FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
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.
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.
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
Financials - Quick OverviewThis unique indicator is designed to provide traders and investors with a concise yet comprehensive view of a company's financial health and sector classification. It features an intuitive table displayed prominently on the chart, offering a blend of essential company information and key financial metrics. This tool is ideal for those looking to integrate fundamental analysis into their technical trading strategy.
Key Features:
Company Sector Information: Get a quick glimpse of the company's industry sector, aiding in understanding its market position and comparative performance within its industry.
Financial Overview: The table includes vital financial data such as Earnings and Sales, providing insights into the company's revenue and profitability.
Growth Metrics: Track both quarter-over-quarter (QoQ) and year-over-year (YoY) growth, offering a dynamic view of the company's performance over time.
Operating Margin Percentage (OPM%): Understand the efficiency of the company's operations with the OPM%, which indicates the proportion of revenue that remains after paying for variable costs of production.
Price-to-Earnings (PE) Ratio: Assess the company's stock value relative to its earnings, an essential metric for valuation and comparative analysis within the sector.
Usage: This indicator is particularly useful for investors and traders who incorporate fundamental analysis into their decision-making process. By providing key financial data directly on the chart, it allows for a more integrated approach to technical and fundamental analysis. The indicator is designed to be straightforward and easy to interpret, making it suitable for both seasoned investors and those new to financial analysis.
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
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.
Bitcoin Limited Growth ModelThe Bitcoin Limeted Growth is a model proposed by QuantMario that offers an alternative approach to estimating Bitcoin's price based on the Stock-to-Flow (S2F) ratio. This model takes into account the limitations of the traditional S2F model and introduces refinements to enhance its analysis.
The S2F model is commonly used to analyze Bitcoin's price by considering the scarcity of the asset, measured by the stock (existing supply) relative to the flow (new supply). However, the LGS-S2F Bitcoin Price Formula recognizes the need for improvements and presents an updated perspective on Bitcoin's price dynamics.
Invalidation of the Normal S2F Model:
The normal S2F model has faced criticisms and challenges. One of the limitations is its assumption of a linear relationship between the S2F ratio and Bitcoin's price, overlooking potential nonlinearities and other market dynamics. Additionally, the normal S2F model does not account for external influences, such as market sentiment, regulatory developments, and technological advancements, which can significantly impact Bitcoin's price.
Addressing the Issues:
The LGS-S2F Bitcoin Price Formula introduces refinements to address the limitations of the traditional S2F model. These refinements aim to provide a more comprehensive analysis of Bitcoin's price dynamics:
Nonlinearity: The LGS-S2F model recognizes that the relationship between the S2F ratio and Bitcoin's price may not be linear. It incorporates a logistic growth function that considers the diminishing returns of scarcity and the saturation of market demand.
Data Analysis: The LGS-S2F model employs statistical analysis and data-driven techniques to validate its predictions. It leverages historical data and econometric modeling to support its analysis of Bitcoin's price.
Utility:
The LGS-S2F Bitcoin Price Formula offers insights for traders and investors in the cryptocurrency market. By incorporating a more refined approach to analyzing Bitcoin's price, this model provides an alternative perspective. It allows market participants to consider various factors beyond the S2F ratio alone, potentially aiding in their decision-making processes.
Key Features:
Adjustable Coefficients
Sigma calculation methods: Normal or Stdev
Credit:
The LGS-S2F Bitcoin Price Formula was developed by QuantMario, who has contributed to the field of cryptocurrency analysis through their research and modeling efforts.
Valuation Metrics Table (P/S, P/E, etc.)This table gives the user a very easy way of seeing many valuation metrics. I also included the 5 year median of the price to sales and price to earnings ratios. Then I calculated the percent difference between the median and the current ratio. This gives a sense of whether or not a stock is over valued or under valued based on historical data. The other ratios are well known and don't require any explanation. You can turn off the ones you don't want in the settings of the indicator. Another thing to mention is that diluted EPS is used in calculations
Financial Radar Chart by zdmreRadar chart is often used when you want to display data across several unique dimensions. Although there are exceptions, these dimensions are usually quantitative, and typically range from zero to a maximum value. Each dimension’s range is normalized to one another, so that when we draw our spider chart, the length of a line from zero to a dimension’s maximum value will be the similar for every dimension.
This Charts are useful for seeing which variables are scoring high or low within a dataset, making them ideal for displaying performance.
How is the score formed?
Debt Paying Ability
if Debt_to_Equity < %10 : 100
elif < 20% : 90
elif < 30% : 80
elif < 40% : 70
elif < 50% : 60
elif < 60% : 50
elif < 70% : 40
elif < 80% : 30
elif < 90% : 20
elif < 100% : 10
else: 0
ROIC
if Return_on_Invested_Capital > %50 : 100
elif > 40% : 90
elif > 30% : 80
elif > 20% : 70
elif > 10% : 50
elif > 5% : 20
else: 0
ROE
if Return_on_Equity > %50 : 100
elif > 40% : 90
elif > 30% : 80
elif > 20% : 70
elif > 10% : 50
elif > 5% : 20
else: 0
Operating Ability
if Operating_Margin > %50 : 100
elif > 30% : 90
elif > 20% : 80
elif > 15% : 60
elif > 10% : 40
elif > 0 : 20
else: 0
EV/EBITDA
if Enterprise_Value_to_EBITDA < 3 : 100
elif < 5 : 80
elif < 7 : 70
elif < 8 : 60
elif < 10 : 40
elif < 12 : 20
else: 0
FREE CASH Ability
if Price_to_Free_Cash_Flow < 5 : 100
elif < 7 : 90
elif < 10 : 80
elif < 16 : 60
elif < 18 : 50
elif < 20 : 40
elif < 22 : 30
elif < 30 : 20
elif < 40 : 15
elif < 50 : 10
elif < 60 : 5
else: 0
GROWTH Ability
if Revenue_One_Year_Growth > %20 : 100
elif > 16% : 90
elif > 14% : 80
elif > 12% : 70
elif > 10% : 50
elif > 7% : 40
elif > 4% : 30
elif > 2% : 20
elif > 0 : 10
else: 0
Joel Greenblatt Magic FormulaJoel Greenblatt Magic Formula. I always wanted to make this.
The Indicator shows 3 values.
ROC,EY,SUM.
ROC= Return On Capital.
EY=Earnings Yield
SUM= Addition of Two.
Formula:
ROC=EBIT / (Net Working Capital + Net Fixed Assets).
EY = EBIT / Enterprise value
Enterprise Value=(Market value of equity + Net Interest-bearing debt)
To implement the strategy, investors start by identifying a universe of stocks, typically large-cap or mid-cap companies that trade on a major stock exchange. Next, they rank the stocks based on their ROC and EY. The companies with the best combination of these two metrics are considered the best investments (based on this ranking).
For example, a stock that ranks 10th on EY and 99th on ROIC gets a value of 109. The two ranks are simply added together and all stocks are ranked on the sum of the two ranks. The stocks with the lowest values are best.
All credits to "The Little Book That Beats The Market" by Joel Greenblatt
The Magic Formula strategy is a stock selection method popularized by Joel Greenblatt’s book The Little Book That Beats the Market.
It involves ranking companies based on Two factors:
A high return on capital and A high Earnings Yield.
The companies with the best combination of these two metrics are considered the best investments. The strategy aims to find undervalued companies with strong financials that have the potential for high returns over the long term.
Fundamental ScreenerThis indicator is designed to compare the year-over-year earnings and sales growth, as well as the P/E ratio of up to 10 stocks simultaneously .
This provides valuable insights into the fundamental performance of multiple stocks at the same time, allowing traders to quickly identify which stocks are outperforming or underperforming their peers.
The earnings and sales growth figures are calculated on a year-over-year basis , comparing the most recent quarter to the same quarter 1 year ago.
The P/E ratio is a valuation metric that measures a company's stock price relative to its trailing twelve months earnings per share.
By comparing these three key metrics across multiple stocks, traders can quickly identify which stock in a group has superior fundamentals.
Customization
Chose to compare 5 or 10 symbols
Table position, color, and size
ValueViewTitle: ValueView
Description:
ValueView is a script designed to cater to the needs of value investors. Its primary purpose is to provide a comprehensive overview of the financial performance of a stock, making it easier for investors to assess the intrinsic value and potential investment opportunities.
The script displays a concise summary of essential fundamental values and metrics in the form of a customizable table, directly integrated into the chart. This allows investors to evaluate the stock's performance for a variable number of fiscal years, as defined by the user. The input flexibility enables users to focus on the timeframes that are most relevant to their analysis.
ValueView works on timeframes greater than or equal to "DAY", ensuring that the data presented is reliable and relevant for long-term value investing strategies. With this feature, investors can focus on the bigger picture and avoid getting distracted by short-term fluctuations.
With ValueView, investors can choose to select or deselect specific metrics according to their investment strategy and preferences. This feature ensures that users are presented with the information they find most valuable, allowing them to make more informed decisions based on their unique perspective.
Key Features:
Quick overview of the financial performance of a stock for value investors
Customizable table displaying essential fundamental values and metrics
User-defined number of fiscal years for analysis
Select and deselect metrics to tailor the output to individual preferences
ValueView offers a convenient, time-saving solution for value investors looking to gain a deep understanding of a stock's financial performance. With its customizable features and easy-to-use interface, this script simplifies the process of identifying promising investments and making informed decisions.
Overvalued/Undervalued OverlayThis indicator will tell you whether the security you are looking at is overvalued or undervalued using a company's total assets and their market cap. In theory, a company's total assets is everything that they own, which then should technically be how much the company is worth. Therefore, if the company's market cap is higher than their total assets, the indicator will read "Overvalued by X%". However, if the company's market cap is lower than their total assets, the indicator will read "Undervalued by X%". If you have any questions, feel free to let me know. Keep in mind that this indicator should be only used for long-term investing.
Financial MetricsGives a sneak peak into some of the important financial ratios described below:
1. P/E : price to earnings ratio (Green when P/E<15)
2. PEG: Price to earnings growth ratio (Green when PEG<1)
3. P/S: Price to sales ratio (Green when P/S<2)
4. EV/FCF: Enterprise Value to Free Cashflow ratio
5. OPM: Operating Profit Margin % (Green when OPM>15%)
6. D/E: Debt to equity ratio (Green when D/E<1)
7. ROE: Return on equity % (Green when ROE>15%)
8. Div_Yield: Dividend yield
Disclaimer: All the limits defined are based on the widely accepted general values, but are subjective to particular sector or group of stocks. For example IT stocks command higher valuation than cyclical stocks like metal. So Compare with other stocks of the same sector to reach any conclusion.
