ATH Drawdown Indicator by Atilla YurtsevenThe ATH (All-Time High) Drawdown Indicator, developed by Atilla Yurtseven, is an essential tool for traders and investors who seek to understand the current price position in relation to historical peaks. This indicator is especially useful in volatile markets like cryptocurrencies and stocks, offering insights into potential buy or sell opportunities based on historical price action.
This indicator is suitable for long-term investors. It shows the average value loss of a price. However, it's important to remember that this indicator only displays statistics based on past price movements. The price of a stock can remain cheap for many years.
1. Utility of the Indicator:
The ATH Drawdown Indicator provides a clear view of how far the current price is from its all-time high. This is particularly beneficial in assessing the magnitude of a pullback or retracement from peak levels. By understanding these levels, traders can gauge market sentiment and make informed decisions about entry and exit points.
2. Risk Management:
This indicator aids in risk management by highlighting significant drawdowns from the ATH. Traders can use this information to adjust their position sizes or set stop-loss orders more effectively. For instance, entering trades when the price is significantly below the ATH could indicate a higher potential for recovery, while a minimal drawdown from the ATH may suggest caution due to potential overvaluation.
3. Indicator Functionality:
The indicator calculates the percentage drawdown from the ATH for each trading period. It can display this data either as a line graph or overlaid on candles, based on user preference. Horizontal lines at -25%, -50%, -75%, and -100% drawdown levels offer quick visual cues for significant price levels. The color-coding of candles further aids in visualizing bullish or bearish trends in the context of ATH drawdowns.
4. ATH Level Indicator (0 Level):
A unique feature of this indicator is the 0 level, which signifies that the price is currently at its all-time high. This level is a critical reference point for understanding the market's peak performance.
5. Mean Line Indicator:
Additionally, this indicator includes a 'Mean Line', representing the average percentage drawdown from the ATH. This average is calculated over more than a thousand past bars, leveraging the law of large numbers to provide a reliable mean value. This mean line is instrumental in understanding the typical market behavior in relation to the ATH.
Disclaimer:
Please note that this ATH Drawdown Indicator by Atilla Yurtseven is provided as an open-source tool for educational purposes only. It should not be construed as investment advice. Users should conduct their own research and consult a financial advisor before making any investment decisions. The creator of this indicator bears no responsibility for any trading losses incurred using this tool.
Please remember to follow and comment!
Trade smart, stay safe
Atilla Yurtseven
Statistics
Trend Shift ProThe indicator is designed to identify shifts or changes in trends as blocks, the indicator's focus on analyzing the Median of Means, Interquartile Range, and Practical Significance for potential trend changes in the market using non parametric Cohen's D. The script is designed to operate on blocks of 21 bars. The key parts of the script related to this are the conditions inside the "if" statements: The bar_index % 21 == 0 condition checks if the current bar index is divisible by 21, meaning it's the beginning of a new block of 21 bars. This condition is used to reset and calculate new values at the start of each block.
Therefore, signals or calculations related to the median of means (MoM), interquartile range (IQR), and Cohen's D are updated and calculated once every 21 bars. What this means is the frequency of signals is shown once every 21 bars.
Price Movements of Blocks:
Block-Based Analysis: This approach divides the price data into blocks or segments, often a fixed number of bars or candles. Each block represents a specific interval of time or price action. It involves No Smoothing: Unlike moving averages, block-based analysis does not apply any smoothing to the price data within each block. It directly examines the raw prices within each block.
Let's break down the key concepts and how they are used for trading:
Median of Means (MoM):
The script calculates the median of the means of seven subgroups, each consisting of three bars in shuffled order.
Each subgroup's mean is calculated based on the typical price (hlc3) of the bars within that subgroup.
The median is then computed from these seven means, representing a central tendency measure.
Note: The Median of Means provides a robust measure of central tendency, especially in situations where the dataset may have outliers or exhibit non-normal distribution characteristics. By calculating means within smaller subgroups, the method is less sensitive to extreme values that might unduly influence the overall average. This can make the Median of Means more robust than a simple mean or median when dealing with datasets that have heterogeneity or skewed distributions.
Interquartile Range (IQR):
The script calculates the IQR for each block of 21 bars.
The IQR is a measure of statistical dispersion, representing the range between the first quartile (Q1) and the third quartile (Q3) of the data.
Q1 and Q3 are calculated from the sorted array of closing prices of the 21 bars.
Non-Parametric Cohen's D Calculation:
Cohen's D is a measure of effect size, indicating the standardized difference between two means.
In this script, a non-parametric version of Cohen's D is calculated, comparing the MoM values of the current block with the MoM values of the previous block.
The calculation involves the MoM difference divided by the square root of the average squared IQR values.
Practical Significance Threshold:
The user can set a threshold for practical significance using the Threshold input.
The script determines practical significance by comparing the calculated Cohen's D with this threshold.
Plotting:
The script plots the MoM values using both straight lines and circles, with the color of the circles indicating the direction of the MoM change (green for upward, red for downward, and blue for no change).
Triangular shapes are plotted when the absolute value of Cohen's D is less than the practical significance threshold.
Overall Purpose for Trading:
The indicator is designed to help traders identify potential turning points or shifts in market sentiment. and use it as levels which needs to be crossed to have a new trend.
Changes in MoM, especially when accompanied by practical significance as determined by Cohen's D, may signal the start of a new trend or a significant move in the market.
Traders using this indicator would typically look for instances where the MoM values and associated practical significance suggest a high probability of a trend change, providing them with potential entry or exit signals. It's important for users to backtest and validate the indicator's effectiveness in different market conditions before relying on it for trading decisions.
COSTAR [SS]This idea came to me after I wrote the post about Co-Integration and pair trading. I wondered if you could use pair trading principles as a way to determine overbought and oversold conditions in a more neutral way than RSI or Stochastics.
The results were promising and this indicator resulted :-)!
About:
COSTAR provides another, more neutral way to determine whether an equity is overbought or oversold.
Instead of relying on the traditional oscillator based ways, such as using RSI, Stochastics and MFI, which can be somewhat biased and narrow sided, COSTAR attempts to take a neutral, unbiased approached to determine overbought and oversold conditions. It does this through using a co-integrated partner, or "pair" that is closely linked to the underlying equity and succeeds on both having a high correlation and a high t-statistic on the ADF test. It then references this underlying, co-integrated partner as the "benchmark" for the co-integration relationship.
How this succeeds as being "unbiased" and "neutral" is because it is responsive to underlying drivers. If there is a market catalyst or just general bullish or bearish momentum in the market, the indicator will be referencing the integrated relationship between the two pairs and referencing that as a baseline. If there is a sustained rally on the integrated partner of the underlying ticker that is holding, but the other ticker is lagging, it will indicate that the other ticker is likely to be under-valued and thus "oversold" because it is underperforming its benchmark partner.
This is in contrast to traditional approaches to determining overbought and oversold conditions, which rely completely on a single ticker, with no external reference to other tickers and no control over whether the move could potentially be a fundamental move based on an industry or sector, or whether it is a fluke or a squeeze.
The control for this giving "false" signals comes from its extent of modelling and assessment of the degree of integration of the relationship. The parameters are set by default to assess over a 1 year period, both the correlation and the integration. Anything that passes this degree of integration is likely to have a solid, co-integrated state and not likely to be a "fluke". Thus, the reliability of the assessment is augmented by the degree of statistical significance found within the relationship. The indicator is not going to prompt you to rely on a relationship that is statistically weak, and will warn you of such.
The indicator will show you all the information you require regarding the relationship and whether it is reliable or not, so you do not need to worry!
How to Use
The first step to use COSTAR is identifying which ticker has a strong relationship with the current ticker. In the main chart, you will see that SPY is overlaid with VIX. There is a strong, negative correlation between the VIX and SPY. When VIX is entered as the paired ticker, the indicator returns the data as stationary, indicating a compatible match.
Now you have 3 ways of viewing this relationship, 2 of which are going to be directly applicable to trading.
You can view them as
Price to Price Ratio (Not very useful for trading, but if you are curious)
Z-Score: Helpful for trading
Co-integration: Helpful for trading
Here is an example of all three:
Example of Z-Score Chart:
Example of Price Ratio:
Example of Co-Integration Pair:
Using for Trading
As stated above, the two best ways to use this for trading is to either use the Z-Score Chart or the Co-Integrated Pair chart.
The Z-Score chart is based off of the price ratio data and provides an assessment of both the independent and dependent data.
The co-integration shows the dependent (the ticker you are trading) in yellow and the independent (the ticker you are referencing) in teal. When teal is above yellow, you will see it is green. This means, based on your benchmark pair, there is still more up room and the ticker you are trading is actually lagging behind.
When the yellow crosses up, it will turn red. This means that your ticker is out-performing the benchmark pair and you likely will see pullback and a "regression to the mean" through re-integration.
The indicator is capable of plotting out entries and exits, which are guided by the z-score:
How Effective is it?
I created a basic strategy in Pinescript, and the back-test results vary. Trading ES1! using NQ1! as the co-integrated pair, results were around 78% effective.
With VIX, results were around 50% effective, but with a net profit.
Generally, the efficacy surpassed that of both stochastics and RSI.
I will be releasing the strategy version of this in the coming days, still just cleaning up that code and making it more "public use" friendly.
Other Applications
If you are a pair trader, you can technically use this for pair trading as well. That's essentially all this is doing :-).
Tips
If you are trading a ticker such as MSFT, AMD, KO etc., it's best to try to find an ETF or index that has that particular ticker as a large holding and use that as your benchmark. You will see on the indicator whether there is a high correlation and whether the data is indeed stationary.
If the indicator returns "Non-stationary", you can attempt to extend your regression range from 252 to 500. If this fixes the issue, ensure that the correlation is still >= 0.5 or <= -0.5. If this does not work still, you will need to find another pair, as its likely the result of incompatibility and an insignificant relationship.
To help you identify tickers with strong relationships, consider using a correlation heatmap indicator. I have one available and I think there are a couple of other similar ish ones out there. You want to make sure the relationship is stable over time (a correlation of >= 0.50 or <= -0.5 over the past 252 to 500 days).
IMPORTANT: The long and short exits delete the signal after one is signaled. Therefore, when you look back in the chart you will notice there are no signals to exit long or short. That is because they signal as they happen. This is to keep the chart clean.
'Tis all my friends!
Hope you enjoy and let me know your questions and suggestions below!
Side note:
COSTAR stands for Co-integration Statistical Analysis and Regression. ;)
Predictive Indicator Matrix v2 (public)Predictive Indicator Matrix for TradingView
The "Predictive Indicator Matrix" is an advanced analytical tool for TradingView, designed to work across multiple timeframes from 1D to 5m. It employs a complex algorithm combining various technical indicators such as the Ichimoku Cloud, ADX, five EMAs, slow and fast versions of MACD, Stochastic Oscillator, and RSI. This combination is meticulously curated to provide a multifaceted view of the market.
The uniqueness of this script lies in its trigonometric and mathematical logic. It utilizes trigonometric functions, like the arctangent and cosine functions, to calculate the 'bias' and 'score' of market trends, presented in decimal percentages (%). These calculations are pivotal in understanding market dynamics and potential directional changes. The 'bias' is calculated using the cosine of the arctangent of the ratio between current and previous scores, adjusted for market shift. This innovative approach provides a nuanced understanding of market momentum and trend strength.
Furthermore, the script dynamically generates prediction lines based on these calculations. These lines represent potential future market paths, plotted using the current market data and the calculated levels from the matrix. This feature visually represents the script's analysis, offering users an intuitive and actionable insight into potential market movements.
The integration of these indicators, along with the trigonometric calculations, makes the script not only unique but also a powerful tool for traders. It encapsulates various market aspects in one matrix, offering a comprehensive analysis that goes beyond traditional indicator-based strategies.
Note 1: This tool is intended for market analysis and should not be construed as investment advice.
Note 2: Community engagement is encouraged. For additional features like a time display on the table, please provide feedback in the comments. I am open to incorporating such features to enhance the tool's utility based on user preference.
Absolute Momentum (Time Series Momentum)Absolute momentum , also known as time series momentum , focuses on the trend of an asset's own past performance to predict its future performance. It involves analyzing an asset's own historical performance, rather than comparing it to other assets.
The strategy determines whether an asset's price is exhibiting an upward (positive momentum) or downward (negative momentum) trend by assessing the asset's return over a given period (standard look-back period: 12 months or approximately 250 trading days). Some studies recommend calculating momentum by deducting the corresponding Treasury bill rate from the measured performance.
Absolute Momentum Indicator
The Absolute Momentum Indicator displays the rolling 12-month performance (measured over 250 trading days) and plots it against a horizontal line representing 0%. If the indicator crosses above this line, it signifies positive absolute momentum, and conversely, crossing below indicates negative momentum. An additional, optional look-back period input field can be accessed through the settings.
Hint: This indicator is a simplified version, as some academic approaches measure absolute momentum by subtracting risk-free rates from the 12-month performance. However, even with higher rates, the values will still remain close to the 0% line.
Benefits of Absolute Momentum
Absolute momentum, which should not be confused with relative momentum or the momentum indicator, serves as a timing instrument for both individual assets and entire markets.
Gary Antonacci , a key contributor to the absolute momentum strategy (find study below), emphasizes its effectiveness in multi-asset portfolios and its importance in long-only investing. This is particularly evident in a) reducing downside volatility and b) mitigating behavioral biases.
Moskowitz, Ooi, and Pedersen document significant 'time series momentum' across various asset classes, including equity index, currency, commodity, and bond futures, in 58 liquid instruments (find study below). There's a notable persistence in returns ranging from one to 12 months, which tends to partially reverse over longer periods. This pattern aligns with sentiment theories suggesting initial under-reaction followed by delayed over-reaction.
Despite its surprising ease of implementation, the academic community has successfully measured the effects of absolute momentum across decades and in every major asset class, including stocks, bonds, commodities, and foreign exchange (FX).
Strategies for Implementing Absolute Momentum:
To Buy a Stock:
Select a Look-Back Period: Choose a historical period to analyze the stock's performance. A common period is 12 months, but this can vary based on your investment strategy.
Calculate Excess Return: Determine the stock's excess return over this period. You can also assume a risk-free rate of "0" to simplify the process.
Evaluate Momentum:
If the excess return is positive, it indicates positive absolute momentum. This suggests the stock is in an upward trend and could be a good buying opportunity.
If the excess return is negative, it suggests negative momentum, and you might want to delay buying.
Consider further conditions: Align your decision with broader market trends, economic indicators, or fundamental analysis, for additional context.
To Sell a Stock You Own:
Regularly Monitor Performance: Use the same look-back period as for buying (e.g., 12 months) to regularly assess the stock's performance.
Check for Negative Momentum: Calculate the excess return for the look-back period. Again, you can assume a risk-free rate of "0" to simplify the process. If the stock shows negative momentum, it might be time to consider selling.
Consider further conditions:Align your decision with broader market trends, economic indicators, or fundamental analysis, for additional context.
Important note: Note: Entering a position (i.e., buying) based on positive absolute momentum doesn't necessarily mean you must sell it if it later exhibits negative absolute momentum. You can initiate a position using positive absolute momentum as an entry indicator and then continue holding it based on other criteria, such as fundamental analysis.
General Tips:
Reassessment Frequency: Decide how often you will reassess the momentum (monthly, quarterly, etc.).
Remember, while absolute momentum provides a systematic approach, it's recommendable to consider it as part of a broader investment strategy that includes diversification, risk management, fundamental analysis, etc.
Relevant Capital Market Studies:
Antonacci, Gary. "Absolute momentum: A simple rule-based strategy and universal trend-following overlay." Available at SSRN 2244633 (2013)
Moskowitz, Tobias J., Yao Hua Ooi, and Lasse Heje Pedersen. "Time series momentum." Journal of financial economics 104.2 (2012): 228-250
SPX Daily Probability Predictor_MFCDescription:
The SPX Daily Probability Predictor is a powerful trading indicator designed exclusively for TradingView, providing traders with valuable insights into the potential movement of the S&P 500 index (SPX) on a daily basis. This indicator utilizes a sophisticated calculation method based on historical price movements, including gaps, to estimate the probability of the index's future direction.
Key Features:
Daily Probability Calculation:
The indicator calculates the daily probability of the SPX movement by analyzing the standard deviation of historical price changes. This statistical approach offers a comprehensive understanding of the market's volatility and aids traders in making more informed decisions.
Historical Movement Inclusion:
Unlike traditional indicators that only consider the closing prices, the SPX Daily Probability Predictor goes a step further by incorporating the full spectrum of daily movements, including gaps. This inclusive approach provides a more accurate representation of market dynamics, enhancing the reliability of the probability predictions.
Real-Time Analysis:
Stay ahead of the market with real-time analysis that adapts to the current trading session. The SPX Daily Probability Predictor dynamically adjusts its calculations throughout the trading day, ensuring that traders receive the most up-to-date and relevant information for their decision-making process.
Customizable Parameters:
Tailor the indicator to your trading preferences with customizable parameters. Adjust the lookback period or fine-tune other settings to align the probability predictions with your individual trading strategy.
By incorporating historical price movements, including gaps, and employing statistical analysis to calculate daily probabilities, the SPX Daily Probability Predictor equips traders with a valuable tool for anticipating potential market directions. Whether you are a seasoned investor or a newcomer to the world of trading, this indicator provides actionable insights that can contribute to more informed decision-making in the dynamic environment of the stock market.
Upcoming Enhancements:
Please note that while the SPX Daily Probability Predictor currently offers a robust set of features for daily market analysis, we are committed to continuous improvement and the development of additional functionalities. In future updates, users can look forward to exciting enhancements, including the capability to forecast future probabilities of market movements. This forward-looking feature will provide traders with a valuable glimpse into potential trends, aiding in more proactive decision-making.
Furthermore, we are actively working on expanding the indicator's scope to accommodate different time frames. Soon, traders will have the option to obtain probability data not only on a daily basis but also for monthly or weekly intervals. This extended flexibility allows for a more comprehensive analysis, catering to various trading styles and preferences.
As we strive to create a versatile and powerful tool for the TradingView community, we welcome user feedback and suggestions for additional features. Your insights play a crucial role in shaping the future evolution of the SPX Daily Probability Predictor, ensuring it remains a valuable asset in the dynamic landscape of financial markets. Stay tuned for updates as we continue to enhance and refine this innovative trading indicator.
[ETNX] BTC CME OI L/SOVERVIEW
This indicator displays how many traders have Long and Short positions opened on CME Bitcoin Futures and Options. The data is provided from the CFTC Commitments of Traders Reports. These reports are given weekly. Therefore, this indicator works better on weekly timeframes.
The COT reports are separated into 5 categories:
Dealer/Intermediary - These participants are typically described as the “sell side” of the market. Though they may not predominately sell futures, they design and sell various financial assets to clients. They tend to have matched books or offset their risk across markets and clients. Futures contracts are part of the pricing and balancing of risk associated with the products they sell and their activities. These include large banks (U.S. and non-U.S.) and dealers in securities, swaps, and other derivatives.
Asset Manager/Institutional - These are institutional investors, including pension funds, endowments, insurance companies, mutual funds, and portfolio/investment managers whose clients are predominantly institutional.
Leveraged Funds - These are typically hedge funds and various types of money managers, including registered commodity trading advisors (CTAs); registered commodity pool operators (CPOs), or unregistered funds identified by CFTC. The strategies may involve taking outright positions or arbitrage within and across markets. The traders may be engaged in managing and conducting proprietary futures trading and trading on behalf of speculative clients.
Other Reportables - Reportable traders not placed into one of the first three categories are placed into the “other reportables” category. The traders in this category mostly use markets to hedge business risk, whether that risk is related to foreign exchange, equities, or interest rates. This category includes corporate treasuries, central banks, smaller banks, mortgage originators, credit unions and any other reportable traders not assigned to the other three categories.
Non Reportable
INPUT DISPLAY
The Open Interest can be displayed in three ways:
Contracts - How many contracts are opened on CME
BTC - How many BTC the contracts worth
Billions USD - How much is worth in USD based on the CME BTC Price
The Open Interest is calculated for:
Futures - The Futures Short and Long Positions Opened
Futures & Options - The Futures & Options Short and Long Positions Opened
Cryptocurrency Cointegration Matrix (SpiritualHealer117)This indicator plots a cointegration matrix for the pairings of 100 cryptocurrencies. The matrix is populated with ADF t-stats (from an ADF-test with 1 lag). An ADF-test (Augmented Dickey-Fuller test) tests the null hypothesis that an AR process has a unit root. If rejected, the alternative hypothesis is usually that the AR process is either stationary or trend-stationary. This model extends upon Lejmer's Cointegration Matrix for forex by enabling the indicator to use cryptocurrency pairs and allows for significantly more pairs to be analyzed using the group selection feature. This indicator arose from collaboration with TradingView user CryptoJuju.
This indicator runs an ADF-test on the residuals (spread) of each pairing (i.e. a cointegration test). It tests if there is a unit root in the spread between the two assets of a pairing. If there is a unit root in the spread, it means the spread varies randomly over time, and any mean reversion in the spread is very hard to predict. By contrast, if a unit root does not exist, the spread (distance between the assets) should remain more or less constant over time, or rise/fall in close to the same rate over time. The more negative the number from an ADF-test, the stronger the rejection of the idea that the spread has a unit root. In statistics, there are different levels which correspond with the confidence level of the test. For this indicator, -3.238 equals a confidence level of 90%, -3.589 equals a confidence level of 95% and -4.375 equals a confidence level of 99% that there is not a unit root. So the colors are based on the confidence level of the test statistic (the t-stat, i.e. the number of the pairing in the matrix). So if the number is greater than -3.238 it is green, if it's between -3.238 and -3.589 it's yellow, if it's between -3.589 and -4.375 it's orange, and if its lower than -4.375 it's red.
There are multiple ways to interpret the results. A strong rejection of the presence of a unit root (i.e. a value of -4.375 or below) is not a guarantee that there is no unit root, or that any of the two alternative hypotheses (that the spread is stationary or trend-stationary) are correct. It only means that in 99% of the cases, if the spread is an AR process, the test is right, and there is no unit root in the spread. Therefore, the results of this test is no guarantee that the result proves one of the alternative solutions. Green therefore means that a unit root cannot be ruled out (which can be interpreted as "the two cryptocurrencies probably don't move together over time"), and red means that a unit root is likely not present (which can be interpreted as "the two cryptocurrencies may move together over time").
One possible way to use this indicator is to make sure you don't trade two pairs that move together at the same time. So basically the idea is that if you already have a trade open in one of the currency pairs of the pairing, only enter a trade in the other currency pair of that pairing if the color is green, or you may be doubling your risk. Alternatively, you could implement this indicator into a pairs trading system, such as a simple strategy where you buy the spread between two cryptocurrencies with a red result when the spread's value drops one standard deviation away from its moving average, and conversely sell when it moves up one standard deviation above the moving average. However, this strategy is not guaranteed to work, since historical data does not guarantee the future.
Specific to this indicator, there are 100 different cryptocurrency tickers which are included in the matrix, and the cointegration matrices between all the tickers can be checked by switching asset group 1 and asset group 2 to different asset groups. The ADF test is computed using a specified length, and if there is insufficient data for the length, the test produces a grayed out box.
NOTE: The indicator can take a while to load since it computes the value of 400 ADF tests each time it is run.
[ETNX] BTC CME TradersOVERVIEW
This indicator displays how many traders have Long and Short positions opened on CME Bitcoin Futures and Options. The short traders have negative values only for display purposes. Therefore, if the short value is displayed as -56, that means that there are 56 traders that have short positions opened. The total of traders is the sum of short and long traders. The data is provided from the CFTC Commitments of Traders Reports. These reports are given weekly. Therefore, this indicator works better on weekly timeframes.
The COT reports are separated into 5 categories:
Dealer/Intermediary - These participants are typically described as the “sell side” of the market. Though they may not predominately sell futures, they design and sell various financial assets to clients. They tend to have matched books or offset their risk across markets and clients. Futures contracts are part of the pricing and balancing of risk associated with the products they sell and their activities. These include large banks (U.S. and non-U.S.) and dealers in securities, swaps, and other derivatives.
Asset Manager/Institutional - These are institutional investors, including pension funds, endowments, insurance companies, mutual funds, and portfolio/investment managers whose clients are predominantly institutional.
Leveraged Funds - These are typically hedge funds and various types of money managers, including registered commodity trading advisors (CTAs); registered commodity pool operators (CPOs), or unregistered funds identified by CFTC. The strategies may involve taking outright positions or arbitrage within and across markets. The traders may be engaged in managing and conducting proprietary futures trading and trading on behalf of speculative clients.
Other Reportables - Reportable traders not placed into one of the first three categories are placed into the “other reportables” category. The traders in this category mostly use markets to hedge business risk, whether that risk is related to foreign exchange, equities, or interest rates. This category includes corporate treasuries, central banks, smaller banks, mortgage originators, credit unions and any other reportable traders not assigned to the other three categories.
Non Reportable
INPUT DISPLAY
The Open Interest can be displayed in three ways:
Futures - The Futures Short and Long Positions Opened
Options - The Options Short and Long Positions Opened
Futures & Options - The Futures & Options Short and Long Positions Opened
Ranges With Targets [ChartPrime]The Ranges With Targets indicator is a tool designed to assist traders in identifying potential trading opportunities on a chart derived from breakout trading. It dynamically outlines ranges with boxes in real-time, providing a visual representation of price movements. When a breakout occurs from a range, the indicator will begin coloring the candles. A green candle signals a long breakout, suggesting a potential upward movement, while a red candle indicates a short breakout, suggesting a potential downward movement. Grey candles indicate periods with no active trade. Ranges are derived from daily changes in price action.
This indicator builds upon the common breakout theory in trading whereby when price breaks out of a range; it may indicate continuation in a trend.
Additionally, users have the ability to customize their risk-reward settings through a multiplier referred to as the Target input. This allows traders to set their Take Profit (TP) and Stop Loss (SL) levels according to their specific risk tolerance and trading strategy.
Furthermore, the indicator offers an optional stop loss setting that can automatically exit losing trades, providing an additional layer of risk management for users who choose to utilize this feature.
A dashboard is provided in the top right showing the statistics and performance of the indicator; winning trades; losing trades, gross profit and loss and PNL. This can be useful when analyzing the success of breakout trading on a particular asset or timeframe.
Baseline Optimizer NNFX [m8b]DESCRIPTION
The Baseline Optimizer indicator is a tool to aid in baseline configuration (specifically moving averages). It manages state across iterations within a single bar to allow the indicator to test different settings. This allows the user to find a specific configuration that works well for that asset and timeframe. It also recreates pieces of the default TradingView backtesting framework so multiple settings can be tested concurrently.
Originality and usefulness
Default pine script doesn't allow for state management within a loop due to the way historical values are handled (e.g. EMA). It also does not allow for backtesting across multiple settings concurrently. The the functions are all unique in that they allow for proper state management during the optimization process.
ADDITIONAL BACKGROUND AND USAGE
While the platform is built to support the NNFX way of trading, this indicator can be utilized by any trader who wants to optimize an MA for a specific asset, chart, or time frame regardless of asset class.
NNFX revolves around a systematic approach to trading, designed to be mechanical and with minimal discretionary input. This strategy typically involves multiple indicators across different categories to confirm trading signals. The approach involves:
Baseline indicator to determine the overall trend direction
Confirmation (Leading & Lagging) indicator used to validate the trade
Volume indicator to confirm the presence of market participation
Exit indicator to signal when to close the trade
Supported Moving Averages
v1 (this indicator): ALMA, DEMA, EMA, HMA, KAMA, RMA / SMMA, SMA, Tilson T3, TEMA, WMA, VWMA
USAGE
By default, this indicator will run on “Standard” mode, and acts as a roll-up of MAs. Simply set the MA type and length.
When mode is set to “Optimizer”, a table will appear on the chart that displays trade stats for the various configurations.
Net Profit, Closed Trades, % Profitable, Profit Factor, Max Drawdown, Avg Trade, Avg Bars
STANDARD SETTINGS
MA Type: ALMA, DEMA, EMA, HMA, KAMA, RMA, SMA, T3, TEMA, WMA, VWMA
MA Length: Length of the MA
MA: Source: Source for the MA
OPTIMIZER SETTINGS
Profit factor threshold: Acts as a filter to the trading stats to make it more readable
% profitable threshold: Acts as a filter to the trading stats to make it more readable
Min trades threshold: Acts as a filter to the trading stats to make it more readable
Start & End Date: The data window for the optimizer to backtest
Trade Direction: All, Long only, Short Only
Pyramid Max: Works the same as standard TradingView pyramid
Optimizer Param Start: The first value for the optimizer
Optimizer Param End: The end value for the optimizer
Optimizer Param Step: The step value for the optimizer
Stats green threshold: The value to turn results green
Stats red threshold: The value to turn results red
IMPORTANT NOTES (Errors & Pine Limitations)
Warm-up Period Multiplier: "Warming up" refers to the period where the indicator begins to reflect accurate and meaningful data. A default value of 5 should generally ensure baseline data is accurate. If performance is an issue (e.g. timeouts), this can be adjusted down at the cost of accuracy. While this may not be ideal, for the purposes of optimization the results should be directionally accurate in most cases with lower values. If you see the stats changing in real-time in the results, that’s often a good indicator your warm-up is too short. Note, the EMA in particular requires a long warm-up due to its nature (~3 x length)
Timeouts: Depending on your TradingView plan, scripts will either timeout after 20 or 40 seconds. If you get too aggressive with either timeframes or Start/End/Step, you may timeout. THIS IS NOT A BUG, it’s a limitation of TradingView and/or your plan. The fixes for this are 1) test less states at a time 2) use a higher timeframe 3) get a Premium TradingView Plan.
Array Size / Memory Size: This should rarely be an issue with baseline optimization, BUT if you get really aggressive with settings (particularly on the T3) you could run into a scenario with Pine reaches/exceeds the limitation of an array size (100,000). If this happens, reduce your timeframe or input param values to resolve.
DISCLAIMER
This indicator is for educational purposes only, not financial advice. The developers are not financial advisors and accept no liability for how you use the information or features. By using this indicator, you acknowledge that all trading decisions are your own responsibility and that past performance does not guarantee future results.
TrendX Earning-Approach Valuation (Stock)TrendX Earning-Approach Valuation (Stock) indicator is a Fundamental Analysis tool that only focus on the Earnings of the company.
USAGE
This Earning-Approach Valuation is easy to use and customize. TrendX valuates a company's Fair Value based on all the earnings multiples and its average with a little interference of users' risk capacity. Technical Analysis is also included as an additional basis for investment decisions.
Valuation tool
The strategy projects the future value of the company based on its Fiscal Quarter operating income, net income and diluted total shares outstanding. Operating income is the income from the core business operations, before interest and taxes. Net income is the income after interest, taxes and other expenses. The strategy assumes that the operating income and net income will grow at the same rate as their historical values.
The strategy also adjusts the diluted total shares outstanding, which may change due to dilutive securities, to calculate the projected EPS. It then uses the price-to-earnings (P/E) as a multiple in future valuation approach.
Value classification
TrendX classifies 2 phases between Under-value and Over-value, which are represented in green and red, respectively. This toolkit can work well with other indicators of technical analysis, but it can also stand on its own because of its built-in Technical Analysis plugins, which are explained below.
Display potential Support and Resistance levels
TrendX shows support and resistance levels based on the company's past and present Fair Values, which is colored in white. It also draws a current Fair Value line with green coloring.
Potential Entry and Exit zone
By combining the Breakout and retesting technique in both Lagging and Leading's perpective, with the Earning-based valuation, traders can optimize not only the entry-level at the Undervalued zone but also the exit-level at the potential “Bear” area.
Margin of Safety
TrendX also incorporates the margin of safety, which is shown in Risk Ability for customs.
CONCLUSION
The strategy is useful for valuing companies that have positive and stable earnings, and a predictable growth rate. Accordingly, it can also be helpful for traders to use alongside other forms of Technical Analysis.
Many traders fail to realize that indicators are not enough to achieve success, and they end up getting confused and frustrated by trying to find a perfect solution. TrendX aims to avoid this problem by providing clear and concise signals that can be easily followed
Disclaimer
The results achieved in the past are not all reliable sources of what will happen in the future. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
The strategy also relies on assumptions that may not be accurate or realistic, which can vary depending on the market conditions and investor sentiment.
If you notice significant changes in the Valuation over time, it is due to revisions in the company’s reported financials, changes in accounting standards, or corrections of previous errors.
Therefore, you should always exercise caution and judgment when making decisions based on past performance.
Expected Move by Option's Implied Volatility High Liquidity
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols with high option liquidity.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options.There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry. This script will display Expected Move data for Symbols within the range of JBL-NOTE in alphabetical order.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Financial PlusFinancial Plus is an indicator designed to provide users with the flexibility to select up to 10 different financial metrics within four key categories: Statistics, Income Statements, Balance Sheets, and Cash Flow. Powered by Pine Script's request.financial() function, this library offers access to over 200 financial metrics.
You can choose from multiple frequency options, such as FQ (quarterly) , FY (yearly) , TTM (trailing twelve months) , and FH (semiannual) , depending on the availability of each metric. For detailed information regarding specific metrics and their supported frequencies, please consult Financial IDs .
BarChangeDeltaThe "BarChangeDelta" indicator, facilitates the calculation of price delta or percent changes between user-defined start and end points within the current or between preceding and current bars. It offers several customizable options to fit various trading strategies.
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This indicator provides the following key functionalities:
- Two Modes:
* PreviousToCurrentBarDelta: Compares user-selected start points from the previous bar to the end points of the current bar.
* CurrentBarDelta: Compares user-selected start and end points within the current bar.
- Start Point/End Point Customization: Allows users to define the source for start and end points used in the delta calculations.
- ABS Mode: Option to display only absolute values, reflected on the histogram drawn.
- Show delta in percents: Enables users to calculate delta in percentage changes instead of price delta.
- Moving Average (MA) Plot: A plot of the MA of the last user-defined number of delta prices or percents.
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The "BarChangeDelta" indicator finds practical application in various trading scenarios. It can be particularly useful for assessing daily price changes between open/close or high/low for determining strike prices, especially for 0DTE trading.
Z-ScoreThe "Z-Score" indicator is a unique and powerful tool designed to help traders identify overbought and oversold conditions in the market. Below is an explanation of its features, usefulness, and what makes it special:
Features:
Z-Score Calculation: The indicator calculates the Z-Score, a statistical measure that represents how far the current price is from the moving average (MA) in terms of standard deviations. It helps identify extreme price movements.
Customizable Parameters: Traders can adjust key parameters such as the Z-Score threshold, the type of MA (e.g., SMA, EMA), and the length of the moving average to suit their trading preferences.
Signal Options: The indicator offers flexibility in terms of signaling. Traders can choose whether to trigger signals when the Z-Score crosses the specified threshold or when it moves away from the threshold.
Visual Signals : Z-Score conditions are represented visually on the chart with color-coded background highlights. Overbought conditions are marked with a red background, while oversold conditions are indicated with a green background.
Information Table: A dynamic information table displays essential details, including the MA type, MA length, MA value, standard deviation, current price, and Z-Score. This information table helps traders make informed decisions.
Usefulness:
Overbought and Oversold Signals: Z-Score is particularly valuable for identifying overbought and oversold market conditions. Traders can use this information to potentially enter or exit positions.
Statistical Analysis: The Z-Score provides a statistical measure of price deviation, offering a data-driven approach to market analysis.
Customization: Traders can customize the indicator to match their trading strategies and preferences, enhancing its adaptability to different trading styles.
Visual Clarity: The visual signals make it easy for traders to quickly spot potential trade opportunities on the price chart.
In summary, the Z-Score indicator is a valuable tool for traders looking to incorporate statistical analysis into their trading strategies. Its customizability, visual signals, and unique statistical approach make it an exceptional choice for identifying overbought and oversold market conditions and potential trading opportunities.
Expected Move by Option's Implied Volatility Symbols: EAT - GBDC
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of EAT-GDBC in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: CLFD-EARN This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of CLFD - EARN in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: B - CLF
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of B - CLF in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
TrendX Financial Modelling (Stock)TrendX Financial Modelling (Stock) indicator is a comprehensive tool that takes full advantage of both financial modelling and technical analysis to estimate the Intrinsic Value of any security. There are 2 main Fundamental methods for Intrinsic valuation: Discounted Cash Flow (DCF) and Basic Valuation.
USAGE
This Intrinsic Value Indicator is easy to use and customize. TrendX enables adjusting the parameters such as the type of basic valuation, market expected growth rate, the earnings multiple, and the margin of safety level according to your own assumptions and preferences. You can also apply different filters and alerts to get notified when a buy or sell signal is generated.
Valuation tool
DCF model will calculate the Present Value of all expected future cash flows, discounted at an appropriate rate, and compare it with the current market condition. In addition, Basic Valuation consists of 6 types of approaches depending on the industry of the target company. Combining these, the chart will show the potential target value from the current price.
Value classification
TrendX classifies 2 phases between Under-value and Fair-value, which are represented in Purple and grey, respectively.
Display potential targets
TrendX spot key target levels based on TrendX’s Valuation toolkit.
Optimal valued entry-exit
By combining the Breakout structure and divergences with the TrendX financial model, investors can optimize not only the entry-level at the Undervalued zone but also the exit-level at the potential “Bear” area.
Margin of safety
TrendX also incorporates the margin of safety principle, which is a key concept in value investing. The margin of safety is the secured zone between the intrinsic value and the market price, expressed as a percentage. The higher the margin of safety, the lower the risk of loss and the higher the potential return, which is customizable based on your preferences.
CONCLUSION
The Intrinsic Financial Model Indicator is very practical for any investor who wants to make informed and rational decisions based on Fundamental Analysis. It will help find undervalued gems in any market and avoid overpaying for overhyped stocks. Accordingly, it can also be helpful for traders to use alongside other forms of Technical Analysis.
Many traders fail to realize that indicators are not enough to achieve success, and they end up getting confused and frustrated by trying to find a perfect solution. TrendX aims to avoid this problem by providing clear and concise signals that can be easily followed
DISCLAIMER
The results achieved in the past are not all reliable sources of what will happen in the future. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
If you notice significant changes in the Intrinsic Valuation over time, it is due to revisions in the company’s reported financials, changes in accounting standards, or corrections of previous errors.
Therefore, you should always exercise caution and judgment when making decisions based on past performance.
Lite Trading Diary : equity curveDynamic trading journal with equity curve display. Detailed results with prop firm objectives, editable, $/month estimation, possibility to compare two strategies.
one line in parameter = one trade.
For each trade, specify : RR (Win, or "-1" for a stoploss), type of trade, and a comment.
The bottom left table summarizes the overall performance with some key information. RA return => Risk adjusted performance.
there is the possibility to define a "Type" : type 1, 2 or 3. It allows to split the equity curve. You can thus distinguish the different sub-strategies of your strategy, visually see their effectiveness, and be able to adjust your risk exposure accordingly.
Learn from your backtests. Identify your strengths, your weaknesses, and improve!
All the conditions to succeed in the challenge are adjustable in the parameters. Please note : drawdown on the equity curve is max drawdown. On the table => static drawdown.
Use "A random day trading" indicator to spice up your training.
I hope this will be useful for you to track your performance !
OI Visible Range Ladder [Kioseff Trading]Hello!
This Script “OI Visible Range Ladder” calculates open interest profiles for the visible range alongside an OI ladder for the visible period!
Features
OI Profile Anchored to Visible Range
OI Ladder Anchored to Visible Range
Standard POC and Value Area Lines, in Addition to Separated POCs and Value Area Lines for each category of OI x Price
Configurable Value Area Targets
Curved Profiles
Up to 9999 Profile Rows per Visible Range
Stylistic Options for Profiles
Up to 9999 volume profile levels (Price levels) can be calculated for each profile, thanks to the new polyline feature, allowing for less aggregation / more precision of open interest at price.
The image above shows primary functionality!
Green profiles = Up OI / Up Price
Yellow profiles = Down OI / Up Price
Purple profiles = Up OI / Down Price
Red profiles = Down OI / Down Price
The image above shows POCs for each OI x Price category!
Profiles can be anchored on the left side for a more traditional look.
The indicator is robust enough to calculate on “small price periods”, or for a price period spanning your entire chart fully zoomed out!
That’s about it :D
This indicator is Part of a series titled “Bull vs. Bear” - a suite of profile-like indicators.
Thanks for checking this out!
If you have any suggestions please feel free to share!
Global Leaders M2Introducing the Global Leaders M2 Indicator
The Global Leaders M2 indicator is a comprehensive tool designed to provide you with crucial insights into the money supply (M2) of the world's top 10 economic powerhouses. This powerful indicator offers a wealth of information to help you make informed decisions in the financial markets.
Key Features:
Multi-Country M2 Data: Access M2 data for the world's top 10 economic leaders, including China, the United States, Japan, Germany, the United Kingdom, France, Italy, Canada, Russia, and India.
Rate of Change Analysis: Understand the rate of change in M2 data for each country and the overall global aggregate, allowing you to gauge the momentum of monetary supply.
Customizable Display: Tailor your chart to display the data of specific countries, or focus on the total global M2 value based on your preferences.
Currency Selection: Choose your preferred currency for displaying the M2 data, making it easier to work with data in your currency of choice.
Interactive Overview Table: Get an overview of M2 data for each country and the global total in an interactive table, complete with color-coded indicators to help you quickly spot trends.
Precision and Clarity: The indicator provides precision to two decimal places and uses color coding to differentiate between positive and negative rate of change.
Whether you're a seasoned investor or a newcomer to the world of finance, the Global Leaders M2 indicator equips you with valuable data and insights to guide your financial decisions. Stay on top of global monetary supply trends, and trade with confidence using this user-friendly and informative tool.
