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Financial

MMRI Chart (Primary)The **Mannarino Market Risk Indicator (MMRI)** is a financial risk measurement tool created by financial strategist Gregory Mannarino. It’s designed to assess the risk level in the stock market and economy based on current bond market conditions and the strength of the U.S. dollar. The MMRI considers factors like the U.S. 10-Year Treasury Yield and the Dollar Index (DXY), which indicate investor confidence in government debt and the dollar's purchasing power, respectively. The formula for MMRI uses the 10-Year Treasury Yield multiplied by the Dollar Index, divided by a constant (1.61) to normalize the risk measure. A higher MMRI score suggests increased market risk, while a lower score indicates more stability. Mannarino has set certain thresholds to interpret the MMRI score: - **Below 100**: Low risk. - **100–200**: Moderate risk. - **200–300**: High risk. - **Above 300**: Extreme risk, indicating market instability and potential downturns. This tool aims to provide insight into economic conditions that may affect asset classes like stocks, bonds, and precious metals. Mannarino often updates MMRI scores and risk analyses in his public market updates.
Pine Script® indicator
by Emilio2014
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.
Pine Script® indicator
by YavuzAkbay
1
Financial Ratios Fundamental StrategyWhat are financial ratios? Financial ratios are basic calculations using quantitative data from a company’s financial statements. They are used to get insights and important information on the company’s performance, profitability, and financial health. Common financial ratios come from a company’s balance sheet, income statement, and cash flow statement. Businesses use financial ratios to determine liquidity, debt concentration, growth, profitability, and market value. The common financial ratios every business should track are 1) liquidity ratios 2) leverage ratios 3)efficiency ratio 4) profitability ratios 5) market value ratios. Initially I had a big list of 20 different ratios for testing, but in the end I decided to stick for the strategy with these ones : Current ratio: Current Assets / Current Liabilities The current ratio measures how a business’s current assets, such as cash, cash equivalents, accounts receivable, and inventories, are used to settle current liabilities such as accounts payable. Interest coverage ratio: EBIT / Interest expenses Companies generally pay interest on corporate debt. The interest coverage ratio shows if a company’s revenue after operating expenses can cover interest liabilities. Payables turnover ratio: Cost of Goods sold (or net credit purchases) / Average Accounts Payable The payables turnover ratio calculates how quickly a business pays its suppliers and creditors. Gross margin: Gross profit / Net sales The gross margin ratio measures how much profit a business makes after the cost of goods and services compared to net sales. With this data, I have created the long and long exit strategy: For long, if any of the 4 listed ratios,such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is ascending after a quarter, its a potential long entry. For example in january the gross margin ratio is at 10% and in april is at 15%, this is an increase from a quarter to another, so it will get a long entry trigger. The same could happen if any of the 4 listed ratios follow the ascending condition since they are all treated equally as important For exit, if any of the 4 listed ratios are descending after a quarter, such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is descending after a quarter, its a potential long exit. For example in april we entered a long trade, and in july data from gross margin comes as 12% . In this case it fell down from 15% to 12%, triggering an exit for our trade. However there is a special case with this strategy, in order to make it more re active and make use of the compound effect: So lets say on july 1 when the data came in, the gross margin data came descending (indicating an exit for the long trade), however at the same the interest coverage ratio came as positive, or any of the other 3 left ratios left . In that case the next day after the trade closed, it will enter a new long position and wait again until a new quarter data for the financial is being published. Regarding the guidelines of tradingview, they recommend to have more than 100 trades. With this type of strategy, using Daily timeframe and data from financials coming each quarter(4 times a year), we only have the financial data available since 2016, so that makes 28 quarters of data, making a maximum potential of 28 trades. This can however be "bypassed" to check the integrity of the strategy and its edge, by taking for example multiple stocks and test them in a row, for example, appl, msft, goog, brk and so on, and you can see the correlation between them all. At the same time I have to say that this strategy is more as an educational one since it miss a risk management and other additional filters to make it more adapted for real live trading, and instead serves as a guiding tool for those that want to make use of fundamentals in their trades If you have any questions, please let me know !
Pine Script® strategy
by exlux
6
Price RatiosJust a handy financial ratio bar where you can quickly view key price ratios. Position, text size and color combinations can be set from input settings. Header is readjusted according to the table position chosen. For example, if position selected as top-center or bottom-center or middle-center, orientation of the table will be horizantal and would display like this: Otherwise, table will have vertical orientation like this: You can also move it to new panel and use it along with other financials scripts such as: Relative-Growth-Screen Quality-Screen With that, your screen would look something like this:
Pine Script® indicator
by Trendoscope
6
Financial Highlights [Fundamentals]█ OVERVIEW This indicator plot basic key financial data to imitate the presentation format of several popular finance site, make it easier for a quick glance of overall company financial health without switching tabs for every single stocks. █ Financial Data Available: - Revenue & PAT (Profit after Tax) - Net Profit Margin (%) - Gross Profit Margin (%) - Earnings Per Share (EPS) - Dividend █ Features: - Toggle between Quarter/Annual Financial Data (Notes: For Dividends, it will always be plotted based on Annual data, at Financial Year ending period) - Options to plot at either at Quarter/Yearly ending period OR Financial Data published date █ Limitation - The accuracy of the data subject to Tradingview's source, but from my observation it's accurate 95% of the time - Recently published data might not be available immediately. e.g. MYX exchange tends to have 1-3 days lag - More information on Tradingview's financial data can be read here -> www.tradingview.com █ Disclaimer Past performance is not an indicator of future results. My opinions and research are my own and do not constitute financial advice in any way whatsoever. Nothing published by me constitutes an investment recommendation, nor should any data or Content published by me be relied upon for any investment/trading activities. I strongly recommends that you perform your own independent research and/or speak with a qualified investment professional before making any financial decisions. Any ideas to further improve this indicator are welcome :)
Pine Script® indicator
by fareidzulkifli
15
Statistical and Financial MetricsGood morning traders! This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market) By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle Here are the metrics you can have by storing data from a variable period of candles (by default 51): ✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE) ✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER) ✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close ✓ Covariance of the two datasets (in BLUE) ✓ Correlation coefficient of the two datasets (in AQUA) ✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same). WHAT IS BETA (β)? The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds. We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk). The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio. Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset. So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld. In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f) where: r_i = expected yeld of the asset r_f = risk free interest rate β = beta r_m = yeld of market portfolio I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
Pine Script® indicator
by Drun30
2