Commitment of Traders: Dual Currency with Change SummaryCommitment of Traders: Dual Currency with Change Summary
Übersicht
Der Commitment of Traders: Dual Currency with Change Summary ist ein leistungsstarker Indikator, der die Commitment of Traders (COT)-Daten für zwei Währungen (Base und Quote) in Echtzeit analysiert und visualisiert. Er bietet eine detaillierte Zusammenfassung der Positionen großer Händler, kleiner Händler und kommerzieller Hedger sowie deren prozentuale Veränderungen im Vergleich zum Vorwochenwert. Mit diesem Indikator können Trader fundierte Entscheidungen auf der Grundlage von COT-Daten treffen und Markttrends besser verstehen.
Hauptfunktionen
Dual Currency Analysis:
Zeigt COT-Daten für Base Currency und Quote Currency an.
Unterstützt verschiedene Währungsmodi (Auto, Root, Base Currency, Currency).
Change Summary Table:
Zeigt die aktuellen und vorherigen Werte für große Händler, kleine Händler und kommerzielle Hedger.
Berechnet die prozentuale Veränderung und die absolute Differenz im Vergleich zum Vorwochenwert.
Flexible Anzeigeoptionen:
Wähle zwischen Long, Short, Long + Short, Long - Short und Long %.
Entscheide, ob Futures, Optionen oder beides angezeigt werden sollen.
Farbliche Hervorhebungen:
Base Currency-Zeilen werden in Grün hinterlegt.
Quote Currency-Zeilen werden in Rot hinterlegt.
Positive prozentuale Veränderungen werden in Grün hervorgehoben, negative in Rot.
Benutzerfreundliche Steuerung:
Einfache Aktivierung/Deaktivierung von Metriken über Checkboxen.
Möglichkeit, den CFTC-Code manuell zu überschreiben.
Anwendungsfälle
Trendbestätigung: Nutze die COT-Daten, um langfristige Markttrends zu bestätigen oder zu widerlegen.
Sentiment-Analyse: Analysiere das Marktsentiment großer Händler und kommerzieller Hedger.
Handelsentscheidungen: Treffe fundierte Entscheidungen basierend auf den Positionen und Veränderungen der Marktteilnehmer.
Vergleiche: Vergleiche die COT-Daten zweier Währungen, um relative Stärken und Schwächen zu identifizieren.
Warum dieser Indikator?
Echtzeit-Daten: Zugriff auf aktuelle COT-Daten direkt in TradingView.
Benutzerfreundlich: Einfache Konfiguration und intuitive Bedienung.
Visuell ansprechend: Klare farbliche Hervorhebungen für schnelle Interpretation.
Flexibel: Anpassbar an verschiedene Handelsstile und Strategien.
Einstellungen
Base Currency Mode: Wähle den Modus für die Base Currency (Auto, Root, Base Currency, Currency).
Quote Currency Mode: Wähle den Modus für die Quote Currency (Auto, Root, Base Currency, Currency).
Futures/Options: Entscheide, ob Futures, Optionen oder beide angezeigt werden sollen.
Display: Wähle die Anzeigeoption (Long, Short, Long + Short, Long - Short, Long %).
CFTC Code: Überschreibe den automatisch ermittelten CFTC-Code manuell.
Show Change Summary Table: Aktiviere oder deaktiviere die Zusammenfassungstabelle.
Beispiel
Base Currency: EUR (Euro)
Quote Currency: USD (US-Dollar)
Change Summary:
Base Large Traders: Vorheriger Wert = -56, Aktueller Wert = -46, Veränderung = +17.86% (Grün)
Quote Commercial Hedgers: Vorheriger Wert = 120, Aktueller Wert = 110, Veränderung = -8.33% (Rot)
Hinweise
Die COT-Daten werden wöchentlich von der CFTC veröffentlicht und sind mit einer Verzögerung von einigen Tagen verfügbar.
Der Indikator ist ideal für langfristige Trader und Investoren, die fundierte Entscheidungen auf der Grundlage von Marktsentiment-Daten treffen möchten.
Viel Spaß beim Trading!
Nutze den Commitment of Traders: Dual Currency with Change Summary, um deine Trading-Strategien zu verbessern und fundierte Entscheidungen auf der Grundlage von COT-Daten zu treffen. Bei Fragen oder Feedback kannst du mich gerne kontaktieren!
Fundamental-analysis
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights.
Blockchain Fundamentals: Global LiquidityGlobal Liquidity Indicator Overview
This indicator provides a comprehensive technical analysis of liquidity trends by deriving a Global Liquidity metric from multiple data sources. It applies a suite of technical indicators directly on this liquidity measure, rather than on price data. When this metric is expanding Bitcoin and crypto tends to bullish conditions.
Features:
1. Global Liquidity Calculation
Data Integration: Combines multiple market data sources using a ratio-based formula to produce a unique liquidity measure.
Custom Metric: This liquidity metric serves as the foundational input for further technical analysis.
2. Timeframe Customization
User-Selected Period: Users can select the data timeframe (default is 2 months) to ensure consistency and flexibility in analysis.
3. Additional Technical Indicators
RSI, Momentum, ROC, MACD, and Stochastic:
Each indicator is computed using the Global Liquidity series rather than price.
User-selectable toggles allow for enabling or disabling each individual indicator as desired.
4. Enhanced MACD Visualization
Dynamic Histogram Coloring:
The MACD histogram color adjusts dynamically: brighter hues indicate rising histogram values while darker hues indicate falling values.
When the histogram is above zero, green is used; when below zero, red is applied, offering immediate visual insight into momentum shifts.
Conclusion
This indicator is an enlightening tool for understanding liquidity dynamics, aiding in macroeconomic analysis and investment decision-making by highlighting shifts in liquidity conditions and market momentum.
Interest Rate & CPI Differential By King OsamaINTEREST RATE & CPI Differential Indicator By King Osama
A must-have tool for forex traders and macro analysts, this indicator tracks interest rate differentials, real interest rate gaps, and CPI (inflation) differences to provide a fundamental edge in trading.
Key Features:
✅ Interest Rate Differential (Rate Diff) – Measures the gap between base and quote currency interest rates. Higher rates attract capital, influencing currency strength. Ideal for carry trade opportunities.
✅ Real Interest Rate Differential (Real Rate Diff) – Adjusts interest rates for inflation (CPI) to reflect the true return on holding a currency. A more accurate indicator of long-term strength.
✅ CPI Differential (CPI Diff) – Compares inflation rates between two economies, helping traders anticipate central bank actions (rate hikes/cuts) based on inflation trends.
✅ Dynamic Table & Bias Signals – Clear LONG/SHORT indications, historical tracking, and real-time updates for macro-driven forex decisions.
🔹 Perfect for swing traders combining fundamentals with technicals! 🚀
DCA Fundamentals 1.0DCA Fundamentals 1.0
Description:
DCA Fundamentals 1.0 is an invite-only indicator designed to help traders and investors make informed decisions by analyzing key fundamental metrics of a company. It aggregates essential financial data—such as book value, earnings per share, total equity, total debt, net income, and total revenue—to provide a comprehensive overview of the stock’s intrinsic value and risk profile. By examining factors like the debt-to-equity ratio and dynamically computing Buffet’s Limit, this tool assists in identifying whether a stock may be undervalued, fairly valued, or overvalued.
Key Features:
Intrinsic Value Calculation: Estimates a stock’s intrinsic worth using a weighted combination of book value per share and EPS.
Buffet’s Limit & Margin of Safety: Adjusts intrinsic value based on the company’s debt-to-equity ratio, providing a margin of safety percentage to gauge potential investment risk.
Debt Warning: Highlights when the debt-to-equity ratio exceeds 2, signaling possible financial instability.
Data Visualization: Displays equity, debt, net income, and revenue as area plots or histograms, helping users quickly assess financial health.
Investment Status: Classifies the stock as undervalued, fairly valued, or overvalued based on current price relative to intrinsic value and Buffet’s Limit.
Dividend-to-ROE Ratio: Offers insight into dividend payout sustainability relative to the company’s return on equity.
Instructions
Fallback Data Handling:
If any financial data is unavailable, fallback values are automatically used to ensure that key calculations remain meaningful and uninterrupted.
Intrinsics & Risk Assessment:
Intrinsic Value: Computed using book value and EPS to understand the stock’s core worth.
Buffet’s Limit: Adjusted from the intrinsic value based on the debt-to-equity ratio. The resulting margin of safety helps gauge the current price’s risk level.
Debt Warning:
Debt-to-Equity Ratio > 2: Triggers a red warning, advising caution due to potentially excessive debt.
Visual Indicators:
Intrinsically Undervalued (Green Area): When price is below intrinsic value, a green shaded area suggests the stock may be undervalued, potentially presenting a buying opportunity.
Debt vs. Equity (Area Plots):
Red Area: Represents debt. A larger red area signals relatively high debt levels.
Green Area: Represents equity. A larger green area suggests stronger financial health.
Revenue & Net Income (Histograms):
Green Bars: Positive or improving fundamentals.
Red Bars: Negative or declining performance.
Investment Status:
Undervalued (Green): Price below intrinsic value.
Fairly Valued (Yellow): Price between intrinsic value and Buffet’s Limit.
Overvalued (Red): Price above intrinsic value, implying increased downside risk.
Table Display:
A convenient table summarizes key metrics at a glance, including P/E ratio, Debt-to-Equity ratio, intrinsic value, margin of safety, net income, total revenue, and the Dividend-to-ROE Ratio.
Dividend-to-ROE Ratio:
This metric provides additional context on the company’s dividend policy relative to its return on equity, aiding in evaluating dividend sustainability.
Disclaimer
Important Disclaimer:
The DCA Fundamentals 1.0 indicator is provided solely for educational and informational purposes. It is not investment advice, a recommendation, or an endorsement of any security or strategy. All calculations are based on data provided by third parties, and their accuracy or completeness is not guaranteed.
Investing and trading involve significant risks. You may lose more than your initial investment. Historical performance or indicators cannot guarantee future results. Before making any investment decisions, you should conduct thorough research, consider consulting a qualified financial professional, and implement robust risk management strategies.
By using DCA Fundamentals 1.0, you acknowledge these risks and agree that neither the creator nor any affiliated parties are responsible for any losses incurred. Use this tool at your own discretion and risk.
CAPE / Shiller PE RatioThe CAPE (Cyclically Adjusted Price-to-Earnings) or Shiller PE ratio is a popular valuation measure used by investors to assess whether a stock or index is over or undervalued relative to its historical earnings. Unlike the traditional P/E ratio, the CAPE ratio smooths earnings over ten years, adjusting for inflation and providing a more stable and long-term view of valuation.
This indicator lets you quickly calculate and visualize the CAPE ratio for any stock on TradingView, helping you make informed decisions about the sustainability of current price levels. With its clear presentation and intuitive setup, you can compare historical CAPE levels and identify potential opportunities for long-term investments or avoid overvalued markets.
Advantages of the CAPE Ratio:
Long-Term Focus : Smooth earnings over ten years, reducing the impact of short-term volatility.
Inflation-Adjusted : Provides a more precise, inflation-adjusted valuation measure over time.
Historical Comparison : Allows for benchmarking against long-term historical averages.
Market Sentiment Indicator : Can highlight overvalued or undervalued markets for long-term investors.
Reduces Noise : Filters out short-term earnings fluctuations, offering a more stable view.
Disadvantages of the CAPE Ratio:
Ignores Recent Earnings : Misses short-term earnings changes, which can affect current valuations.
Outdated Data : Relies on old earnings data that may not reflect recent company performance.
Less Effective for Growth Stocks : May undervalue high-growth stocks focused on future earnings.
Sector Limitations : Works best for broad markets, less so for fast-changing industries.
Debated Predictive Power : It’s unreliable for timing short-term market movements.
In short, the CAPE ratio is excellent for long-term valuation but has limitations for short-term or growth-focused investing.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
PE Ratio Intrinsic ValueThe "Median PE Ratio and Intrinsic Value" indicator is designed for traders and investors who wish to evaluate the intrinsic value of a stock based on a comparative analysis of Price-to-Earnings (PE) ratios across multiple stocks. This tool not only provides insights into whether a stock is undervalued or overvalued but also allows you to visualize the intrinsic value directly on the chart.
Comparison Across Multiple Stocks:
This indicator calculates the PE ratio for up to five different stocks, allowing you to compare the target stock's valuation against four other same sector companies. By default, the stocks included are Apple (AAPL), Google (GOOG), Microsoft (MSFT), and Amazon (AMZN), but you can customize these symbols to fit your analysis needs.
Dynamic PE Ratio Calculation:
The indicator calculates the PE ratio for each stock by dividing the current price by the earnings per share (EPS). The EPS data is retrieved based on the selected period, which can be one of the following:
FY (Fiscal Year)
FH (Fiscal Half-Year)
FQ (Fiscal Quarter)
TTM (Trailing Twelve Months)
You can easily switch between these periods using the provided input options, enabling a more customized analysis based on your preferred financial timeframe.
Once the PE ratios for the selected stocks are computed, the indicator calculates the average PE ratio. The average value is a robust measure that reduces the influence of outliers and provides a balanced view of market valuation.
The intrinsic value of the stock on the chart is calculated by multiplying its EPS by the median PE ratio of the selected stocks. This gives you an estimate of what the stock should be worth if it were to trade at a fair valuation relative to the chosen peers.
The intrinsic value is plotted directly on the price chart as a step line with breaks. This step line style is chosen to represent changes in intrinsic value clearly, with breaks indicating periods where the calculated value is not valid (e.g., negative intrinsic value). Only positive intrinsic values are displayed, helping you focus on meaningful data.
You can easily customize the stocks analyzed by entering the ticker symbols of your choice. Additionally, the indicator allows you to adjust the timeframe for EPS data, giving you flexibility depending on whether you are focused on long-term trends or shorter financial periods.
How to Use:
Compare the current stock price to the plotted intrinsic value. If the current price is below the intrinsic value, the stock may be undervalued. Conversely, if the price is above the intrinsic value, the stock might be overvalued. By comparing your stock against major market players, you can gauge whether it's trading at a premium or discount relative to other key companies in the sector. Use the period selection (FY, FQ, TTM) to adapt your analysis to different market conditions or earnings cycles, giving you more control over your valuation assessment.
Ideal For:
Long-term Investors looking to assess the intrinsic value of a stock based on comparative analysis.
Fundamental Analysts who want to combine multiple stocks' PE ratios to estimate a fair valuation.
Value Investors interested in finding undervalued opportunities by comparing the market price to intrinsic value.
Institutional Activity Index [AlgoAlpha]🌟 Introducing the Institutional Activity Index by AlgoAlpha 🌟
Welcome to a powerful new indicator designed to gauge institutional trading activity! This cutting-edge tool combines volume analysis with price movement to derive a unique index that shines a spotlight on potential institutional moves in the market. 🎯📈
Key Features:
🔍 Normalization Period : Adjust the look-back period for normalization to tailor the sensitivity to your trading strategy.
📊 Moving Average Types : Choose from SMA, HMA, EMA, RMA, WMA, or VWMA to smooth the index and pinpoint trends.
🌈 Color-Coded Trends : Instant visual feedback on index trend direction with customizable up and down colors.
🔔 Alerts : Set alerts for when the index shows increasing activity, decreasing activity, or has reached a peak.
Quick Guide to Using the Institutional Activity Index:
1. 📝 Add the Indicator: Add the indicator to favorites. Adjust the normalization period, MA type, and peak detection settings to match your trading style.
2. 📈 Market Analysis: Similar to volume that reflects the amount of collective trading activity, this index reflects an estimate of the amount of trading activity by institutions. A higher value means that institutions are trading the asset more, this can mean selling or buying as the indicator does not indicate direction . Look out for peak signals, which may indicate that institutions have already secured positions in preparation for a move in price.
3. 🔔 Set Alerts: Enable alerts to notify you when there is a significant change in the activity levels or a new peak is detected, allowing for timely decisions without constant monitoring.
How It Works: 🛠
It is common knowledge that institutions trade with high amounts of capital, but employ tactics so as to not move the price significantly when entering on positions. This can be done by entering in times of high liquidity so that when an institution buys, there are enough sellers to cancel out the price movements and prevent a huge pump in price and vice versa. The Institutional Activity Index calculates liquidity by measuring the volume relative to the price range (close-open). This value is smoothed using median and a user defined moving average type and period, enhancing its clarity. If normalization is enabled, the index is adjusted relative to its range over a user-defined period, making the data comparable across different conditions.
Embrace this innovative tool to enhance your trading insights and strategies! 🚀✨
US CPIIntroducing "US CPI" Indicator
The "US CPI" indicator, based on the Consumer Price Index (CPI) of the United States, is a valuable tool for analyzing inflation trends in the U.S. economy. This indicator is derived from official data provided by the U.S. Bureau of Labor Statistics (BLS) and is widely recognized as a key measure of inflationary pressures.
What is CPI?
The Consumer Price Index (CPI) is a measure that examines the average change in prices paid by consumers for a basket of goods and services over time. It is an essential economic indicator used to gauge inflationary trends and assess changes in the cost of living.
How is "US CPI" Calculated?
The "US CPI" indicator in this script retrieves CPI data from the Federal Reserve Economic Data (FRED) using the FRED:CPIAUCSL symbol. It calculates the rate of change in CPI over a specified period (typically 12 months) and applies technical analysis tools like moving averages (SMA and EMA) for trend analysis and smoothing.
Why Use "US CPI" Indicator?
1. Inflation Analysis: Monitoring CPI trends provides insights into the rate of inflation, which is crucial for understanding the overall economic health and potential impact on monetary policy.
2. Policy Implications: Changes in CPI influence decisions by policymakers, central banks, and investors regarding interest rates, fiscal policies, and asset allocation.
3. Market Sentiment: CPI data often impacts market sentiment, influencing trading strategies across various asset classes including currencies, bonds, and equities.
Key Features:
1. Customizable Smoothing: The indicator allows users to apply exponential moving average (EMA) smoothing to CPI data for clearer trend identification.
2. Visual Representation: The plotted line visually represents the inflation rate based on CPI data, helping traders and analysts assess inflationary pressures at a glance.
Sources and Data Integrity:
The CPI data used in this indicator is sourced directly from FRED, ensuring reliability and accuracy. The script incorporates robust security protocols to handle data requests and maintain data integrity in a trading environment.
In conclusion, the "US CPI" indicator offers a comprehensive view of inflation dynamics in the U.S. economy, providing traders, economists, and policymakers with valuable insights for informed decision-making and risk management.
Disclaimer: This indicator and accompanying analysis are for informational purposes only and should not be construed as financial advice. Users are encouraged to conduct their own research and consult with professional advisors before making investment decisions.
NVT Z-ScoreNVT Z-Score Script:
Data Source and Calculation: This script calculates the NVT ratio by dividing the market cap (assumed from QUANDL data) by a 90-day MA of the transaction volume (also from QUANDL), similar to the NVTS calculation. However, the adaptation lies in further analyzing the NVT ratio through a Z-score approach, not explicitly described in the original NVTS methodology.
Z-Score Analysis: The script calculates the mean and standard deviation of the NVT ratio over a user-defined period (daysForMean, defaulting to 180 days) and then computes the Z-score of the current NVT ratio relative to this historical data. This Z-score analysis introduces a standardized way of understanding the NVT ratio's deviation from its historical average, offering a nuanced view of market valuation states.
Visualization and Dynamic Zones: The visualization emphasizes Z-score-based dynamic zones (green, yellow, and red), determined by the stdDevMultiplier. These zones are plotted and filled on the chart, providing visual cues for interpreting the NVT ratio's current state in relation to its historical norm. This aspect significantly differs from the traditional NVTS approach by directly incorporating the concept of standard deviation and Z-scores into the analysis.
Inflation CorrelationHeyo fellas,
In today’s dynamic economic landscape, understanding the relationship of market prices to other economical factors like inflation rate is crucial. The Inflation Correlation Indicator is designed to provide traders with a clear visualization of this relationship. By correlating average inflation rates from selected countries with market closing prices, this indicator offers a unique perspective on potential market movements influenced by inflationary trends.
Features:
Country Selection: Choose from the European Union (EU), Germany (DE), or the United States (US) to tailor the correlation analysis to your specific market interest.
Correlation Length Customization: Adjust the correlation length to refine the sensitivity of the indicator to recent inflation data.
Visual Clarity: The correlation histogram changes color based on the direction of the correlation, providing an intuitive understanding of the inflation correlation.
Whether you’re a fundamental analyst seeking to incorporate macroeconomic indicators into your strategy or a trader looking for an edge in inflation-sensitive markets, the Inflation Correlation Indicator is an indispensable tool in your TradingView arsenal.
Thanks for checking this out!
Best regards,
simwai
(CF|360) Caruso Financial DashboardThe Caruso Financial 360 Dashboard (CF|360) revolutionizes your TradingView charts by seamlessly integrating comprehensive Fundamental, Statistical, Technical, Performance, and Event information into an intuitively organized dashboard. This empowers users to make informed investment decisions effortlessly, eliminating the need to switch between pages or applications.
The dashboard is strategically divided into five distinct sections, each color-coded for user-friendly navigation. A quick glance at the dark blue "Fundamentals" table reveals two years of quarterly EPS and Sales data, YoY % change, and Surprise %, complete with report dates. Users can explore eight years of annual data and choose between Non-GAAP EPS, Diluted EPS, and Basic EPS for versatile analysis. Opting for Non-GAAP EPS also unveils next quarter estimates. The Fundamentals section further encompasses P/E and P/S data, alongside TTM dividend and dividend yield information.
In the yellow "Extended Fundamentals" section, users gain insights into Gross, EBITDA, and Net margins for easy profitability comparisons within the same industry group. Return on Equity data and Free Cashflow per share provide perspectives on profitability, efficiency, and financial flexibility.
The light blue "Statistics" section furnishes essential statistical measures for a rapid grasp of a company's trading characteristics. Metrics such as Market Cap, Average Volume per day (Shares and $ value), VWAP, Up/Down volume ratio, ATR%, Alpha, Beta, Shares Outstanding & Float, 52-week High/Low, and % distance from the 52-week high are presented. Additionally, market breadth is depicted through Nasdaq and NYSE 52-week high/low data.
The purple "Technical & Performance" section seamlessly integrates both Technical Analysis data and Performance statistics, enabling users to assess the stock's technical context and performance against the market over different periods. Technical indicators, including three customizable moving average types, RSI, ADX, Bollinger Band, Keltner Band, and daily and weekly closing ranges, are featured.
The grey top "Events" section offers a quick overview of the next earnings release date, countdown, and associated color changes as the date approaches. Company name, sector, and industry details are also presented.
To enhance information visibility, record EPS and Sales data are highlighted, emphasizing new records, along with highlights for new 52-week highs and lows.
The CF|360 offers customization options , including three display styles for Desktops, Desktop Slim, and Mobile devices.
Users can also tailor the lengths of technical indicators to suit their preferences. International market enthusiasts will appreciate that the CF|360 provides financial and market data for various regions, including the US, EU, Canada, and beyond.
88 Metrics Included:
Fundamentals Section (Dark Blue Group)
EPS (Adjusted Non-GAAP, Diluted, Basic)
- Quarterly, YoY % Chg, Surprise, Report Date, Next Quarter Estimate (Adjusted EPS only)
- Annual, YoY % Chg
Sales
- Quarterly, YoY % Chg, Surprise, Report Date, Next Quarter Estimate
- Annual, YoY % Chg
P/E ratio
P/S ratio
Dividend TTM
Dividend TTM Yield
Fundamentals Extended (Yellow Group)
Gross Margin
EBITDA Margin
Net Margin
Return on Equity (ROE)
Free Cashflow per Share (FCFPS)
Debt to Equity (Debt)
Effective Interest Rate (Int Rate)
Statistics (Light Blue Group)
Market Cap
Average Daily Volume (Shares)
Average Daily Volume (Dollar Value)
VWAP (Daily)
Average True Range Percent
Shares Outstanding
Shares in Float
Percentage of Share in Float
52-Week High
52-Week Low
% off of 52-Week High
Up / Down Volume Ratio
Beta
Alpha
Nasdaq Net 52-Week High/Lows
Nasdaq 52-Week Highs
Nasdaq 52-Week Lows
NYSE Net 52-Week High/Lows
NYSE 52-Week Highs
NYSE 52-Week Lows
Technical & Performance (Purple Group)
Moving Average Value (3 different averages)
Distance from Moving Average (3 different averages)
Relative Strength Index (RSI)
Average Directional Index (ADX)
Bollinger Band Value (Upper/Lower)
%b
Keltner Band Value (Upper/Lower)
%k
Percentage Changes Since Today’s Open
Daily Closing Range (DCR)
Weekly Closing Range (WCR)
Current Week % Change
1 Month % Change
3 Month % Change
6 Month % Change
1 Year % Change
3 Year % Change
YTD % Change
S&P 500 YTD % Change
Name, Group, & Events (Grey Section)
Company Name
Sector
Industry
Next Earnings Date
Days Until Next Earnings Date
Event Highlights
Record EPS (Quarterly/Annual)
Record Sales (Quarterly/Annual)
52-Week High
52-Week Low
Layout Types
Desktop
Get the full experience with the Desktop view.
Desktop Slim
Save screen real estate with a slim version of the dashboard.
Mobile
Take the most vital metrics with you on your mobile device. For the best experience, view in landscape mode.
BTC Supply in Profits and Losses (BTCSPL) [AlgoAlpha]Description:
🚨The BTC Supply in Profits and Losses (BTCSPL) indicator, developed by AlgoAlpha, offers traders insights into the distribution of INDEX:BTCUSD addresses between profits and losses based on INDEX:BTCUSD on-chain data.
Features:
🔶Alpha Decay Adjustment: The indicator provides the option to adjust the data against Alpha Decay, this compensates for the reduction in clarity of the signal over time.
🔶Rolling Change Display: The indicator enables the display of the rolling change in the distribution of Bitcoin addresses between profits and losses, aiding in identifying shifts in market sentiment.
🔶BTCSPL Value Score: The indicator optionally displays a value score ranging from -1 to 1, traders can use this to carry out strategic dollar cost averaging and reverse dollar cost averaging based on the implied value of bitcoin.
🔶Reversal Signals: The indicator gives long-term reversal signals denoted as "▲" and "▼" for the price of bitcoin based on oversold and overbought conditions of the BTCSPL.
🔶Moving Average Visualization: Traders can choose to display a moving average line, allowing for better trend identification.
How to Use ☝️ (summary):
Alpha Decay Adjustment: Toggle this option to enable or disable Alpha Decay adjustment for a normalized representation of the data.
Moving Average: Toggle this option to show or hide the moving average line, helping traders identify trends.
Short-Term Trend: Enable this option to display the short-term trend based on the Aroon indicator.
Rolling Change: Choose this option to visualize the rolling change in the distribution between profits and losses.
BTCSPL Value Score: Activate this option to show the BTCSPL value score, ranging from -1 to 1, 1 implies that bitcoin is extremely cheap(buy) and -1 implies bitcoin is extremely expensive(sell).
Reversal Signals: Gives binary buy and sell signals for the long term
Bitcoin/Hash Rate Oscillator & MAWhat it does:
Finds the ratio of BTC price to the Hash Rate with an additional MA applied to find changes in volatility with relative context. Best used as a two lines cross indicator.
When the ratio of price to hashrate increases, it may be a sign miners cannot or will not sell as much.
When the ratio decreases, it may indicate miners have more capability and/or incentive to sell.
How it works:
The indicator uses a MA applied to the hashrate(first MA input), then finds the difference between it and the actual hash rate. Then it finds the STD of that to create an oscillating value. BTC is divided by said value. Then a second MA is applied to that ratio(second MA input)
Fair Value by MMEnglish
IMPORTANT NOTICE
This indicator is used to find fair value based on historical data. Past growth data may not be sustainable, which will cause the price targets given by the indicator to be inaccurate. Any price on this indicator cannot be considered as investment advice. Trading decisions are the responsibility of the person using the indicator.
What is the Fair Value by MM indicator?
This is an indicator that tries to find the fair value of a stock by looking at its historical data and growth over a certain period of time. By analyzing a stock's historical growth data, it generates a fair value and potential price estimate.
The indicator presents the financial data of a stock with 3 different data sets.
1. Summary and Valuation
2. Average Quarterly Growth
3. Profit margins
** Number of Lookback Periods for Quarters **
The first input of the indicator is where you specify how many quarters back to value the stock. By default, it is based on the last 12 quarters, i.e. 3 years. Since there is not enough historical data for newly listed companies, you can change this figure according to the company you are analyzing.
** Show Summary **
The Indicator starts in this mode by default. This mode gives you data such as sales, EBITDA, EBIT, net profit and free cash flow in PER SHARE and TTM values. The reason for using per share values is that a company's price is per share, and it saves you time to look at all other metrics on a per share basis. For example, if a company with a share price of $10 has sales per share of $5, we can say that this company has generated half of its market capitalization in sales revenue in the last 1 year.
In the indicator's default mode (Show Summary);
1. Sales per share TTM (Red)
2. EBITDA per share TTM (Orange)
3. EBIT per share TTM (Yellow)
4. Net Income per share TTM (Blue)
5. Free Cash Flow per share TTM (Green)
6. Share close price (White)
7. Fair value of the share (Green if price is below fair value, Red if price is above fair value)
8. Price target for the next 12 months (Yellow)
** Show AVG Growth QoQ **
When this option is selected, you can see the average quarterly growth in sales, EBITDA, EBIT, net profit and free cash flow, respectively, over the period you have selected (e.g. the last 12 quarters). This data gives an idea about the company's growth and the pace of its growth.
** Show Profit Margins **
When this option is selected, you can see gross profit margin, EBITDA margin, EBIT margin, net profit margin and free cash flow margin data respectively. It provides a quick overview to determine whether the company is increasing revenue by narrowing profit margins or increasing both revenue growth and profit margins.
** Include Sales **
When this option is selected, sales revenues are included in the company's valuation.
** Include Ebitda **
When this option is selected, EBITDA is included in the valuation of the company.
** Include Ebit **
When this option is selected, EBIT is included in the valuation of the company.
** Include Net Profit **
When this option is selected, net profit is included in the valuation of the company.
** Include FCF **
When this option is selected, free cash flow is included in the valuation of the company.
By default, the valuation is based on sales, EBITDA and EBIT. Net profit and free cash flow can be optionally selected. Or the metrics you do not want can be excluded from the valuation calculation.
What do the colors mean?
** Red **
Represents the company's data related to the company's sales.
** Orange **
Represents the company's data related to the company's EBITDA.
** Yellow **
Represents the company's data related to the company's EBIT.
** Blue **
Represents the company's data related to the company's Net Income.
** Green **
Represents the company's data related to the company's Free Cash Flow.
Turkish
ÖNEMLİ UYARI
Bu indikatör geçmiş verileri baz alarak adil değer bulmaya yarar. Geçmişte oluşan büyüme verileri sürdürelebilir olmayabilir, bu da indikatörün verdiği fiyat hedeflerinin yanılmasına sebep olacaktır. Bu indikatör üzerinde yer alan herhangi bir fiyat, yatırım tavsiyesi kapsamında değerlendirilemez. Alım/satım kararları indikatörü kullanan kişinin sorumluluğundadır.
Fair Value by MM indikatörü nedir?
Bu bir hissenin belirli bir periyotu kapsayan geçmiş verilerine ve gelişimlerine bakarak adil değerini bulmaya çalışan bir indikatördür. Bir hissenin geçmiş büyüme verilerini analiz ederek adil değer ve potansiyel fiyat tahmini oluşturur.
İndikatör bir hissenin finansal datasını 3 farklı veri seti ile sunmaktadır.
1. Özet ve Değerleme
2. Ortalama Çeyreklik Büyümeler
3. Kar marjları
** Number of Lookback Periods for Quarters **
İndikatörün ilk input’u, hisseyi değerlemek için kaç çeyrek geriye bakacağınızı belirttiğiniz kısımdır. Varsayılan olarak son 12 çeyrek, yani 3 yılı baz alır. Yeni arz olmuş şirketlerde yeterli geçmiş veri bulunmadığı için bu rakamı incelediğiniz şirkete göre değiştirebilirsiniz.
** Show Summary **
İndikatör varsayılan olarak bu modda başlar. Bu mod, satışlar, favök, esas faaliyet karı, net kar ve serbest nakit akışı gibi verileri HİSSE BAŞINA ve YILLIKLANDIRILMIŞ değerleri ile size verir. Hisse başına değerlerin kullanılmasındaki sebep, bir şirketin fiyatı hisse başınadır, ve diğer tüm metriklere hisse başına bakmak size zaman kazandırır. Örneğin, hisse fiyatı $10 olan bir şirketin, hisse başına satışları $5 ise, bu şirket son 1 yılda piyasa değerinin yarısı kadar satış geliri elde etmiş diyebiliriz.
İndikatörün varsayılan modunda (Show Summary);
1. Hisse başına yıllıklandırılmış Satışlar (Kırmızı)
2. Hisse başına yıllıklandırılmış FAVÖK (Turuncu)
3. Hisse başına yıllıklandırılmış Esas Faaliyet Karı (Sarı)
4. Hisse başına yıllıklandırılmış Net Kar (Mavi)
5. Hisse başına yıllıklandırılmış Serbest Nakit Akışı (Yeşil)
6. Hisse kapanış fiyatı (Beyaz)
7. Hissenin adil değeri (Fiyat Adil değerin altında ise Yeşil, Üstünde ise Kırmızı)
8. Önümüzdeki 12 aylık fiyat hedefi (Sarı)
** Show AVG Growth QoQ **
Bu seçenek seçildiğinde, sırası ile satışlar, favök, esas faaliyet karı, net kar ve serbest nakit akışının, seçmiş olduğunuz periyotta (örneğin son 12 çeyrek), çeyreklik olarak ortalama % kaç büyüdüğünü görebilirsiniz. Bu veri, şirketin gelişimi ve gelişim hızı hakkında fikir vermektedir.
** Show Profit Margings **
Bu seçenek seçildiğinde, sırası ile brüt kar marjı, favök marjı, esas faaliyet kar marjı, net kar marjı ve serbest nakit akışı marjı verilerini görebilirsiniz. Şirketin karlılık marjlarını daraltarak mı gelirini arttırdığını yoksa hem gelir artışı hem de kar marjlarını arttırdığını tespit etmek için hızlı bir bakış sunar.
** Include Sales **
Bu seçenek seçildiğinde, şirketin değerlemesine satış gelirleri dahil edilir.
** Include Ebitda **
Bu seçenek seçildiğinde, şirketin değerlemesine favök dahil edilir.
** Include Ebit **
Bu seçenek seçildiğinde, şirketin değerlemesine esas faaliyet karları dahil edilir.
** Include Net Profit **
Bu seçenek seçildiğinde, şirketin değerlemesine net kar dahil edilir.
** Include FCF **
Bu seçenek seçildiğinde, şirketin değerlemesine serbest nakit akışı dahil edilir.
Varsayılan olarak, satışlar, favök ve esas faaliyet karı üzerinden değerleme yapılır. Net kar ve serbest nakit akışı isteğe göre seçilebilir. Ya da istemediğiniz metrikler değerleme hesaplamasından çıkarılabilir.
Renkler ne anlama geliyor?
** Kırmızı **
Şirketin satışları ile ilgili verilerini temsil eder.
** Turuncu **
Şirketin favök’ü ile ilgili verilerini temsil eder.
** Sarı **
Şirketin esas faaliyet karı ile ilgili verilerini temsil eder.
** Mavi **
Şirketin net karı ile ilgili verileri temsil eder.
** Yeşil **
Şirketin serbest nakit akışı ile ilgili verilerini temsil eder.
FCF / FFO / CFOA and dividends per shareThe indicator shows the Free Cashflow, Funds From Operations or Cash From Operating Activities per share and you can compare it to the dividends per share. You can see at a glance whether the dividends could be paid by one of this KPI. Please use the 12M time unit for the best result.
Blockchain FundamentalThis indicator is made for traders to harness fundamental blockchain data for better decision-making. Unlike traditional tools, this indicator doesn't depend on standard technical indicators. It offers a novel perspective by focusing on core blockchain metrics like capitalization, miner activity, and other intrinsic data elements. I've designed a distinct scoring logic, exclusive to BF, ensuring it's user-friendly and provides actionable insights for traders at all levels.
Mainly created for Bitcoin , but can be applied to any other crypto assets in cost of losing some metrics in the analysis.
Ethereum chart:
Features:
Customizable Moving Averages:
Choose from an array of moving averages, with the flexibility to adjust the length for a tailored analysis, aiding in pinpointing asset trends.
Blockchain Metrics Integration:
Incorporates a range of blockchain metrics such as Market Cap to Realised Cap ratio, Spent Output Profit Ratio, ATH Drawdown, and more.
Blockchain Metrics Evaluation:
Each metric can be toggled on/off to customize the analysis. Using default settings, traders can use all of the metrics combined.
Every metric is essentially evaluated on a scale from -100 to 100 and then combined with others. If any metric is uncertain about its direction (equals to 0), then the score of it is not accounted in a final calculation.
Kalman Filter:
This indicator offers the option to apply a Kalman filter to the signals, enhancing the smoothness and accuracy of the indicator’s output. This is my approach to mitigate the noise in the final output.
Signal Oscillator:
Displays the aggregated score of all selected blockchain metrics.
Offers visual signals with adjustable upper and lower bounds for easy interpretation based on particular asset observation.
Visual Elements:
Signal Oscillator:
A visual representation of the aggregated blockchain fundamental score.
(White line for a raw calculation, orange line for kalman-filtered one)
Signal Counter:
Displays the count of metrics currently being considered in the fundamental score calculation. (grey line at the middle of an indicator)
Buy/Sell Signal Coloring:
The background color changes to indicate potential buying or selling opportunities based on user-defined bounds.
Usage:
Analysis:
Use the signal oscillator to identify potential market tops and bottoms based on blockchain fundamental data.
Adjust the bounds to customize the sensitivity of buy/sell signals.
Customization:
Enable/disable specific blockchain metrics to tailor the indicator to your analytical needs.
Adjust the moving average type and length for better analysis.
Integration:
Combine with other technical indicators to create a comprehensive trading strategy.
Utilize in conjunction with volume and price action analysis for enhanced decision-making. Every output could be used in traders custom strategies and indicators.
BearMetricsLooking at the financial health of a company is a critical aspect of stock analysis because it provides essential insights into the company's ability to generate profits, meet its financial obligations, and sustain its operations over the long term. Here are several reasons why assessing a company's financial health is important when evaluating a stock:
1. **Profitability and Earnings Growth**: A company's financial statements, particularly the income statement, provide information about its profitability. Analyzing earnings and revenue trends over time can help you assess whether the company is growing or declining. Investors generally prefer companies that show consistent earnings growth.
2. **Risk Assessment**: Financial statements, including the balance sheet and income statement, offer a comprehensive view of a company's assets, liabilities, and equity. By evaluating these components, you can gauge the level of financial risk associated with the stock. A healthy balance sheet typically includes a manageable debt load and strong equity.
3. **Cash Flow Analysis**: Cash flow statements reveal how effectively a company manages its cash, which is crucial for day-to-day operations, debt servicing, and future investments. Positive cash flow is essential for a company's stability and growth prospects.
4. **Debt Levels**: Examining a company's debt levels and debt-to-equity ratio can help you determine its leverage. High debt levels can be a cause for concern, as they may indicate that the company is at risk of financial distress, especially if it struggles to meet interest payments.
5. **Liquidity**: Liquidity is vital for a company's short-term survival. By assessing a company's current assets and current liabilities, you can gauge its ability to meet its short-term obligations. Companies with low liquidity may face difficulties during economic downturns or unexpected financial challenges.
6. **Dividend Sustainability**: If you're an income-oriented investor interested in dividend-paying stocks, you'll want to ensure that the company can sustain its dividend payments. A healthy balance sheet and consistent cash flow can provide confidence in dividend sustainability.
7. **Investment Confidence**: A company with a strong financial position is more likely to attract investor confidence and positive sentiment. This can lead to higher stock prices and a lower cost of capital for the company, which can be beneficial for its growth initiatives.
8. **Risk Mitigation**: By assessing a company's financial health, you can mitigate investment risk. Understanding a company's financial position allows you to make more informed decisions about the level of risk you are comfortable with and whether a particular stock aligns with your risk tolerance.
9. **Long-Term Viability**: Ultimately, investors are interested in companies that have the potential for long-term success. A company with a healthy financial foundation is more likely to weather economic downturns, adapt to industry changes, and thrive over the years.
In summary, examining a company's financial health is a fundamental aspect of stock analysis because it provides a comprehensive picture of the company's current state and its ability to navigate future challenges and capitalize on opportunities. It helps investors make informed decisions and assess the long-term prospects of a stock in their portfolio.
SFC Valuation Model - US SectorSector analysis is an assessment of the economic and financial condition and prospects of a given sector of the economy. Sector analysis serves to provide an investor with a judgment about how well companies in the sector are expected to perform. Sector analysis is typically employed by investors who specialize in a particular sector, or who use a top-down or sector rotation approach to investing.
Sector analysis is based on the premise that certain sectors perform better during different stages of the business cycle. The business cycle refers to the up and down changes in economic activity that occur in an economy over time. The business cycle consists of expansions, which are periods of economic growth, and contractions, which are periods of economic decline.
Investors who employ a top-down approach to sector analysis focus first on macroeconomic conditions in their search for companies that have the potential to outperform. They start by looking at those macroeconomic factors that have the biggest impact on the largest part of the population and the economy, such as unemployment rates, economic outputs, and inflation.
Every sector shows the average return from three ETFs - SPDR, Vanguard, iShares. There is a possibility to see the returns from every ETF by just holding the cursor on the sector name.
There are few valuation methods/steps
- Macroeconomics - analyse the current economic;
- Define how the sector is performing;
- Relative valuation method - compare few stocks and find the Outlier;
- Absolute valuation method historically- define how the stock performed in the past;
- Absolute valuation method - define how the stock is performed now and find the fair value;
- Technical analysis
How to use:
1. Once you have completed the initial evaluation step, simply load the indicator.
2. Analyse which sector is outperforming.
SFC Valuation Model - RelativeComparable company analysis, or “Comps” for short, is commonly used to value firms by comparing them to publicly traded companies with similar business operations. An analyst will compare the current share price a public company relative to some metric such as its earnings to derive a P/E ratio. It will then use that ratio to value the company it is trying to determine the worth of.
One of the most popular relative valuation multiples is the price-to-earnings (P/E) ratio. It is calculated by dividing stock price by earnings per share (EPS), and is expressed as a company's share price as a multiple of its earnings. A company with a high P/E ratio is trading at a higher price per dollar of earnings than its peers and is considered overvalued. Likewise, a company with a low P/E ratio is trading at a lower price per dollar of EPS and is considered undervalued. This framework can be carried out with any multiple of price to gauge relative market value. Therefore, if the average P/E for an industry is 10x and a particular company in that industry is trading at 5x earnings, it is relatively undervalued to its peers.
Limitations
Like any valuation tool, relative valuation has its limitations. The biggest limitation is the assumption that the market has valued the business correctly.
Second, all valuation metrics are based on past performance. Investors' perceptions of future performance heavily influence stock prices and most relative valuation metrics don’t account for growth.
Finally and most importantly, relative valuation is no assurance that the "cheaper" company will outperform its peer.
With this indicator, investors can easily compare a few companies and find the outlier. It calculates the average for the sector and highlights the stock that is above the average.
Due to some limitations, the indicator can only compare 5 tickers, but users can always load it twice for more stocks.
Save hours of data entry into Excel spreadsheets to compare stocks !
There are few valuation methods/steps
- Macroeconomics - analyse the current economic;
- Define how the sector is performing;
- Relative valuation method - compare few stocks and find the Outlier;
- Absolute valuation method historically- define how the stock performed in the past;
- Absolute valuation method - define how the stock is performed now and find the fair value;
- Technical analysis
How to use:
1. Once you have completed the initial evaluation steps, simply load the indicator.
2. Add the forwarded EPS.
3. The indicator will do the rest of the calculations for you.
SFC Valuation Model - Fair ValueValuation is the analytical process of determining the current (or projected) worth of an asset or a company. There are many techniques used for doing a valuation. An analyst placing a value on a company looks at the business's management, the composition of its capital structure, the prospect of future earnings, and the market value of its assets, among other metrics.
Fundamental analysis is often employed in valuation, although several other methods may be employed such as the capital asset pricing model (CAPM) or the dividend discount model (DDM), Discounted Cash Flow (DCF) and many others.
A valuation can be useful when trying to determine the fair value of a security, which is determined by what a buyer is willing to pay a seller, assuming both parties enter the transaction willingly. When a security trades on an exchange, buyers and sellers determine the market value of a stock or bond.
There is no universal standard for calculating the intrinsic value of a company or stock. Financial analysts attempt to determine an asset's intrinsic value by using fundamental and technical analyses to gauge its actual financial performance.
Intrinsic value is useful because it can help an investor understand whether a potential investment is overvalued or undervalued.
This indicator allows investors to simulate different scenarios depending on their view of the stock's value. It calculates different models automatically, but users can define the fair value manually by changing the settings.
For example: change the weight of the model; choose how conservatively want to evaluate the stock; use different growth rate or discount rate and so on.
The indicator shows other useful metrics in order to help investors to evaluate the stock.
This indicator can save users hours of searching financial data and calculating fair value.
There are few valuation methods/steps
- Macroeconomics - analyse the current economic;
- Define how the sector is performing;
- Relative valuation method - compare few stocks and find the Outlier;
- Absolute valuation method historically- define how the stock performed in the past;
- Absolute valuation method - define how the stock is performed now and find the fair value;
- Technical analysis
How to use:
1. Once you have completed the initial evaluation steps, simply load the indicator.
2. Check the default settings and see if they suit you.
3. Find the fair value and wait for the stock to reach it.
