Ohlson O-Score IndicatorThe Ohlson O-Score is a financial metric developed by Olof Ohlson to predict the probability of a company experiencing financial distress. It is widely used by investors and analysts as a key tool for financial analysis.
Inputs:
Period: Select the financial period for analysis, either "FY" (Fiscal Year) or "FQ" (Fiscal Quarter).
Country: Specify the country for Gross Net Product data. This helps in tailoring the analysis to specific economic conditions.
Gross Net Product : Define the number of years back for the index to be set at 100. This parameter provides a historical context for the analysis.
Table Display : Customize the display of various tables to suit your preference and analytical needs.
Key Features:
Predictive Power : The Ohlson O-Score is renowned for its predictive power in assessing the financial health of a company. It incorporates multiple financial ratios and indicators to provide a comprehensive view.
Financial Distress Prediction : Use the O-Score to gauge the likelihood of a company facing financial distress in the future. It's a valuable tool for risk assessment.
Country-Specific Analysis : Tailor the analysis to the economic conditions of a specific country, ensuring a more accurate evaluation of financial health.
Historical Context : Set the Gross Net Product index at a specific historical point, allowing for a deeper understanding of how a company's financial health has evolved over time.
How to Use:
Select Period : Choose either Fiscal Year or Fiscal Quarter based on your preference.
Specify Country : Input the country for country-specific Gross Net Product data.
Set Historical Context : Determine the number of years back for the index to be set at 100, providing historical context to your analysis.
Custom Table Display : Personalize the display of various tables to focus on the metrics that matter most to you.
Calculation and component description
Here is the description of O-score components as found in orginal Ohlson publication :
1. SIZE = log(total assets/GNP price-level index). The index assumes a base value of 100 for 1968. Total assets are as reported in dollars. The index year is as of the year prior to the year of the balance sheet date. The procedure assures a real-time implementation of the model. The log transform has an important implication. Suppose two firms, A and B, have a balance sheet date in the same year, then the sign of PA - Pe is independent of the price-level index. (This will not follow unless the log transform is applied.) The latter is, of course, a desirable property.
2. TLTA = Total liabilities divided by total assets.
3. WCTA = Working capital divided by total assets.
4. CLCA = Current liabilities divided by current assets.
5. OENEG = One if total liabilities exceeds total assets, zero otherwise.
6. NITA = Net income divided by total assets.
7. FUTL = Funds provided by operations divided by total liabilities
8. INTWO = One if net income was negative for the last two years, zero otherwise.
9. CHIN = (NI, - NI,-1)/(| NIL + (NI-|), where NI, is net income for the most recent period. The denominator acts as a level indicator. The variable is thus intended to measure change in net income. (The measure appears to be due to McKibben ).
Interpretation
The foundational model for the O-Score evolved from an extensive study encompassing over 2000 companies, a notable leap from its predecessor, the Altman Z-Score, which examined a mere 66 companies. In direct comparison, the O-Score demonstrates significantly heightened accuracy in predicting bankruptcy within a 2-year horizon.
While the original Z-Score boasted an estimated accuracy of over 70%, later iterations reached impressive levels of 90%. Remarkably, the O-Score surpasses even these high benchmarks in accuracy.
It's essential to acknowledge that no mathematical model achieves 100% accuracy. While the O-Score excels in forecasting bankruptcy or solvency, its precision can be influenced by factors both internal and external to the formula.
For the O-Score, any results exceeding 0.5 indicate a heightened likelihood of the firm defaulting within two years. The O-Score stands as a robust tool in financial analysis, offering nuanced insights into a company's financial stability with a remarkable degree of accuracy.
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Earnings CountdownSince TradingView for some reason removed the small UI element in the symbol details window showing the amount of days left til a company releases its next earnings report, I decided to make my own.
A simple script with options for choosing the position and at what amount of days left the displayed color should change to red (mimicking the old feature).
I would suggest placing the indicator somewhere else than the main price chart, since it will be difficult to place it somewhere where it doesn't obscure something. Default is bottom and right since I place it on a separate volume indicator where the number is clearly visible.
THISMA cbpremiumDescription:
This script is tailored for traders interested in monitoring the premium difference between the Coinbase BTCUSD pair and another selected exchange.
Key Features:
- Customizable Exchange Selection: Users can input the symbol of any other exchange to compare against Coinbase's BTCUSD pair. The default comparison is set against BITFINEX:BTCUSD.
- Real-Time Premium Calculation: The script calculates the premium or discount of Coinbase's Bitcoin price over the chosen exchange. It does this by subtracting the closing price of Bitcoin on the selected exchange from Coinbase's closing price.
- Intuitive Color Coding: The premium difference is visually represented in a histogram format. If Coinbase's price is higher, the bar is shown in a bright yellow (RGB: 236, 222, 92), indicating a premium. If it's lower, the bar is displayed in a deep blue (RGB: 46, 125, 189), signifying a discount.
Applications:
- Market Comparison: This tool is excellent for traders who want to compare Bitcoin's market value across different exchanges quickly. It helps in identifying potential arbitrage opportunities.
- Price Analysis: By understanding the premium or discount of Bitcoin on Coinbase compared to another exchange, traders can gain insights into market sentiment and potential price movements on different platforms.
ROCE with 3-Year EMAThis Pine Script indicator, "3-Year EMA of Return on Capital Employed (ROCE)," is designed for investors and traders who incorporate both fundamental and technical analysis in their market approach. ROCE is a crucial metric for evaluating the efficiency and profitability of a company's capital employment. Our script enhances this analysis by overlaying a 3-year Exponential Moving Average (EMA) on the ROCE, allowing users to compare current performance against a longer-term trend.
Key Features:
ROCE Calculation: The script calculates the Return on Capital Employed (ROCE) using EBIT (Earnings Before Interest and Taxes) for the Trailing Twelve Months (TTM) and Capital Employed (Total Assets minus Short Term Debt) for the Fiscal Year (FY). This calculation provides a snapshot of how effectively a company is using its capital to generate profits.
3-Year EMA Overlay: The script features a 3-year EMA of the ROCE, providing a smoothed, long-term trend line. This EMA helps in identifying broader trends in a company's operational efficiency and profitability, making it easier to spot deviations from the historical norm.
Customizable for Different Data Frequencies: Whether your data is quarterly, monthly, or weekly, the script is adaptable. The length of the EMA is adjustable to suit the data frequency, ensuring accurate representation over a 3-year period.
Visualization: The ROCE and its 3-year EMA are plotted with distinct colors for easy comparison and analysis. This visual representation aids in quickly assessing the company's current performance against its historical trend.
Customization: Users can adjust the EMA length to match the frequency of their data (e.g., 12 for quarterly, 36 for monthly, 156 for weekly data).
Usage Tips:
Best used on companies with stable and consistent reporting.
Combine with other fundamental and technical indicators fo
r comprehensive analysis.
Disclaimer: This script is provided for informational and educational purposes only and should not be construed as investment advice.
Election Year GainsShows the yearly gains of the chart in U.S. Election years.
Use the options to turn on other years in the cycle.
For use with the 12M chart.
Will show non-sensical data with other intervals.
Crypto USD LiquidityThe "Crypto USD Liquidity " indicator is designed to offer a comprehensive analysis of liquidity dynamics within the cryptocurrency market, specifically focusing on various stablecoins. This versatile tool allows users to tailor their analysis by adjusting key parameters such as the Rate of Change (ROC) length and the smoothing rate.
The indicator incorporates a user-friendly interface with options to selectively display the supply data for major stablecoins, including USDT, BUSD, USDC, DAI, and TUSD . Users can toggle these options to observe and compare the liquidity trends of different stablecoin assets.
The total liquidity is computed as the summation of the selected stablecoin supplies, providing a holistic view of the overall crypto market liquidity. The Rate of Change (ROC) and its smoothing are then applied to the aggregated liquidity data. This process helps users identify trends and potential turning points in the liquidity landscape.
The visual representation on the chart includes a color-coded display: positive changing ROC values are shaded in green, indicating potential increases in liquidity, while negative values are shaded in red, suggesting potential decreases. This color scheme enhances the user's ability to quickly interpret the changing dynamics of stablecoin liquidity.
Moreover, the script includes a Zero Line for reference and overlays the raw ROC values for additional insight. The resulting chart not only serves as a powerful analytical tool for traders and investors but also contributes to a deeper understanding of the nuanced movements within the broader cryptocurrency market.
In summary, the "Crypto USD Liquidity" Pine Script indicator empowers users with a customizable and visually informative tool for analyzing and interpreting the complex dynamics of stablecoin liquidity, facilitating more informed decision-making in the realm of cryptocurrency trading and investment.
COT Index by NielsThe COT index is an indicator for determining trend reversals based on the net positions of commercials from the CFTC COT report.
A time frame of 26 weeks is selected as the basis. If the value is greater than or equal to 75, this is a bullish sign; if it is less than or equal to 25, this is a bearish sign.
You can select the number of weeks to be used for the calculation.
As the CFTC data is only published on Fridays at 21:30, the value of the current week is hidden until the market closes.
In addition, the background changes color when the index reaches an extreme range.
Both functions can be deactivated in the settings.
Hodl Calculation v1.0I have developed an indicator that calculates the value of our currency if we had periodically bought any stock or cryptocurrency on any exchange. I believe many individuals would be interested in computing such values.
You can customize the start and end times, choose the amount of currency to be used for each deal, and select from two frequency options.
The first option involves specific intervals, such as hourly, every three days, or bi-weekly.
The second option allows purchases at specific dates or times, like every 15th of the month at 12:00 PM, every Monday at 11:00 AM, or every day at 6:00 AM.
After selecting the frequency, the indicator performs calculations and presents statistical information in a table.
The summarized data includes frequency value, total selected period duration, number of deals, total quantity, total cost, current value, and profit/loss status.
MicroStrategy / Bitcoin Market Cap RatioThis indicator offers a unique analytical perspective by comparing the market capitalization of MicroStrategy (MSTR) with that of Bitcoin (BTC) . Designed for investors and analysts interested in the correlation between MicroStrategy's financial performance and the Bitcoin market, the script calculates and visualizes the ratio of MSTR's market capitalization to Bitcoin's market capitalization.
Key Features:
Start Date: The script considers data starting from July 28, 2020, aligning with MicroStrategy's initial announcement to invest in Bitcoin.
Data Sources: It retrieves real-time data for MSTR's total shares outstanding, MSTR's stock price, and BTC's market capitalization.
Market Cap Calculations: The script calculates MicroStrategy's market cap by multiplying its stock price with the total shares outstanding. It then forms a ratio of MSTR's market cap to BTC's market cap.
Bollinger Bands: To add a layer of analysis, the script includes Bollinger Bands around the ratio, with customizable parameters for length and multiplier. These bands can help identify overbought or oversold conditions in the relationship between MSTR's and BTC's market values.
The indicator plots the MSTR/BTC market cap ratio and the Bollinger Bands, providing a clear visual representation of the relationship between these two market values over time.
This indicator is ideal for users who are tracking the impact of Bitcoin's market movements on MicroStrategy's valuation or vice versa. It provides a novel way to visualize and analyze the interconnectedness of a leading cryptocurrency asset and a major corporate investor in the space.
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.
Free cash flow yieldThis script shows
- FCF Yield Net based on enterprise value. See reference: www.investopedia.com
- FCF Yield Diluted: which reduced CFC net by dilution amount.
- FCF % change.
This should give you a good overview on how well the company is at growing FCF and how efficiently they are creating FCF.
BTC ETF VolumesVolume
This script plots the trading volume of all BTC spot ETFs as well as the aggregate volume. Works on any chart and any timeframe.
Indicators
The volume of every ETF is plotted in a different color, with the total column adding up to the aggregate volume.
If you have price and indicator labels enabled you will also see individual ETF volume on your price scale on the right hand side.
If more BTC ETFs get launched I will add them.
Bitcoin ETF Tracker (BET)Get all the information you need about all the different Bitcoin ETFs.
With the Bitcoin ETF Tracker, you can observe all possible Bitcoin ETF data:
The ETF name.
The ticker.
The price.
The volume.
The share of total ETF volume.
The ETF fees.
The exchange and custodian.
At the bottom of the table, you'll find the day's total volume.
In addition, you can see the volume for the different Exchanges, as well as for the different Custodians.
If you don't want to display these lines to save space, you can uncheck "Show Additional Data" in the indicator settings.
The Idea
The goal is to provide the community with a tool for tracking all Bitcoin ETF data in a synthesized way, directly in your TradingView chart.
How to Use
Simply read the information in the table. You can hover above the Fees and Exchanges cells for more details.
The table takes space on the chart, you can remove the extra lines by unchecking "Show Additional Data" in the indicator settings or reduce text size by changing the "Table Text Size" parameter.
Upcoming Features
As soon as we have a little more history, we'll add variation rates as well as plots to observe the breakdown between the various Exchanges and Custodians.
MVRV Z-ScoreThe MVRV ratio was created by Murad Mahmudov & David Puell. It simply compares Market Cap to Realised Cap, presenting a ratio (MVRV = Market Cap / Realised Cap). The MVRV Z-Score is a later version, refining the metric by normalising the peaks and troughs of the data.
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
Volume Exhaustion [AlgoAlpha]Introducing the Volume Exhaustion by AlgoAlpha, is an innovative tool that aims to identify potential exhaustion or peaks in trading volume , which can be a key indicator for reversals or continuations in market trends 🔶.
Key Features:
Signal Plotting : A special feature is the plotting of 'Release' signals, marked by orange diamonds, indicating points where the exhaustion index crosses under its previous value and is above a certain boundary. This could signify critical market points 🚨.
Calculation Length Customization : Users can adjust the calculation and Signal lengths to suit their trading style, allowing for flexibility in analysis over different time periods. ☝️
len = input(50, "Calculation Length")
len2 = input(8, "Signal Length")
Visual Appeal : The script offers customizable colors (col for the indicator and col1 for the background) enhancing the visual clarity and user experience 💡.
col = input.color(color.white, "Indicator Color")
col1 = input.color(color.gray, "Background Color")
Advanced Volume Processing : At its core, the script utilizes a combination of Hull Moving Average (HMA) and Exponential Moving Average (EMA) applied to the volume data. This sophisticated approach helps in smoothing out the volume data and reducing lag.
sv = ta.hma(volume, len)
ssv = ta.hma(sv, len)
Volume Exhaustion Detection : The script calculates the difference between the volume and its smoothed version, normalizing this value to create an exhaustion index (fff). Positive values of this index suggest potential volume exhaustion.
f = sv-ssv
ff = (f) / (ta.ema(ta.highest(f, len) - ta.lowest(f, len), len)) * 100
fff = ff > 0 ? ff : 0
Boundary and Zero Line : The script includes a boundary line (boundary) and a zero line (zero), with the area between them filled for enhanced visual interpretation. This helps in assessing the relative position of the exhaustion index.
Customizable Background : The script colors the background of the chart for better readability and to distinguish the indicator’s area clearly.
Overall, Volume Exhaustion is designed for traders who focus on volume analysis. It provides a unique perspective on volume trends and potential exhaustion points, which can be crucial for making informed trading decisions. This script is a valuable addition for traders looking to enhance their trading experience with advanced volume analysis tools.
Market Health MonitorThe Market Health Monitor is a comprehensive tool designed to assess and visualize the economic health of a market, providing traders with vital insights into both current and future market conditions. This script integrates a range of critical economic indicators, including unemployment rates, inflation, Federal Reserve funds rates, consumer confidence, and housing market indices, to form a robust understanding of the overall economic landscape.
Drawing on a variety of data sources, the Market Health Monitor employs moving averages over periods of 3, 12, 36, and 120 months, corresponding to quarterly, annual, three-year, and ten-year economic cycles. This selection of timeframes is specifically chosen to capture the nuances of economic movements across different phases, providing a balanced view that is sensitive to both immediate changes and long-term trends.
Key Features:
Economic Indicators Integration: The script synthesizes crucial economic data such as unemployment rates, inflation levels, and housing market trends, offering a multi-dimensional perspective on market health.
Adaptability to Market Conditions: The inclusion of both short-term and long-term moving averages allows the Market Health Monitor to adapt to varying market conditions, making it a versatile tool for different trading strategies.
Oscillator Thresholds for Recession and Growth: The script sets specific thresholds that, when crossed, indicate either potential economic downturns (recessions) or periods of growth (expansions), allowing traders to anticipate and react to changing market conditions proactively.
Color-Coded Visualization: The Market Health Monitor employs a color-coding system for ease of interpretation:
-- A red background signals unhealthy economic conditions, cautioning traders about potential risks.
-- A bright red background indicates a confirmed recession, as declared by the NBER, signaling a critical time for traders to reassess risk exposure.
-- A green background suggests a healthy market with expected economic expansion, pointing towards growth-oriented opportunities.
Comprehensive Market Analysis: By combining various economic indicators, the script offers a holistic view of the market, enabling traders to make well-informed decisions based on a thorough understanding of the economic environment.
Key Criteria and Parameters:
Economic Indicators:
Labor Market: The unemployment rate is a critical indicator of economic health.
High or rising unemployment indicates reduced consumer spending and economic stress.
Inflation: Key for understanding monetary policy and consumer purchasing power.
Persistent high inflation can lead to economic instability, while deflation can signal weak
demand.
Monetary Policy: Reflected by the Federal Reserve funds rate.
Changes in the rate can influence economic activity, borrowing costs, and investor
sentiment.
Consumer Confidence: A predictor of consumer spending and economic activity.
Reflects the public’s perception of the economy
Housing Market: The housing market often leads the economy into recession and recovery.
Weakness here can signal broader economic problems.
Market Data:
Stock Market Indices: Reflect overall investor sentiment and economic
expectations. No gains in a stock market could potentially indicate that economy is
slowing down.
Credit Conditions: Indicated by the tightness of bank lending, signaling risk
perception.
Commodity Insight:
Crude Oil Prices: A proxy for global economic activity.
Indicator Timeframe:
A default monthly timeframe is chosen to align with the release frequency of many economic indicators, offering a balanced view between timely data and avoiding too much noise from short-term fluctuations. Surely, it can be chosen by trader / analyst.
The Market Health Monitor is more than just a trading tool—it's a comprehensive economic guide. It's designed for traders who value an in-depth understanding of the economic climate. By offering insights into both current conditions and future trends, it encourages traders to navigate the markets with confidence, whether through turbulent times or in periods of growth. This tool doesn't just help you follow the market—it helps you understand it.
[Suitable Hope] Crypto Marketcap Dominance OverviewThe Crypto Marketcap Dominance Overview indicator is a simple yet very useful indicator that aims at helping traders identify where the crypto liquidity is flowing. The indicator uses Cryptocap's real time crypto marketcap dominance data (in %) between several key categories:
- Bitcoin
- True total 2 (altcoins and Ethereum excluding the top 3 biggest stablecoins)
- True total 3 (altcoins excl. Ethereum and the top 3 biggest stablecoins)
- Ethereum
- Stablecoins
- Defi.
The indicator works across all timeframes but is best used on the default daily timeframe to identify changes in liquidity trends between the different categories. More categories can be expected to be added in the future; depending on Cryptocap's available data.
Traders or users of this indicator have a selections of options:
- Choose a dedicated timeframe
- Turn on/off the individual categories they wish to use
- Turn on/off labels
- Change global colour coding of each category and label
- Activate or deactive the 0 to 100% bands
Although there are a couple of similar indicators trying to do something similar, I tend to find them lacking clarity. I coded this indicator to provide a more simple and clearer view of the crypto marketcap dominance. I hope you find this indicator helpful.
Happy trading and good luck!
ETH Crypto P/S RatioP/S ratio = Crypto Asset Market Capitalization / Annual Sales Revenue
The indicator divides the Market Capitalization by the total annual ETH fees from Glassnode.
How to read it:
A low P/S ratio means that the crypto price is undervalued relative to the fees that are generated, while a high P/S ratio signifies that the price is overvalued.
Central Bank Liquidity YOY % ChangeThis shows the percent change from a year ago (YOY%) in Central Bank Liquidity
It's important to the study rate of change data in this liquidity metric and compare it to the nominal chart.
When this chart is accelerating, liquidity is being added, meaning it's a good time to be in assets.
When this chart is declining, liquidity is being removed, meaning it's a good time to be in cash.
Bottoms in markets coincide with the rate of change of liquidity going from negative (below the zero line) to positive (above zero)
Central Bank Liquidity = Total value of the assets of all Federal Reserve Banks - Overnight Reverse Repurchase Agreements (RRP) - The Treasury General Account (TGA)
Stock's Intrinsic Value| DCF modelScript Description
This pine script is based on a YouTube video titled: Warren Buffett: How to Calculate the Intrinsic Value of a Stock. Warren Buffett is a famous value investor who follows the principles of his mentor Benjamin Graham. He looks for companies that have strong competitive advantages, consistent earnings, and low debt. He also considers the intrinsic value of a company, which is the present value of its future cash flows, and compares it to the market price. He prefers to buy stocks that are trading below their intrinsic value and hold them for a long time.
One of the methods that Buffett uses to estimate the intrinsic value of a company is the discounted cash flow (DCF) model. This involves projecting the free cash flow (FCF) of the company for several years and then discounting it back to the present using an appropriate discount rate. The discount rate is usually the weighted average cost of capital (WACC) of the company, which reflects its cost of equity and debt. The sum of the discounted FCFs and terminal value is the intrinsic value of the company.
Lastly, a margin of safety is included when using the DCF method for stock valuation because of uncertainty and error in estimating future cash flows and the intrinsic value of the company.
When the current price is below margin of safety, it means that the stock is currently undervalued and being price at significantly below its intrinsic value.
Guideline for determining each variable in this script
FCF growth rate: This is the annual rate at which the free cash flow (FCF) of the company is expected to grow over a forecast 10-year period. You can use historical FCF growth rates, industry averages, analyst estimates, or your assumptions to project the FCF growth rate. The higher the FCF growth rate, the higher the intrinsic value will be.
Discount rate: This is the rate of return that you require to invest in the company. It reflects the risk and opportunity cost of investing in the company. You can use the weighted average cost of capital (WACC) of the company, capital pricing model (CAPM), hurdle rate, or market rate as the discount rate. The lower the discount rate, the higher the intrinsic value.
The margin of safety: Provides a cushion against errors in the valuation or adverse events that may affect the company. The margin of safety depends on your personal preference and risk tolerance. Normally is at 15% - 30%, the higher the margin of safety you set, the lower the chance that the stock will hit that level.
How to use this script
Step 1: This script only works for stocks that have financial data of free cash flow and total common shares outstanding
Step 2: Please use a yearly chart (12-month chart)
Step 3: You are required to determine a growth rate that will grow the free cash flow 10 years into the future
Step 4: You are required to determine a discount rate for the calculations
Step 5: You are required to add a margin of safety (Accounting for uncertainty)
Step 6: The rest of the calculations will be done automatically.
Disclaimer when using this script
I'm not a financial advisor
This script is for education purposes only
There are risks involved with stock market investing and investors should not act upon the content or information found here without first seeking advice from an accountant, financial planner, lawyer or other professional.
I can’t guarantee that this script will be error-free as I still consider myself a Pinescript beginner
Before making any decisions, investors should always research companies individually
I'll not be liable for any loss incurred, arising from the use of, or reliance on, this script
Limitations of this script
This script only works on the yearly chart (12 monthly charts)
The intrinsic value of a company will be negative if the company have a negative forecasted free cash flow
You need to make an educated guess about the growth rate, discount rate and margin of safety
This script uses free cash flow instead of owner's earnings (Operating cash flow - Maintenance capital expenditure), therefore it can't accurately estimate the maintenance capital expenditure.
Need at least 6 years’ worth of financial data
Market capitalisation uses total common shares outstanding multiplied by the closing price instead of using company-level total outstanding shares multiplied by the closing price
Analytics Trading DashboardThe Analytics Trading Dashboard is a tool designed to bring key information about a company into an easy-to-view dashboard. The indicator combines Company Info, Fundamental Data, Price & Volume Data, and Analyst Recommendations all into one table.
Let’s dive into the details by section:
Company Info:
Name – Company name.
Market Cap – Total dollar market value of the company’s outstanding shares of stock.
Float Shares / Shares Outstanding – Floating shares indicate the number of shares available for trading. Outstanding shares are any shares held by shareholders and company insiders.
Sector – The stock's sector.
Industry Group - The industry group the stock belongs to.
IPO Date – Date on which a security is first publicly traded.
Dividend – The latest dividend amount if the company pays one.
Fundamental Data:
EPS Due – The date the company is set to report earnings next.
EPS Est Next Qtr – The earnings per share estimate for the upcoming report.
EPS Est % Chg (Current Qtr) – The earnings growth as a percentage based on the reported earnings of the same quarter from the previous year.
EPS % Chg (Last Qtr) – The earnings growth of the last reported quarter as a percentage versus the same quarter from the previous year.
Last Qtr EPS Surprise – The amount reported earnings beat or missed estimates from the last reported quarter.
Last 3 Qtrs Avg. EPS Growth – The average percentage growth of the last 3 earnings reports.
# Qtrs of EPS Acceleration – The number of consecutive quarters that EPS has increased.
Last 3 Qtrs Avg. Rev Growth – The average percentage growth of the last 3 revenue numbers reported.
# Qtrs of Rev Acceleration – The number of consecutive quarters that revenue has increased.
Gross Margin – Measures gross profit compared to revenue as a percentage.
Debt/Equity Ratio – The ratio of debt to equity, or financial leverage.
Price and Volume Data:
52 Week High – The highest high of the last 52 weeks.
% Off 52 Week High – The percentage the current price has decreased from the 52-week high.
Price vs. Moving Average – The distance as a percentage that the current price is from the selected moving average.
Average Volume – The average number of shares traded based on the selected lookback period.
Average $ Volume – The average of the total value of shares traded based on the selected lookback period.
Pocket Pivots – The number of pocket pivots that have occurred in the selected lookback period.
Up/Down Volume Ratio - A 50-day ratio derived by dividing total volume on up days by the total volume on down days.
ATR – The average true range shown as a dollar value and percentage of current price.
ADR – The average daily range shown as a dollar value and percentage of current price.
Beta - Beta is a measure of its volatility relative to the overall market, indicating how much the stock's price is expected to fluctuate compared to the market average.
Analyst Ratings:
Strong Buy – The number of strong buy recommendations.
Buy – The number of buy recommendations.
Hold – The number of hold recommendations.
Sell – The number of sell recommendations.
Strong Sell – The number of strong sell recommendations.
The Analytics Trading Dashboard also comes with the flexibility to select your preferred moving average for price and volume analysis, as well as to choose the specific lookback period for calculating the Average True Range (ATR), Average Daily Range (ADR), and Pocket Pivots lookback period.
Limited Growth Stock-to-Flow (LGS2F) [AlgoAlpha]Description:
The "∂ Limited Growth Stock-to-Flow (LG-S2F)" indicator, developed by AlgoAlpha, is a technical analysis tool designed to analyze the price of Bitcoin (BTC) based on the Stock-to-Flow model. The indicator calculates the expected price range of BTC by incorporating variables such as BTC supply, block height, and model parameters. It also includes error bands to indicate potential overbought and oversold conditions.
How it Works:
The LG-S2F indicator utilizes the Stock-to-Flow model, which measures the scarcity of an asset by comparing its circulating supply (stock) to its newly produced supply (flow). In this script, the BTC supply and block height data are obtained to calculate the price using the model formula. The formula includes coefficients (a, b, c) and exponentiation functions to derive the expected price.
The script incorporates error bands based on uncertainty values derived from the standard errors of the model parameters. These error bands indicate the potential range of variation in the expected price, accounting for uncertainties in the model's parameters. The upper and lower error bands visualize potential overbought and oversold conditions, respectively.
Usage:
Traders can utilize the LG-S2F indicator to gain insights into the potential price movements of Bitcoin. The indicator's main line represents the expected price, while the error bands highlight the potential range of variation. Traders may consider taking long positions when the price is near or below the lower error band and short positions when the price is close to or above the upper error band.
It's important to note that the LG-S2F indicator is specifically designed for Bitcoin and relies on the Stock-to-Flow model. Users should exercise caution and consider additional analysis and factors before making trading decisions solely based on this indicator.
Originality:
The LG-S2F indicator, developed by QuantMario and AlgoAlpha, is an original implementation that combines the Stock-to-Flow model with error bands to provide a comprehensive view of BTC's potential price range. While the concept of Stock-to-Flow analysis exists, the specific calculations, incorporation of error bands, and customization options in this script are unique to QuantMario's methodology. The script is released under Mozilla Public License 2.0, allowing users to utilize and modify it while adhering to the license terms.
