targets with Point of Control (POC):
This script is designed to help traders identify key price target levels based on configurable multipliers of the the Average True Range (ATR) and the volume based Point of Control (POC). It is intended for intraday traders looking to capture significant price movements.
Features:
ATR Price Targets: The script calculates three levels of price targets above and below the first bar of the day, based on the ATR of the last 22 days (assuming 5-minute candles). These targets are adjustable through the settings, allowing traders to set their own ATR multipliers.
Point of Control (POC): The POC is determined as the price level of the highest volume bar since the start time, providing an indication of the most traded price within the specified period.
Customizable Start Time: Traders can set their desired start time for the calculation of price targets and POC, allowing for flexibility in aligning the indicator with their trading strategy.
Plot Lines: The ATR price targets are plotted as lines for easy visualization on the chart.
Usage:
The ATR price targets can be used as potential take-profit or stop-loss levels.
The POC can serve as a key level for assessing market sentiment and potential reversals.
Traders can adjust the ATR multipliers and start time based on their specific trading style and market conditions.
Settings:
ATR Price Targets 1, 2, 3: Adjust the multipliers for the ATR price targets. By default, these are set to 1*ATR for T1+/T1-, 3*ATR for T2+/T2- and ATR*6 for T3+/T3-. Adjust with caution as the price targets found in defaults have proven to be more accurate over intraday cycles for volatile stocks.
Start Hour & Start Minute: Set the starting hour and minute for the calculations. By default, these are set to the opening 5 minute intraday bar, but can also be set to the opening bar of pre-market hours.
Buffett IndicatorThis is an open-source version of the Buffett indicator. The old version was code-protected and broken, so I created another version.
It's computed simply as the entire SPX 500 capitalization divided by the US GDP. Since TradingView does not have data for the SPX 500 capitalization, I used quarterly values of SPX devisors as a proxy.
I tried to create another version of the Buffett indicator for other countries/indexes, but I can't find the data. If you can help me find data for index divisors, I can add more choices to this indicator.
It's interesting to see how this indicator's behavior has changed in the last few years. Levels that looked crazy are not so crazy anymore.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Murrey Math
The Murrey Math indicator is a set of horizontal price levels, calculated from an algorithm developed by stock trader T.J. Murray.
The main concept behind Murrey Math is that prices tend to react and rotate at specific price levels. These levels are calculated by dividing the price range into fixed segments called "ranges", usually using a number of 8, 16, 32, 64, 128 or 256.
Murrey Math levels are calculated as follows:
1. A particular price range is taken, for example, 128.
2. Divide the current price by the range (128 in this example).
3. The result is rounded to the nearest whole number.
4. Multiply that whole number by the original range (128).
This results in the Murrey Math level closest to the current price. More Murrey levels are calculated and drawn by adding and subtracting multiples of the range to the initially calculated level.
Traders use Murrey Math levels as areas of possible support and resistance as it is believed that prices tend to react and pivot at these levels. They are also used to identify price patterns and possible entry and exit points in trading.
The Murrey Math indicator itself simply calculates and draws these horizontal levels on the price chart, allowing traders to easily visualize them and use them in their technical analysis.
HOW TO USE THIS INDICATOR?
To use the Murrey Math indicator effectively, here are some tips:
1. Choose the appropriate Murrey Math range : The Murrey Math range input (128 by default in the provided code) determines the spacing between the levels. Common ranges used are 8, 16, 32, 64, 128, and 256. A smaller range will give you more levels, while a larger range will give you fewer levels. Choose a range that suits the volatility and trading timeframe you're working with.
2. Identify potential support and resistance levels: The horizontal lines drawn by the indicator represent potential support and resistance levels based on the Murrey Math calculation. Prices often react or reverse at these levels, so they can be used to spot areas of interest for entries and exits.
3. Look for price reactions at the levels: Watch for price action like rejections, bounces, or breakouts at the Murrey Math levels. These reactions can signal potential trend continuation or reversal setups.
4. Trail stop-loss orders: You can place stop-loss orders just below/above the nearest Murrey Math level to manage risk if the price moves against your trade.
5. Set targets at future levels: Project potential profit targets by looking at upcoming Murrey Math levels in the direction of the trend.
7. Adjust range as needed: If prices are consistently breaking through levels without reacting, try adjusting the range input to a different value to see if it provides better levels.
In which asset can this indicator perform better?
The Murrey Math indicator can potentially perform well on any liquid financial asset that exhibits some degree of mean-reversion or trading range behavior. However, it may be more suitable for certain asset classes or trading timeframes than others.
Here are some assets and scenarios where the Murrey Math indicator can potentially perform better:
1. Forex Markets: The foreign exchange market is known for its ranging and mean-reverting nature, especially on higher timeframes like the daily or weekly charts. The Murrey Math levels can help identify potential support and resistance levels within these trading ranges.
2. Futures Markets: Futures contracts, such as those for commodities (e.g., crude oil, gold, etc.) or equity indices, often exhibit trading ranges and mean-reversion trends. The Murrey Math indicator can be useful in identifying potential turning points within these ranges.
3. Stocks with Range-bound Behavior: Some stocks, particularly those of large-cap companies, can trade within well-defined ranges for extended periods. The Murrey Math levels can help identify the boundaries of these ranges and potential reversal points.
4. I ntraday Trading: The Murrey Math indicator may be more effective on lower timeframes (e.g., 1-hour, 30-minute, 15-minute) for intraday trading, as prices tend to respect support and resistance levels more closely within shorter time periods.
5. Trending Markets: While the Murrey Math indicator is primarily designed for range-bound markets, it can also be used in trending markets to identify potential pullback or continuation levels.
Momentum Ghost Machine [ChartPrime]Momentum Ghost Machine (ChartPrime) is designed to be the next generation in momentum/rate of change analysis. This indicator utilizes the properties of one of our favorite filters to create a more accurate and stable momentum oscillator by using a high quality filtered delayed signal to do the momentum comparison.
Traditional momentum/roc uses the raw price data to compare current price to previous price to generate a directional oscillator. This leaves the oscillator prone to false readings and noisy outputs that leave traders unsure of the real likelihood of a future movement. One way to mitigate this issue would be to use some sort of moving average. Unfortunately, this can only go so far because simple moving average algorithms result in a poor reconstruction of the actual shape of the underlying signal.
The windowed sinc low pass filter is a linear phase filter, meaning that it doesn't change the shape or size of the original signal when applied. This results in a faithful reconstruction of the original signal, but without the "high frequency noise". Just like any filter, the process of applying it requires that we have "future" samples resulting in a time delay for real time applications. Fortunately this is a great thing in the context of a momentum oscillator because we need some representation of past price data to compare the current price data to. By using an ideal low pass filter to generate this delayed signal we can super charge the momentum oscillator and fix the majority of issues its predecessors had.
This indicator has a few extra features that other momentum/roc indicators dont have. One major yet simple improvement is the inclusion of a moving average to help gauge the rate of change of this indicator. Since we included a moving average, we thought it would only be appropriate to add a histogram to help visualize the relationship between the signal and its average. To go further with this we have also included linear extrapolation to further help you predict the momentum and direction of this oscillator. Included with this extrapolation we have also added the histogram in the extrapolation to further enhance its visual interpretation. Finally, the inclusion of a candle coloring feature really drives how the utility of the Momentum Machine .
There are three distinct options when using the candle coloring feature: Direct, MA, and Both. With direct the candles will be colored based on the indicators direction and polarity. When it is above zero and moving up, it displays a green color. When it is above zero and moving down it will display a light green color. Conversely, when the indicator is below zero and moving down it displays a red color, and when it it moving up and below zero it will display a light red color. MA coloring will color the candles just like a MACD. If the signal is above its MA and moving up it will display a green color, and when it is above its MA and moving down it will display a light green color.
When the signal is below its MA and moving down it will display a red color, and when its below its ma and moving up it will display a light red color. Both combines the two into a single color scheme providing you with the best of both worlds. If the indicator is above zero it will display the MA colors with a slight twist. When the indicator is moving down and is below its MA it will display a lighter color than before, and when it is below zero and is above its MA it will display a darker color color.
Length of 50 with a smoothing of 100
Length of 50 with a smoothing of 25
By default, the indicator is set to a momentum length of 50, with a post smoothing of 2. We have chosen the longer period for the momentum length to highlight the performance of this indicator compared to its ancestors. A major point to consider with this indicator is that you can only achieve so much smoothing for a chosen delay. This is because more data is required to produce a smoother signal at a specified length. Once you have selected your desired momentum length you can then select your desired momentum smoothing . This is made possible by the use of the windowed sinc low pass algorithm because it includes a frequency cutoff argument. This means that you can have as little or as much smoothing as you please without impacting the period of the indicator. In the provided examples above this paragraph is a visual representation of what is going on under the hood of this indicator. The blue line is the filtered signal being compared to the current closing price. As you can see, the filtered signal is very smooth and accurately represents the underlying price action without noise.
We hope that users can find the same utility as we did in this indicator and that it levels up your analysis utilizing the momentum oscillator or rate of change.
Enjoy
Price Action Fractal Forecasts [AlgoAlpha]🔮 Price Action Fractal Forecasts - Unleash the Power of Historical Patterns! 🌌✨
Dive into the future with AlgoAlpha's Price Action Fractal Forecasts ! This innovative indicator utilizes the mesmerizing complexity of fractals to predict future price movements, offering traders a unique edge in the market. By analyzing historical price action and identifying repeating patterns, this tool forecasts future price trends, providing visually engaging and actionable insights.
Key Features:
🔄 Flexible Data Series Selection: Choose your preferred data series for precise analysis.
🕰 Flexible Training and Reference Data Windows: Customize the length of training data and reference periods to match your trading style.
📈 Custom Forecast Length: Adjust the forecast horizon to suit your strategic objectives.
🌈 Customizable Visual Elements: Tailor the colors of forecast deviation cones, data reference areas, and more for optimal chart readability.
🔄 Anticipatory and Repetitive Forecast Modes: Select between anticipating future trends or identifying repetitive patterns for forecasts.
🔎 Enhanced Similarity Search: Leverages correlation metrics to find the most similar historical data segments.
📊 Forecast Deviation Cone: Visualize potential price range deviations with adjustable multipliers.
🚀 Quick Guide to Maximizing Your Trading with Price Action Fractal Forecasts:
🛠 Add the Indicator: Search for "Price Action Fractal Forecasts" in TradingView's Indicators & Strategies. Customize settings according to your trading strategy.
📊 Strategic Forecasting: Monitor the forecast deviation cone and forecast directional changes for insights into potential future price movements.
🔔 Alerts for Swift Action: Set up notifications based on forecast changes to stay ahead of market movements without constant monitoring.
Behind the Magic: How It Works
The core of the Price Action Fractal Forecasts lies in its ability to compare current market behavior with historical data to unearth similar patterns. It first establishes a training data window to analyze historical prices. Within this window, it then defines a reference length to identify the most recent price action that will serve as the basis for comparison. The indicator searches through the historical data within the training window to find segments that closely match the recent price action in the reference period.
Depending on whether you choose the anticipatory or repetitive forecast mode, the indicator either looks ahead to predict future prices based on past outcomes following similar patterns or focuses on the repeating patterns within the reference period itself for forecasts. The forecast's direction can be configured to reflect the mean average of forecasted prices or the end-point relative to the start-point of the forecast, offering flexibility in how forecasts are interpreted.
To enhance the comprehensiveness and visualization, the indicator features a forecast deviation cone. This cone represents the potential range of price movements, providing a visual cue for volatility and uncertainty in the forecasted prices. The intensity of this cone can be adjusted to suit individual preferences, offering a visual guide to the level of risk and uncertainty associated with the forecasted price path.
Embrace the fractal magic of markets with AlgoAlpha's Price Action Fractal Forecasts and transform your trading today! 🌟🚀
Daily Close GAP Detector [Yosiet]User Manual for "Daily Close GAP Detector "
Overview
This script is designed to help traders identify and react to significant gaps in daily market prices. It plots daily open and close prices and highlights significant gaps with a cross. The script is particularly useful for identifying potential breakouts or reversals based on these gaps.
Configuration
GAP Close Threshold: This input allows you to set a threshold for the gap size that you consider significant. The default value is 0.001.
Timeframe Seeker: This input lets you choose the timeframe for the gap detection. The default is 'D' for daily.
Features
Daily Open and Close Lines: The script plots daily open and close prices. If the close price is lower than the open price, the line is colored red; otherwise, it's green.
Gap Detection: It calculates the difference between the current day's close and the previous day's close, both adjusted for the selected timeframe. If this difference exceeds the threshold, it's considered a significant gap.
Significant Gap Indicator: A cross is plotted on the chart to indicate significant gaps. The color of the cross indicates whether the gap is a short or long gap: red for short gaps and green for long gaps.
Alert Conditions: The script sets up alert conditions for short and long gap breakouts. You can customize the alert messages to include details like the ticker symbol, interval, price, and exchange.
How to Use
Add the Script to Your Chart: Copy the script into the Pine Script editor on TradingView and add it to your chart.
Configure Inputs: Adjust the "GAP Close Threshold" and "Timeframe Seeker" inputs as needed.
Review the Chart: The script will overlay daily open and close prices on your chart, along with crosses indicating significant gaps.
Set Alerts: Use the script's alert conditions to set up alerts for short and long gap breakouts. You can customize the alert messages to suit your trading strategy.
Extending the Code
To extend this script, you can modify the gap detection logic, add more indicators, or integrate it with other scripts for a more comprehensive trading strategy. Remember to test any changes thoroughly before using them in live trading.
Pi Cycle Indicator Low and High
The Pi Cycle Indicator is a technical analysis tool used in finance, particularly within cryptocurrency markets, to identify potential market tops or bottoms. It is based on two moving averages: the 111-day moving average and the 350-day moving average of Bitcoin's price. The indicator suggests that when these two moving averages converge or cross each other, it may signal significant market turning points. The name "Pi Cycle" comes from the mathematical relationship between these two moving averages, roughly equivalent to the mathematical constant Pi (3.14). Traders and analysts use this indicator to gauge potential trend reversals and make informed decisions regarding their trading strategies. However, like any technical analysis tool, it should be used in conjunction with other indicators and fundamental analysis for a comprehensive understanding of market conditions.
Order-Block Detector ICT/SMT + FVG + SignalsOrderBlock-Finder
This script shows order-blocks (OB) and fair-value-gaps (FVG). Additionaly there are entry signals for OB and FVG. The Dist-Parameter tell how many candles should exist between the beginning of the OB or FVG and the pullback.
Order-Blocks
An order block in trading typically refers to a significant grouping of buy or sell orders at a particular price level within a financial market. These blocks of orders can influence price movement when they are executed. Here's a breakdown:
Buy Order Block: This occurs when there's a large concentration of buy orders at a specific price level. It indicates a significant interest among traders to purchase the asset if the price reaches that level.
Sell Order Block: Conversely, a sell order block happens when there's a notable accumulation of sell orders at a particular price level. This suggests that many traders are willing to sell the asset if the price reaches that level.
Impact on Price: Order blocks can influence price movement because when the market approaches these levels, the orders within the block may be triggered, leading to increased buying or selling pressure, depending on the type of block. This surge in trading activity can cause the price to either bounce off the level or break through it.
Support and Resistance: Order blocks are often associated with support and resistance levels. A buy order block may act as support, preventing the price from falling further, while a sell order block may serve as resistance, hindering upward price movement.
Fair-Value-Gap
The fair value gap in trading refers to the difference between the current market price of an asset and its calculated fair value. This concept is often used in financial markets, especially in the context of stocks and other securities. Here's a breakdown:
Market Price: The market price is the price at which an asset is currently trading in the market. It is determined by the interaction of supply and demand forces, as well as various other factors such as news, sentiment, and economic conditions.
Fair Value: Fair value represents the estimated intrinsic value of an asset based on fundamental analysis, which includes factors such as earnings, dividends, cash flow, growth prospects, and prevailing interest rates. It's essentially what an asset should be worth based on its fundamentals.
Fair Value Calculation: Analysts and investors use various methods to calculate the fair value of an asset. Common approaches include discounted cash flow (DCF) analysis, comparable company analysis (CCA), and dividend discount models (DDM), among others.
Fair Value Gap: The fair value gap is the numerical difference between the calculated fair value of an asset and its current market price. If the market price is higher than the fair value, it suggests that the asset may be overvalued. Conversely, if the market price is lower than the fair value, it indicates that the asset may be undervalued.
Trading Implications: Traders and investors often pay attention to the fair value gap to identify potential trading opportunities. If the market price deviates significantly from the fair value, it may present opportunities to buy or sell the asset with the expectation that the market price will eventually converge towards its fair value.
CVD Divergence Indicator.1.mmAs a member of the K1m6a Lions discussion community we often use versions of the Cumulative Volume Delta indicator
as one of our primary tools along with RSI, RSI Divergences, Open interest, Volume Profile, TPO and Fibonacci levels.
We also discuss visual interpretations of CVD Divergences across multiple time frames much like RSI divergences.
RSI Divergences can be identified as possible Bullish reversal areas when the RSI is making higher low points while
the price is making lower low points.
RSI Divergences can be identified as possible Bearish reversal areas when the RSI is making lower high points while
the price is making higher high points.
CVD Divergences can also be identified the same way on any timeframe as possible reversal signals. As with RSI, these Divergences
often occur as a trend's momentum is giving way to lower volume and areas when profits are being taken signaling a possible reversal
of the current trending price movement.
Hidden Divergences are identified as calculations that may be signaling a continuation of the current trend.
Having not found any public domain versions of a CVD Divergence indicator I have combined some public code to create this
indicator and matching strategy. The calculations for the Cumulative Volume Delta keep a running total for the differences between
the positive changes in volume in relation to the negative changes in volume. A relative upward spike in CVD is created when
there is a large increase in buying vs a low amount of selling. A relative downward spike in CVD is created when
there is a large increase in selling vs a low amount of buying.
In the settings menu, the is a drop down to be used to view the results in alternate timeframes while the chart remains on current timeframe. The Lookback settings can be adjusted so that the divs show on a more local, spontaneous level if set at 1,1,60,1. For a deeper, wider view of the divs, they can be set higher like 7,7,60,7. Adjust them all to suit your view of the divs.
To create this indicator/strategy I used a portion of the code from "Cumulative Volume Delta" by @ contrerae which calculates
the CVD from aggregate volume of many top exchanges and plots the continuous changes on a non-overlay indicator.
For the identification and plotting of the Divergences, I used similar code from the Tradingview Technical "RSI Divergence Indicator"
This indicator should not be used as a stand-alone but as an additional tool to help identify Bullish and Bearish Divergences and
also Bullish and Bearish Hidden Divergences which, as opposed to regular divergences, may indicate a continuation.
