COT-NocTradingIndicator Description:
Commitments of Traders (COT) Data Indicator
The Commitments of Traders (COT) Data Indicator on TradingView provides insights into market sentiment based on the weekly CFTC (Commodity Futures Trading Commission) reports. It plots three key lines derived from this data, offering valuable information for traders seeking to understand positioning trends among large speculators, commercial hedgers, and small traders.
Lines Plotted:
Commercials: Reflects positions held by commercial entities engaged in the production or sale of the underlying commodity. Their positions often act as a hedge against physical market exposure.
Non Commercials: Represents positions held by large speculators, typically hedge funds and large financial institutions, who often take more significant positions based on their market outlook.
Retail Traders: Shows positions held by small traders, including individual retail traders and smaller institutional players, providing insights into the broader retail sentiment.
Labeling:
Each line is accompanied by a label to clearly identify its corresponding group, enhancing clarity and ease of interpretation for traders analyzing the indicator.
Usage:
Trend Confirmation: Monitor the positioning of commercial and non commercial relative to retail traders to confirm trends and potential reversals.
Sentiment Analysis: Assess shifts in market sentiment based on changes in positioning across different trader categories.
Trading Signals: Use crossovers, divergences, and extreme positioning relative to historical data to generate potential trading signals.
This indicator is valuable for traders looking to incorporate institutional positioning data into their trading strategies, offering a deeper understanding of market dynamics beyond price action alone.
Analisis Fundamental
Bitcoin Fundamentals - Bitcoin Block RewardThe Bitcoin Block Reward is the batch of new Bitcoins generated by the miners after solving each block.
The Block Reward is set as a basic rule and cannot be changed without agreement between the entire Bitcoin network. It started at 50 BTC during the first period. Afterwards the Block Reward gets adjusted to half of it value (Halving Event) on each cycle of 210000 blocks mined.
This is the only way that new bitcoins are created. It creates an incentive for miners to secure the network.
Over time the Block Reward will decreases to a value that might not cover the mining costs. At that point, the use of the Bitcoin Network might have increased sufficiently as to generate enough transaction fees to cover the mining costs.
MOTIVATION
Even though this is a very simple indicator, I'm currently missing a data source to compute the Block Reward value within Tradingview. Therefore, I created this indicator and its associated library function to enable its visualization and (eventually) for coders to make use of the source function to power more elaborate scripts related to the Halving Events.
Hope that helps!
RunRox - Backtesting System (ASMC)Introducing RunRox - Backtesting System (ASMC), a specially designed backtesting system built on the robust structure of our Advanced SMC indicator. This innovative tool evaluates various Smart Money Concept (SMC) trading setups and serves as an automatic optimizer, displaying which entry and exit points have historically shown the best results. With cutting-edge technology, RunRox - Backtesting System (ASMC) provides you with effective strategies, maximizing your trading potential and taking your trading to the next level
🟠 HOW OUR BACKTESTING SYSTEM WORKS
Our backtesting system for the Advanced SMC (ASMC) indicator is meticulously designed to provide traders with a thorough analysis of their Smart Money Concept (SMC) strategies. Here’s an overview of how it works:
🔸 Advanced SMC Structure
Our ASMC indicator is built upon an enhanced SMC structure that integrates the Institutional Distribution Model (IDM), precise retracements, and five types of order blocks (CHoCH OB, IDM OB, Local OB, BOS OB, Extreme OB). These components allow for a detailed understanding of market dynamics and the identification of key trading opportunities.
🔸 Data Integration and Analysis
1. Historical Data Testing:
Our system tests various entry and exit points using historical market data.
The ASMC indicator is used to simulate trades based on predefined SMC setups, evaluating their effectiveness over a specified time period.
Traders can select different parameters such as entry points, stop-loss, and take-profit levels to see how these setups would have performed historically.
2. Entry and Exit Events:
The backtester can simulate trades based on 12 different entry events, 14 target events, and 14 stop-loss events, providing a comprehensive testing framework.
It allows for testing with multiple combinations of entry and exit strategies, ensuring a robust evaluation of trading setups.
3. Order Block Sensitivity:
The system uses the sensitivity settings from the ASMC indicator to determine the most relevant order blocks and fair value gaps (FVGs) for entry and exit points.
It distinguishes between different types of order blocks, helping traders identify strong institutional zones versus local zones.
🔸 Optimization Capabilities
1. Auto-Optimizer:
The backtester includes an auto-optimizer feature that evaluates various setups to find those with the best historical performance.
It automatically adjusts parameters to identify the most effective strategies for both trend-following and counter-trend trading.
2. Stop Loss and Take Profit Optimization:
It optimizes stop-loss and take-profit levels by testing different settings and identifying those that provided the best historical results.
This helps traders refine their risk management and maximize potential returns.
3. Trailing Stop Optimization:
The system also optimizes trailing stops, ensuring that traders can maximize their profits by adjusting their stops dynamically as the market moves.
🔸 Comprehensive Reporting
1. Performance Metrics:
The backtesting system provides detailed reports, including key performance metrics such as Net Profit, Win Rate, Profit Factor, and Max Drawdown.
These metrics help traders understand the historical performance of their strategies and make data-driven decisions.
2. Flexible Settings:
Traders can adjust initial balance, commission rates, and risk per trade settings to simulate real-world trading conditions.
The system supports testing with different leverage settings, allowing for realistic assessments even with tight stop-loss levels.
🔸 Conclusion
The RunRox Backtesting System (ASMC) is a powerful tool for traders seeking to validate and optimize their SMC strategies. By leveraging historical data and sophisticated optimization algorithms, it provides insights into the most effective setups, enhancing trading performance and decision-making.
🟠 HERE ARE THE AVAILABLE FEATURES
Historical backtesting for any setup – Select any entry point, exit point, and various stop-loss options to see the results of your setup on historical data.
Auto-optimizer for finding the best setups – The indicator displays settings that have shown the best results historically, providing valuable insights.
Auto-optimizer for counter-trend setups – Discover entry and exit points for counter-trend trading based on historical performance.
Auto-optimizer for stop-loss – The indicator shows stop-loss points that have been most effective historically.
Auto-optimizer for take-profit – The indicator identifies take-profit points that have performed well in historical trading data.
Auto-optimizer for trailing stop – The indicator presents trailing stop settings that have shown the best historical results.
And much more within our indicator, all of which we will cover in this post. Next, we will showcase the possible entry points, targets, and stop-loss options available for testing your strategies
🟠 ENTRY SETTINGS
12 Event Triggers for Trade Entry
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Trade Direction Options
Long Only: Enter long positions only
Short Only: Enter short positions only
Long and Short: Enter both long and short positions based on trend
3 Levels for Order Block/FVG Entries
Beginning: Enter the trade at the first touch of the Order Block/FVG
Middle: Enter the trade when the middle of the Order Block/FVG is reached
End: Enter the trade upon full filling of the Order Block/FVG
*Three levels work only for Order Blocks and FVG. For trade entries based on BOS or CHoCH, these settings do not apply as these parameters are not available for these types of entries
You can choose any combination of trade entries imaginable.
🟠 TARGET SETTINGS
14 Target Events, Including Fixed % and Fixed RR (Risk/Reward):
Fixed - % change in price
Fixed RR - Risk Reward per trade
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels of Order Block/FVG for Target
Beginning: Close the trade at the first touch of your target.
Middle: Close the trade at the midpoint of your chosen target.
End: Close the trade when your target is fully filled.
Customizable Parameters
Easily set your Fixed % and Fixed RR targets with a user-friendly input field. This field works only for the Fixed and Fixed RR entry parameters. When selecting a different entry point, this field is ignored
Choose any combination of target events to suit your trading strategy.
🟠 STOPLOSS SETTINGS
14 Possible StopLoss Events Including Entry Orderblock/FVG
Fixed - Fix the loss on the trade when the price moves by N%
Entry Block
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels for Order Blocks/FVG Exits
Beginning: Exit the trade at the first touch of the order block/FVG.
Middle: Exit the trade at the middle of the order block/FVG.
End: Exit the trade at the full completion of the order block/FVG.
Dedicated Field for Setting Fixed % Value
Set a fixed % value in a dedicated field for the Fixed parameter. This field works only for the Fixed parameter. When selecting other exit parameters, this field is ignored.
🟠 ADDITIONAL SETTINGS
Trailing Stop, %
Set a Trailing Stop as a percentage of your trade to potentially increase profit based on historical data.
Move SL to Breakeven, bars
Move your StopLoss to breakeven after exiting the entry zone for a specified number of bars. This can enhance your potential WinRate based on historical performance.
Skip trade if RR less than
This feature allows you to skip trades where the potential Risk-to-Reward ratio is less than the number set in this field.
🟠 EXAMPLE OF MANUAL SETUP
For example, let me show you how it works on the chart. You select entry parameters, stop loss parameters, and take profit parameters for your trades, and the strategy automatically tests this setup on historical data, allowing you to see the results of this strategy.
In the screenshot above, the parameters were as follows:
Trade Entry: CHoCH OB (Beginning)
Stop Loss: Entry Block
Take Profit: Break of BOS
The indicator will automatically test all possible trades on the chart and display the results for this setup.
🟠 AUTO OPTIMIZATION SETTINGS
In the screenshot above, you can see the optimization table displaying various entry points, exits, and stop-loss settings, along with their historical performance results and other parameters. This feature allows you to identify trading setups that have shown the best historical outcomes.
This functionality will enhance your trading approach, providing you with valuable insights based on historical data. You’ll be aware of the Smart Money Concept settings that have historically worked best for any specific chart and timeframe.
Our indicator includes various optimization options designed to help you find the most effective settings based on historical data. There are 5 optimization modes, each offering unique benefits for every trader
Trend Entry - Optimization of the best settings for trend-following trades. The strategy will enter trades only in the direction of the trend. If the trend is upward, it will look for long entry points and vice versa.
Counter Trend Entry - Finding setups against the trend. If the trend is upward, the script will search for short entry points. This is the opposite of trend entry optimization.
Stop Loss - Identifying stop-loss points that showed the best historical performance for the specific setup you have configured. This helps in finding effective exit points to minimize losses.
Take Profit - Determining targets for the configured setup based on historical performance, helping to identify potentially profitable take profit levels.
Trailing Stop - Finding optimal percentages for the trailing stop function based on historical data, which can potentially increase the profit of your trades.
Ability to set parameters for auto-optimization within a specified range. For example, if you choose FixRR TP from 1 to 10, the indicator will automatically test all possible Risk Reward Take Profit variations from 1 to 10 and display the results for each parameter individually.
Ability to set initial deposit parameters, position commissions, and risk per trade as a fixed percentage or fixed amount. Additionally, you can set the maximum leverage for a trade.
There are times when the stop loss is very close to the entry point, and adhering to the risk per trade values set in the settings may not allow for such a loss in any situation. That’s why we added the ability to set the maximum possible leverage, allowing you to test your trading strategy even with very tight stop losses.
Duplicated Smart Money Structure settings from our Advanced SMC indicator that you can adjust to match your trading style flexibly. All these settings will be taken into account during the optimization process or when manually calculating settings.
Additionally, you can test your strategy based on higher timeframe order blocks. For example, you can test a strategy on a 1-minute chart while displaying order blocks from a 15-minute timeframe. The auto-optimizer will consider all these parameters, including higher timeframe order blocks, and will enter trades based on these order blocks.
Highly flexible dashboard and results optimization settings allow you to display the tables you need and sort results by six different criteria: Profit Factor, Profit, Winrate, Max Drawdown, Wins, and Trades. This enables you to find the exact setup you desire, based on these comprehensive data points.
🟠 ALERT CUSTOMIZATION
With this indicator, you can set up buy and sell alerts based on the test results, allowing you to create a comprehensive trading strategy. This feature enables you to receive real-time signals, making it a powerful tool for implementing your trading strategies.
🟠 STRATEGY PROPERTIES
For backtesting, we used realistic initial data for entering trades, such as:
Starting balance: $1000
Commission: 0.01%
Risk per trade: 1%
To ensure realistic data, we used the above settings. We offer two methods for calculating your order size, and in our case, we used a 1% risk per trade. Here’s what it means:
Risk per trade: This is the maximum loss from your deposit if the trade goes against you. The trade volume can change depending on your stop-loss distance from the entry point. Here’s the formula we use to calculate the possible volume for a single trade:
1. quantity = percentage_risk * balance / loss_per_1_contract (incl. fee)
Then, we calculate the maximum allowed volume based on the specified maximum leverage:
2. max_quantity = maxLeverage * balance / entry_price
3. If quantity < max_quantity, meaning the leverage is less than the maximum allowed, we keep quantity. If quantity > max_quantity, we use max_quantity (the maximum allowed volume according to the set leverage).
This way, depending on the stop-loss distance, the position size can vary and be up to 100% of your deposit, but the loss in each trade will not exceed the set percentage, which in our case is 1% for this backtest. This is a standard risk calculation method based on your stop-loss distance.
🔸 Statistical Significance of Trade Data
In our strategy, you may notice there weren’t enough trades to form statistically significant data. This is inherent to the Smart Money Concept (SMC) strategy, where the focus is not on the number of trades but rather on the risk-to-reward ratio per trade. In SMC strategies, it’s crucial to avoid taking numerous uncertain setups and instead perform a comprehensive analysis of the market situation.
Therefore, our strategy results show fewer than 100 trades. It’s important to understand that this small sample size isn’t statistically significant and shouldn’t be relied upon for strategy analysis. Backtesting with a small number of trades should not be used to draw conclusions about the effectiveness of a strategy.
🔸 Versatile Use Cases
The methods of using this indicator are numerous, ranging from identifying potentially the best-performing order blocks on the chart to creating a comprehensive trading strategy based on the data provided by our indicator. We believe that every trader will find a valuable application for this tool, enhancing their entry and exit points in trades.
Disclaimer
Past performance is not indicative of future results. The results shown by this indicator do not guarantee similar outcomes in the future. Use this tool as part of a comprehensive trading strategy, considering all market conditions and risks.
How to access
For access to this indicator, please read the author’s instructions below this post
PFCF Price BandPFCF Price Band shows price calculated using the previous period's high and low P/TTM FCFPS (TTM's price to free cash flow per share over the last 12 months) multiplied by TTM's current FCFPS ( Similar to price theory = P/E x expected earnings per share)
If the current P/FCFPS is lower than the minimum P/FCFPS, it is considered cheap. In other words, above the maximum P/FCFPS is considered expensive.
PFCF Price Band consists of 2 parts.
- Firstly, the historical P/FCFPS value in "Green" (if TTM FCFPS is positive) or "Red" (if TTM FCFPS is negative) status changes based on the latest high or low price of TTM FCFPS.
- Second, the blue line is the closing price divided by TTM FCFPS, which shows the current P/FCF.
P.S. It is recommended to use it together with the PE Band indicator because just net profit does not mean that a company has good cash flow.
ΔYoY(Economics)Year over year indicator which will benchmark the most recent data vs 1 year lookback; Will automate the lookback for quarterly and monthly data based on timeframe selected (3M for quarterly, 1M for monthly). Tradingview will aggregate weekly data into a monthly data point. SMA applied to get the average over some x period.
Ln(close)Natural log indicator for normalizing data. SMA applied so you can take the average of that normalization factor. Personally use it for US economic data where the value is very large (GDI, Fed Balance Sheet, USM2 etc.) and the year over year delta is not pertinent (USM2) or not available (GDI.. although I did make an indicator to get YoY :D). Any additional ideas leave a comment and I'll take a look.
MarketcapDefinition
This indicator was designed to reveal the relationship between the price of the product and its market value. The red average marketcap line that appears on the chart is the line. And the further up this line moves from the chart, the more it shows that there is a mismatch between the price and the market value. So what does this incompatibility mean? There are purchases of the product, but since the supply of the product into circulation is constantly increasing, it means that these purchases are not reflected in the price, which means there is inflation.
The main purpose of our indicator is to calculate inflation of the product. It is the understanding of whether or not the amount of supply put into circulation in response to the investment is reflected in the product price while increasing the market value.
Attention: Transactions are made based on the data received via CRYPTOCAP. In cases where this data cannot be received, the "UNSUPPORTED SOURCE" warning is displayed. You can use Settings to change the source from which data can be retrieved.
Labels
The labels are explained one by one below.
MARKETCAP: Shows the current market value.
ATH MARKETCAP: Shows the highest market value of all time.
MARKETCAP RATIO: It gives the ratio between the highest level and the lowest level of the market value.
PRICE RATIO: Gives the ratio between the highest level and the lowest level of the crypto price.
ALL INFLATION PERCENT: It refers to the percentage of all inflation that has developed so far. It is also the percentage difference between market value and price.
MONTHLY INFLATION PERCENT: It refers to the monthly estimated inflation percentage.
CIRCULATING SUPPLY: It refers to the estimated circulation supply of the product.
Best Use
It should bring to mind the idea that the further the indicator curve moves away from the price, the higher the inflation will be. In order for a product to reach its previous peak, its market value must normally increase by the "MARKETCAP RATIO" value and the "PRICE RATIO" value. This should make you think that this product needs more investment to reach its former peak. And it is necessary to be careful when purchasing such products.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
Analyst Table (Zeiierman)█ Overview
The Analyst Table (Zeiierman) provides a comprehensive visual representation of analyst estimates and recommendations for any stock. This indicator displays crucial analyst data, including the highest, average, and lowest price targets, directly on the price chart. Additionally, it features a well-organized table summarizing various types of analyst recommendations, offering traders valuable insights into market sentiment and expectations. This tool is ideal for traders seeking a quick overview of analyst opinions and recommendations on specific stocks.
█ How It Works
The indicator works by retrieving analyst data such as price targets and recommendations from the TradingView data feed. It visually represents these estimates on the chart and creates a structured table for easy reference, consolidating all the information in an organized format.
Key Components:
High Estimate Line: A dotted line representing the highest price target.
Low Estimate Line: A dotted line representing the lowest price target.
Target Estimate Box: A box representing the range between the average and median price targets.
Analyst Table: A table displaying detailed information about various analyst recommendations and price targets.
█ How to Use
Traders can use this indicator to gain insights into the expectations of financial analysts regarding the future performance of an asset. By observing the highest, lowest, and average price targets, traders can assess the range of possible future prices as predicted by analysts. The recommendation table helps in understanding the general sentiment among analysts, whether it's bullish, bearish, or neutral.
Visual Analysis: Use the visual indicators to quickly gauge where the current price stands relative to analyst targets.
Sentiment Assessment: Refer to the table to understand the distribution of buy, hold, and sell recommendations.
█ Settings
The indicator settings allow users to enable or disable different target lines, select colors for the lines and table cells, and choose the position and size of the analyst table on the chart.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Earnings X-RayThe script presents earnings and revenues in a tabular format. Particularly, it calculates percentage changes.
Earnings data can be found in TradingView Financials. However, percentage changes are not provided. Can TradingView implement this in the future?
Displaying earnings table on the chart has its benefits. No additional clicks required to access the data. This significantly streamlines the stock scanning process.
It is important to quickly evaluate a company's earnings when scanning for stocks. The script provides this capability.
Similar scripts have been created previously. This script corrects calculations and improves presentation with the concise code.
Data access:
Earnings = request.earnings(syminfo.tickerid, earnings.actual)
FutureEarnings = earnings.future_eps
FutureRevenue = earnings.future_revenue
Can more than one quarter of future earnings estimates become available in Pine Script in the future?
The script was validated against MarketSurge.
Features:
Quarterly or Yearly data
Configurable number of fiscal periods
Configurable location on the chart
Optional Dark mode
[INVX] P/E band (panel)What is it?
The P/E Bollinger Band indicator is a hybrid tool combining fundamental analysis (P/E ratio) with technical analysis (Bollinger Bands).
It uses Bollinger Bands around a company's P/E ratio to identify potentially overvalued or undervalued zones.
The P/E ratio itself measures a stock's price relative to its earnings per share.
The Bollinger Bands, based on standard deviations, create a dynamic upper and lower band around the average P/E ratio.
Why P/E Bollinger Band?
Provides a visual representation of a company's relative valuation compared to its historical P/E range.
Can help identify areas where the P/E ratio might be deviating significantly from its historical norm.
Who should use it
Investors who combine technical and fundamental analysis for a more comprehensive stock evaluation.
Value investors seeking to identify potentially undervalued companies.
How to use
A P/E value that breaches the upper Bollinger Band suggests potential overvaluation, indicating the stock might be due for a price correction.
Conversely, a P/E value that falls below the lower Bollinger Band might signal undervaluation, presenting a potential buying opportunity (considering the company's fundamentals remain sound).
[INVX] P/E band (overlay)What is it?
The P/E Bollinger Band indicator is a hybrid tool combining fundamental analysis (P/E ratio) with technical analysis (Bollinger Bands).
It uses Bollinger Bands around a company's P/E ratio to identify potentially overvalued or undervalued zones.
The P/E ratio itself measures a stock's price relative to its earnings per share.
The Bollinger Bands, based on standard deviations, create a dynamic upper and lower band around the average P/E ratio.
Why P/E Bollinger Band?
Provides a visual representation of a company's relative valuation compared to its historical P/E range.
Can help identify areas where the P/E ratio might be deviating significantly from its historical norm.
Who should use it
Investors who combine technical and fundamental analysis for a more comprehensive stock evaluation.
Value investors seeking to identify potentially undervalued companies.
How to use
A P/E value that breaches the upper Bollinger Band suggests potential overvaluation, indicating the stock might be due for a price correction.
Conversely, a P/E value that falls below the lower Bollinger Band might signal undervaluation, presenting a potential buying opportunity (considering the company's fundamentals remain sound).
Sharpe RatioThe Sharpe Ratio Indicator is a widely-used tool designed to measure the risk-adjusted performance of an asset. The Sharpe Ratio helps investors understand how much excess return they are receiving for the extra volatility endured for holding a riskier asset. By comparing the return of an investment to the risk-free rate and accounting for the volatility of the investment's returns, the Sharpe Ratio provides a clear metric for evaluating the return on investment per unit of risk.
Features:
Calculation Period Input: Allows users to specify the period over which the Sharpe Ratio is calculated, making it flexible and adaptable to various trading strategies and time frames.
Risk-Free Rate Input: Users can set a specific risk-free rate, enabling a customized risk-return analysis based on prevailing market conditions or individual investment preferences.
Daily Returns Calculation: The indicator calculates daily returns, which are used to determine the mean return and standard deviation.
Sharpe Ratio Calculation: The indicator calculates the Sharpe Ratio by dividing the excess return (mean return minus risk-free rate) by the standard deviation of returns and annualizing the result (assuming 252 trading days in a year).
Visual Plot: The Sharpe Ratio is plotted on the chart, with a reference zero line to help users quickly assess whether the asset's returns are favorable relative to the risk-free rate.
How to Use:
Add the Indicator to Your Chart: Copy the script into the Pine Script editor on TradingView and add it to your chart.
Specify the Calculation Period: Adjust the Calculation Period input to match your desired time frame for the Sharpe Ratio calculation.
Set the Risk-Free Rate: Input the current risk-free rate (e.g., the yield on 10-year government bonds) to customize the risk-return analysis.
Interpret the Sharpe Ratio: A higher Sharpe Ratio indicates better risk-adjusted performance, while a ratio below zero suggests that the asset has underperformed relative to the risk-free rate.
Omega RatioThe Omega Ratio Indicator is a powerful tool designed to measure the risk-adjusted performance of an asset. Unlike traditional measures like the Sharpe or Sortino Ratios, the Omega Ratio considers both the frequency and magnitude of returns above and below a specified target return, providing a more comprehensive view of an asset's performance. This makes it an ideal choice for traders and investors seeking to evaluate the probability of achieving a desired return relative to the risk taken.
Features:
Calculation Period Input: Allows users to specify the period over which the Omega Ratio is calculated, making it flexible and adaptable to various trading strategies and time frames.
Target Return Input: Users can set a specific target return, enabling a customized risk-return analysis based on individual investment goals.
Daily Returns Calculation: The indicator calculates daily returns, which are used to determine the cumulative returns above and below the target return.
Omega Ratio Calculation: By dividing the cumulative returns above the target return by the cumulative returns below it, the indicator provides a clear measure of the likelihood of achieving the target return.
Visual Plot: The Omega Ratio is plotted on the chart, with a reference line at 1, helping users quickly assess whether the asset's returns are favorable relative to the target.
How to Use:
Add the Indicator to Your Chart: Copy the script into the Pine Script editor on TradingView and add it to your chart.
Specify the Calculation Period: Adjust the Calculation Period input to match your desired time frame for the Omega Ratio calculation.
Set the Target Return: Input your desired target return to customize the risk-return analysis.
Interpret the Omega Ratio: An Omega Ratio greater than 1 indicates that the asset's returns are more likely to exceed the target return than to fall short, whereas a ratio less than 1 suggests the opposite.
Sortino RatioThe Sortino Ratio Indicator is a custom script developed to measure the risk-adjusted performance of an asset. Unlike the Sharpe Ratio, which penalizes both upside and downside volatility equally, the Sortino Ratio specifically differentiates between harmful volatility (downside risk) and overall volatility. This makes it a preferred choice for traders and investors who are particularly concerned with downside risk.
Features:
Calculation Period Input: Users can specify the period over which the Sortino Ratio is calculated, making it adaptable to different time frames and trading strategies.
Daily Returns Calculation: The indicator calculates daily returns using logarithmic returns, which provides a more accurate reflection of percentage changes in price.
Mean Return and Downside Deviation: The script calculates the mean of daily returns and the downside deviation, focusing only on negative returns that fall below the mean.
Annualized Sortino Ratio: The Sortino Ratio is annualized assuming 252 trading days in a year, providing a standardized measure that can be easily compared across different assets and time periods.
Visual Plot: The indicator plots the Sortino Ratio on the chart, with a reference zero line to help users quickly assess the performance relative to the risk-free rate.
How to Use:
Add the Indicator to Your Chart: Copy the script into the Pine Script editor on TradingView and add it to your chart.
Specify the Calculation Period: Adjust the Calculation Period input to match your desired time frame for the Sortino Ratio calculation.
Interpret the Sortino Ratio: A higher Sortino Ratio indicates better risk-adjusted performance, while a ratio below zero suggests that the asset has underperformed relative to its downside risk.
FaikValThe "FaikVal" indicator is a powerful tool designed to help traders analyze relative price movements between a base asset and up to three comparison assets. This indicator uses exponential moving averages (EMA) and normalization techniques to identify potential overbought and oversold situations.
Functions and Applications:
Comparison of Price Ratios: The indicator calculates the ratio of the closing price of the base asset to the closing prices of three user-defined comparison assets. This allows for direct comparative analysis and helps identify relative strengths and weaknesses.
EMA Calculations: Two EMAs are calculated for each price ratio (with configurable periods). The difference between these two EMAs serves as the basis for further calculations.
Normalization: The calculated values are normalized over a defined period, helping to smooth out extreme values and facilitate analysis. This normalization transforms the values onto a scale from -100 to 100.
Optional Smoothing: Optional smoothing of the normalized values can be enabled to further reduce short-term fluctuations and generate clearer signals.
Visual Signals: The indicator plots three lines (one for each comparison ratio), representing the normalized values. Additionally, horizontal lines are displayed at +60, -60, and 0 to mark overbought and oversold zones as well as neutral areas.
Customizability: Users can adjust the periods of the EMAs, the length of the normalization period, and the smoothing period. They can also specify which of the three indicators should be displayed.
Applications:
Relative Strength Analysis: Identify whether the base asset is performing stronger or weaker compared to other markets or instruments.
Trend Confirmation: Confirm existing trends by analyzing the movements of the base asset relative to the comparison assets.
Overbought and Oversold Signals: Use the displayed values and horizontal lines to identify potential market turning points and determine entry or exit points.
!!! It works best on the weekly and daily chart for swing trading. It is a set up tool, to determin weather you should go long or short and not a market timing tool. For timing you could use concepts like trend and supply and demand!!!
The "FaikVal" indicator offers versatile and detailed analysis, making it particularly useful for traders seeking deeper insights into relative price strength and weakness.
Intelle_city - World Cycle - Ath & Atl - Logarithmic - Strategy.Overview
Indicators: Strategy !
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for a buy-sell strategy; there is also a signal indicator from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для стратегии покупок продаж, есть также и сигнальный от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Strategy – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator ist für eine Kauf-Verkaufs-Strategie konzipiert; es gibt auch einen Signalindikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
intellect_city - World Cycle - Ath & Atl - Logarithmic - Signal.Indicator Overview
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for signal purchases of sales, there is also a strategic one from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
-----------------------------
Описание на русском:
-----------------------------
Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для сигнальных покупок продаж, есть также и стратегический от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
-----------------------------
Beschreibung - Deutsch
-----------------------------
Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Signal – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator dient zur Signalisierung von Käufen oder Verkäufen, es gibt auch einen strategischen Indikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Auto Gann KEYLVLS "Auto Gann KEYLVLS" indicator can be a valuable tool for traders, especially those who employ Gann theory in their analysis. Here are some ways to effectively use this indicator:
Identifying Key Price Levels: Gann lines are known for their ability to identify key support and resistance levels. Use the plotted Gann lines to identify significant price levels where the market may react.
Confirmation of Trend Reversals: When price approaches a Gann line, observe how the price reacts. A bounce off a Gann line can confirm the continuation of the trend, while a break of a Gann line may indicate a potential trend reversal.
Entry and Exit Points: Gann lines can serve as entry and exit points for trades. Look for confluence between Gann lines and other technical indicators or patterns to identify high-probability trade setups.
Trading with the Trend: In an uptrend, consider buying opportunities near Gann support levels, while in a downtrend, look for selling opportunities near Gann resistance levels.
Risk Management: Use Gann lines to set stop-loss and take-profit levels. Place stop-loss orders below Gann support levels for long trades and above Gann resistance levels for short trades to manage risk effectively.
Timeframe Analysis: Utilize the flexibility of this indicator to plot Gann lines on different timeframes. Compare Gann lines across multiple timeframes to identify alignment or divergence, which can provide additional confirmation for trading decisions.
Combination with Other Indicators: Combine the information provided by Gann lines with other technical indicators, such as moving averages, RSI, or MACD, to strengthen your trading decisions.
Input Parameters:
The script defines several input parameters that control the behavior of the Gann lines, such as the number of weeks to look back for highs and lows, the number of Gann lines to plot, line extension settings, and options to show or hide specific Gann lines like .25, .37, .50, .63, and .75.
Auto Gann Functionality:
The script calculates the highest high and lowest low for the specified number of weeks, hours, and minutes.
It then calculates quartile levels (0.25, 0.50, 0.75) based on the weekly high and low.
Gann lines are drawn based on these levels, with options to extend them left and/or right.
Labels are added to the Gann lines indicating their values.
Weekly Gann Lines:
The script plots Gann lines and labels based on the weekly high and low levels.
Labels are added to these lines indicating their values.
Sub Gann Lines:
Additional Gann lines are plotted based on the weekly high and low levels, with subdivisions for lower timeframes like H4, H1, M15, and M1.
Label Management:
Labels are managed based on user preferences, including options to show labels once on the left side, redraw labels on the right side, or not show labels at all.
Intellect_city - World Cycle - Ath - Timeframe 1D and 1WIndicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA, not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. However, in this instance, it does so with a high degree of accuracy over Bitcoin's adoption phase of growth.
Bitcoin Price Prediction Using This Tool
The Pi Cycle Top Indicator forecasts the cycle top of Bitcoin’s market cycles. It attempts to predict the point where Bitcoin price will peak before pulling back. It does this on major high time frames and has picked the absolute tops of Bitcoin’s major price moves throughout most of its history.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter-term moving average, which is the 111-day moving average, has reached an x2 multiple of the 350-day moving average. Historically, it has proved advantageous to sell Bitcoin around this time in Bitcoin's price cycles.
It is also worth noting that this indicator has worked during Bitcoin's adoption growth phase, the first 15 years or so of Bitcoin's life. With the launch of Bitcoin ETF's and Bitcoin's increased integration into the global financial system, this indicator may cease to be relevant at some point in this new market structure.
Intellect_city - Halvings Bitcoin CycleWhat is halving?
The halving timer shows when the next Bitcoin halving will occur, as well as the dates of past halvings. This event occurs every 210,000 blocks, which is approximately every 4 years. Halving reduces the emission reward by half. The original Bitcoin reward was 50 BTC per block found.
Why is halving necessary?
Halving allows you to maintain an algorithmically specified emission level. Anyone can verify that no more than 21 million bitcoins can be issued using this algorithm. Moreover, everyone can see how much was issued earlier, at what speed the emission is happening now, and how many bitcoins remain to be mined in the future. Even a sharp increase or decrease in mining capacity will not significantly affect this process. In this case, during the next difficulty recalculation, which occurs every 2014 blocks, the mining difficulty will be recalculated so that blocks are still found approximately once every ten minutes.
How does halving work in Bitcoin blocks?
The miner who collects the block adds a so-called coinbase transaction. This transaction has no entry, only exit with the receipt of emission coins to your address. If the miner's block wins, then the entire network will consider these coins to have been obtained through legitimate means. The maximum reward size is determined by the algorithm; the miner can specify the maximum reward size for the current period or less. If he puts the reward higher than possible, the network will reject such a block and the miner will not receive anything. After each halving, miners have to halve the reward they assign to themselves, otherwise their blocks will be rejected and will not make it to the main branch of the blockchain.
The impact of halving on the price of Bitcoin
It is believed that with constant demand, a halving of supply should double the value of the asset. In practice, the market knows when the halving will occur and prepares for this event in advance. Typically, the Bitcoin rate begins to rise about six months before the halving, and during the halving itself it does not change much. On average for past periods, the upper peak of the rate can be observed more than a year after the halving. It is almost impossible to predict future periods because, in addition to the reduction in emissions, many other factors influence the exchange rate. For example, major hacks or bankruptcies of crypto companies, the situation on the stock market, manipulation of “whales,” or changes in legislative regulation.
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Table - Past and future Bitcoin halvings:
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Date: Number of blocks: Award:
0 - 03-01-2009 - 0 block - 50 BTC
1 - 28-11-2012 - 210000 block - 25 BTC
2 - 09-07-2016 - 420000 block - 12.5 BTC
3 - 11-05-2020 - 630000 block - 6.25 BTC
4 - 20-04-2024 - 840000 block - 3.125 BTC
5 - 24-03-2028 - 1050000 block - 1.5625 BTC
6 - 26-02-2032 - 1260000 block - 0.78125 BTC
7 - 30-01-2036 - 1470000 block - 0.390625 BTC
8 - 03-01-2040 - 1680000 block - 0.1953125 BTC
9 - 07-12-2043 - 1890000 block - 0.09765625 BTC
10 - 10-11-2047 - 2100000 block - 0.04882813 BTC
11 - 14-10-2051 - 2310000 block - 0.02441406 BTC
12 - 17-09-2055 - 2520000 block - 0.01220703 BTC
13 - 21-08-2059 - 2730000 block - 0.00610352 BTC
14 - 25-07-2063 - 2940000 block - 0.00305176 BTC
15 - 28-06-2067 - 3150000 block - 0.00152588 BTC
16 - 01-06-2071 - 3360000 block - 0.00076294 BTC
17 - 05-05-2075 - 3570000 block - 0.00038147 BTC
18 - 08-04-2079 - 3780000 block - 0.00019073 BTC
19 - 12-03-2083 - 3990000 block - 0.00009537 BTC
20 - 13-02-2087 - 4200000 block - 0.00004768 BTC
21 - 17-01-2091 - 4410000 block - 0.00002384 BTC
22 - 21-12-2094 - 4620000 block - 0.00001192 BTC
23 - 24-11-2098 - 4830000 block - 0.00000596 BTC
24 - 29-10-2102 - 5040000 block - 0.00000298 BTC
25 - 02-10-2106 - 5250000 block - 0.00000149 BTC
26 - 05-09-2110 - 5460000 block - 0.00000075 BTC
27 - 09-08-2114 - 5670000 block - 0.00000037 BTC
28 - 13-07-2118 - 5880000 block - 0.00000019 BTC
29 - 16-06-2122 - 6090000 block - 0.00000009 BTC
30 - 20-05-2126 - 6300000 block - 0.00000005 BTC
31 - 23-04-2130 - 6510000 block - 0.00000002 BTC
32 - 27-03-2134 - 6720000 block - 0.00000001 BTC
Stock Rating [TrendX_]# OVERVIEW
This Stock Rating indicator provides a thorough evaluation of a company (NON-FINANCIAL ONLY) ranging from 0 to 5. The rating is the average of six core financial metrics: efficiency, profitability, liquidity, solvency, valuation, and technical ratings. Each metric encompasses several financial measurements to ensure a robust and holistic evaluation of the stock.
## EFFICIENCY METRICS
1. Asset-to-Liability Ratio : Measures a company's ability to cover its liabilities with its assets.
2. Equity-to-Liability Ratio : Indicates the proportion of equity used to finance the company relative to liabilities.
3. Net Margin : Shows the percentage of revenue that translates into profit.
4. Operating Expense : Reflects the costs required for normal business operations.
5. Operating Expense Ratio : Compares operating expenses to total revenue.
6. Operating Profit Ratio : Measures operating profit as a percentage of revenue.
7. PE to Industry Relative PE/PB : Compares the company's PE ratio to the industry average.
## PROFITABILITY METRICS
1. ROA : Indicates how efficiently a company uses its assets to generate profit.
2. ROE : Measures profitability relative to shareholders' equity.
3. EBITDA : Reflects a company's operational profitability.
4. Free Cash Flow Margin : Shows the percentage of revenue that remains as free cash flow.
5. Revenue Growth : Measures the percentage increase in revenue over a period.
6. Gross Margin : Reflects the percentage of revenue exceeding the cost of goods sold.
7. Net Margin : Percentage of revenue that is net profit.
8. Operating Margin : Measures the percentage of revenue that is operating profit.
## LIQUIDITY METRICS
1. Current Ratio : Indicates the ability to cover short-term obligations with short-term assets.
2. Interest Coverage Ratio : Measures the ability to pay interest on outstanding debt.
3. Debt-to-EBITDA : Compares total debt to EBITDA.
4. Debt-to-Equity Ratio : Indicates the relative proportion of debt and equity financing.
## SOLVENCY METRICS
1. Altman Z-score : Predicts bankruptcy risk
2. Beneish M-score : Detects earnings manipulation.
3. Fulmer H-factor : Predicts business failure risk.
## VALUATION METRICS
1. Industry Relative PE/PB Comparison : Compares the company's PE and PB ratios to industry averages.
2. Momentum of PE, PB, and EV/EBITDA Multiples : Tracks the trends of PE, PB, and EV/EBITDA ratios over time.
## TECHNICAL METRICS
1. Relative Strength Index (RSI) : Measures the speed and change of price movements.
2. Supertrend : Trend-following indicator that identifies market trends.
3. Moving Average Golden-Cross : Occurs when a short-term MA crosses above mid-term and long-term MA which are determined by half-PI increment in smoothing period.
4. On-Balance Volume Golden-Cross : Measures cumulative buying and selling pressure.
[InvestorUnknown] Performance MetricsOverview
The Performance Metrics indicator is a tool designed to help traders and investors understand and utilize key performance metrics in their strategies. This indicator is inspired by the Rolling Risk-Adjusted Performance Ratios created by @EliCobra, but it offers enhanced usability and additional features to provide a more user-friendly code for understanding the calculations.
Features
Rolling Lookback:
Dynamic Lookback Calculation: The indicator automatically calculates the number of bars from the start of the asset's price history, up to a maximum of 5000 bars due to TradingView platform restrictions.
Adjustable Lookback Period: Users can manually set a lookback period or choose to use the rolling lookback feature for dynamic calculations.
RollingLookback() =>
x = bar_index + 1
y = x > 4999 ? 5000 : x > 1 ? (x - 1) : x
y
Trend Analysis
The Trend Analysis section in this indicator helps traders identify the direction of the market trend based on the balance of positive and negative returns over time. This is achieved by calculating the sums of positive and negative returns and optionally smoothing these values to provide a clearer trend signal.
Configuration: Enable smoothing if you want to reduce noise in the trend analysis. Choose between EMA and SMA for smoothing. Set the length for smoothing according to your preference for sensitivity (shorter lengths are more sensitive to changes, longer lengths provide smoother signals).
Interpretation:
- A positive trend difference (filled with green) indicates a bullish trend, suggesting more positive returns.
- A negative trend difference (filled with red) indicates a bearish trend, suggesting more negative returns.
- Colored bars provide a quick visual cue on the trend direction, helping to make timely trading decisions.
// The Trend Analysis section calculates and optionally smooths the sums of positive and negative returns.
// This helps identify the trend direction based on the balance of positive and negative returns over time.
Ps = Smooth ? Smooth_type == "EMA" ? ta.ema(pos_sum, Smooth_len) : ta.sma(pos_sum, Smooth_len) : pos_sum
Ns = Smooth ? Smooth_type == "EMA" ? ta.ema(neg_sum, Smooth_len) : ta.sma(neg_sum, Smooth_len) : neg_sum
// Calculate the difference between smoothed positive and negative sums
dif = Ps + Ns
Performance Metrics Table
Visual Table Display: Option to display a table on the chart with calculated performance metrics. This table includes comprehensive metrics like Mean Return, Positive and Negative Mean Return, Standard Deviation, Sharpe Ratio, Sortino Ratio, and Omega Ratio.
Performance Metrics Calculated
Mean Return:
Description: The average return over the lookback period.
Purpose: Helps in understanding the overall performance of the asset by providing a simple average of returns.
Positive Mean Return:
Description: The average of all positive returns over the lookback period.
Purpose: Highlights the average gain during profitable periods, giving insight into the asset's potential upside.
Negative Mean Return:
Description: The average of all negative returns over the lookback period.
Purpose: Focuses on the average loss during unprofitable periods, helping to assess the downside risk.
Standard Deviation (STDEV):
Description: A measure of volatility that calculates the dispersion of returns from the mean.
Purpose: Indicates the risk associated with the asset. Higher standard deviation means higher volatility and risk.
Sharpe Ratio:
Description: A risk-adjusted return metric that divides the mean return by the standard deviation of returns. It can be annualized if selected.
Purpose: Provides a standardized way to compare the performance of different assets by considering both return and risk. A higher Sharpe Ratio indicates better risk-adjusted performance.
sharpe_ratio = mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1)
Sortino Ratio:
Description: Similar to the Sharpe Ratio but focuses only on downside volatility. It divides the mean return by the standard deviation of negative returns. It can be annualized if selected.
Purpose: Offers a better assessment of downside risk by ignoring upside volatility. A higher Sortino Ratio indicates a higher return per unit of downside risk.
sortino_ratio = mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1)
Omega Ratio:
Description: The ratio of the probability-weighted average of positive returns to the probability-weighted average of negative returns.
Purpose: Measures the overall likelihood of positive returns compared to negative returns. An Omega Ratio greater than 1 indicates more frequent and/or larger positive returns compared to negative returns.
omega_ratio = (prob_pos * mean_pos) / (prob_neg * -mean_neg)
By calculating and displaying these metrics, the indicator provides a comprehensive view of the asset's performance, enabling traders and investors to make informed decisions based on both returns and risk-adjusted metrics.
Use Cases:
Performance Evaluation: Assesses an asset's performance by analyzing both returns and risk factors, giving a clear picture of profitability and volatility.
Risk Comparison: Compares the risk-adjusted returns of different assets or portfolios, aiding in identifying investments with superior risk-reward trade-offs.
Risk Management: Helps manage risk exposure by evaluating downside risks and overall volatility, enabling more informed and strategic investment decisions.
PE BandThe PE Band shows the highest and lowest P/E in the previous period with TTM EPS. If the current P/E is lower than the minimum P/E, it is considered cheap. In other words, higher than the maximum P/E is considered expensive.
PE Band consists of 2 lines.
- Firstly, the historical P/E value in "green" (if TTM EPS is positive) or "red" (if TTM EPS is negative) states will change according to the latest high or low price of TTM EPS, such as: :
After the second quarter of 2023 (end of June), how do prices from 1 July – 30 September reflect net profits? The program will get the highest and lowest prices during that time.
After the 3rd quarter of 2023 (end of September), how do prices from 1 Oct. - 31 Dec. reflect net profits? The program will get the highest and lowest prices during that time.
- Second, the blue line is the closing price divided by TTM EPS, which shows the current P/E.
