Liquidity Dependent Price Stability AlgorithmThe Liquidity Dependent Price Stability (LDPS) indicator is designed to measure liquidity levels on an equity and, from those measurements, provide Bullish or Bearish outlooks for future price action. These outlooks are given via reporting the equity's Liquidity Condition and Liquidity Flow.
Interpretation
Liquidity Condition (LC) and Liquidity Flow (LF) measurements are displayed with color-specific chart colors and/or with text output.
LC can be reported as "Weak Bullish", "Bullish", or "Strong Bullish" for Bullish outlooks and "Weak Bearish", "Bearish" or "Strong Bearish" for Bearish outlooks. LC can also just be reported as "Bullish" or "Bearish".
Bullish LCs have a statistical correlation with future price appreciation, and Bearish LCs have a statistical correlation with price depreciation. When LC is “Bullish”, the price is likely to go up, and if LC is “Bearish”, the price is likely to go down.
Liquidity Flow (LF) is a measure of how LC is changing. When LC is becoming more bullish, LF is reported as “Improving”. When LC is becoming more bearish, LF is reported as “Worsening”. LF is only displayed via text output.
Settings and Configurations
LDPS Sensitivity and Reactivity: Determines if you want LDPS to be more sensitive to changing conditions or less sensitive. This choice affects how certain LDPS is when forming its future outlooks. LDPS achieves this increase in sensitivity and reactivity by lowering the bar for what LDPS considers a significant change.
Aggressive : LDPS will optimize reporting early changes in LC and LF at the expensive of accuracy. Aggressive is good for low-risk trading styles that prefer to exit a position early rather than deal with increased risk of oppositional movement.
Balanced : LDPS will try to balance reporting changes in LC and LF with maintaining accuracy. Balanced style is a good setting to start out with and is applicable across the widest range of equity’s and timeframes.
Conservative : LDPS will optimize accuracy over being sensitive to changes in LC or LF. Conservative is a good choice for lower timeframes and traders who only want to change or exit positions with the greatest confidence.
LDPS Reporting Style: Determines how you want LC to be reported.
Simplified : LDPS will only report LC as “Bullish” or “Bearish”.
Full : LDPS will increase its reporting details and include the “Strong” and “Weak” pre-fixes, when appropriate.
LDPS Candle Coloring: There are three different ways that LC can be reported on the chart via coloring.
LDPS Candle Replacement: This will replace the chart’s default candles with those created by LDPS. Note: In order to see LDPS’ candles and not the chart’s, you have to disable to chart’s candles. This can be done in Settings -> Symbol and unchecking “Body”, “Borders” and “Wick” boxes.
LDPS Candle Coloring: This will just color the bodies of the chart’s default candles. Note: This setting should not have the chart’s candle’s disabled.
LDPS Background Coloring: This will color the chart’s background rather than any candles.
LDPS Text Output: LC and LF are reported via a text box that can be moved several places on the chart, or the text box can be removed.
LDPS Measurements – Display: When selected, LC and LF will be reported via the text box.
LDPS Measurement – Text Location: Determines where the text box with LC and LF are located.
LDPS Measurement – Text Size: Determines the size of LC and LF within the text box.
LDPS Measurement – Background Color: Determines the background color of the text box with LC and LF.
LDPS Condition Color Selection – Bullish / Bearish: Color selection for each type of LC. Note: If the Simplified reporting style is selected, the “Full Bullish” and “Full Bearish” are the bullish and bearish color choices, respectively.
Frequently Asked Questions:
Where can I get additional Information?
Please check the “Author’s Instructions” section below.
Where can I find the results of the LDPS research?
Please check the “Author’s Instructions” section below.
Help! Something’s not working!
Apologies. Please see the email listed in “Author’s Instructions” below and let’s get started on solving the issue.
Which Sensitivity setting should I use?
The author’s preference is Conservative in most cases, but the answer for you depends on your preferred style.
An analogy might help: the aggressive setting will ensure LDPS is early to the party – every party. Of the parties that really kick off, you can be certain LDPS is there, but they had to visit a several of parties before finding the right one.
The Conservative setting won’t bring LDPS to every party – it will gladly stay at the one it’s at but when it detects the next real big hit, LDPS will move to that party instead. It won’t be the first one there, but it is definitely earlier than most.
Should I use the Full or Simplified reporting style?
Depending on how engaged you are with the particular equity or position, either choice can be beneficial. The Full reporting style will let you detect changes in LC before they might show with the Simplified reporting style. Some enjoy the additional data, some (like the Author) enjoy keeping things simple.
I can see LDPS’ colors in the chart’s candlesticks when the settings are open, but not when the settings are closed. How come?
If you are using the “LDPS Candle Replacement” setting, be sure to turn off the Chart’s default candles by right-clicking on the chart, going to Settings, then Symbol and then un-checking “Body”, “Border” and “Wick”. This should fix the issue.
I think there’s a bug – where do I report it?
Thank you for reaching out about a potential bug or issue! Please see the email below in “Author’s Instructions” to report the issue.
Statistics
LDPM Crossover Scanner AddonThe LDPM Crossover Scanner is designed to be used in conjunction with the Liquidity Dependent Price Movement Algorithm and is included with LDPM access.
The LDPM Crossover Scanner displays the LDPM status for up to 10 equity's. When conditions are bearish, per LDPM, the equity will light up on the scanner; otherwise, the equity will not light up.
When used in aggregate, this becomes a particularly useful way to measure up-coming market moves (especially when the crossover scanner showcases equities with significant beta to the chart's underlying!).
Liquidity Dependent Price Movement AlgorithmLiquidity-Dependent Price Movement (LDPM) is a metric designed to directly measure liquidity on a equity in real time, and to translate those measurements into signals to provide insights into where the anticipate price-direction is headed.
Liquidity can be characterized as a way of measuring how smoothly things are running in the market. When things are running smoothly – such as when there is good agreement as to the price of an asset, then things are considered liquid. Conversely, when things are not running smoothly, just as when the bid or the ask do not agree with each other, then things are considered not liquid. These different states have different outcome liklihoods.
In a liquid environment, a stock can trade a lot of shares without moving the price. On the other hand, when a stock is not liquid, even small volumes can move the price substantially.
It is therefore helpful to know when a stock is liquid to the upside or to the downside, or even, when a stock is not liquid to the upside or the downside. These data have statistical associations with future price movement and volatility.
The use of LDPM is straightforward:
If the price is above LDPM: bullish outlooks.
If the price is below LDPM: bearish outlooks.
There are a few key differences about LDPM as compared to other indicators, namely that timeframe matters . That means, LDPM will tailor its output to the timeframe selected. The advantage of this is that it allows LDPM to be "tailored" to the specific timeframe as desired, without having to do any conversions or adaptations mentally.
Key Settings and Configurations:
Setting - Smoothing Type of LDPM :
Default: KF.
LDPM can be smoothened if desired. There are 5 different types of smoothing available:
EMA : Exponential Smoothing
SMA : Simple Smoothing
WMA : Weighted Smoothing
RMA : Modified Smoothing
KF : Kellman Smoothing
The default is "KF" for Kellman Smoothing.
Setting - Include LDPM-Granular :
Default: Off.
LDPM-Granular is the more "raw" form of LDPM that displays the candle-specific result, rather than the smoothened result. This can be toggled on or off, if desired. LDPM granular is helpful for looking at candle-specific
Setting - Place LDPM Standard :
Default: Off.
An additional, single, LDPM line can be placed via this toggle. Settings for this LDPM can be configured directly below toggle.
Setting - Place LDPM-Fib :
Default: On.
LDPM-Fib is a default setting for displaying 5 LDPMs (LDPM-13, LDPM-21, LDPM-34, LDPM-55, and LDPM-89) whose lookbacks are spaced via the Fib sequence. Useful for those who enjoy a static relationship between the different "layers" of LDPM.
Setting - Place LDPM-Reference :
Default: Off.
Since LDPM is time-interval dependent, there may be times when a higher-order timeframe is desired to act as a reference. For instance, suppose you want to go long if the 1-Hour LDPM experiences a bullish crossover, but you want to scalp shorts on the 15-minute timeframe until then. Then you could place the chart on the 15-minute interval for your scalping, and then place a 1-Hour reference LDPM that will show you when the 1-Hour LDPM and price experience a crossover.
Note: The reference must be a higher-order timeframe. So if your chart is on the 15-minute, you can only reference timeframes greater than 15.
Setting - LDPM Box Creation :
Default: On.
Instead of implementing a reference LDPM, it is possible to display the other timeframes in a data table with conditional coloring for if the overall LDPM-Price relationship is bullish or bearish.
Why Chose LDPM
There are no other Liquidity-measuring indicators available to the retail investor. Measuring liquidity often requires the use of expensive data and high-throughput computing to be used in real-time. Neither of these requirements apply to utilizing LDPM.
Additionally, the data are supportive that LDPM provides statistically significant, price-direction-correct outlooks.
Volatility and Volume by Hour EXT(Extended republication, use this instead of the old one)
The goal of this indicator is to show a “characteristic” of the instrument, regarding the price change and trading volume. You can see how the instrument “behaved” throughout the day in the lookback period. I've found this useful for timing in day trading.
The indicator creates a table on the chart to display various statistics for each hour of the day.
Important: ONLY SHOWS THE TABLE IF THE CHART’S TIMEFRAME IS 1H!
Explanation of the columns:
1. Volatility Percentage (Volat): This column shows the volatility of the price as a percentage. For example, a value of "15%" means the price movement was 15% of the total daily price movement within the hour.
2. Hourly Point Change (PointCh): This column shows the change in price points for each hour in the lookback period. For example, a value of "5" means the price has increased by 5 points in the hour, while "-3" means it has decreased by 3 points.
3. Hourly Point Change Percentage (PrCh% (LeverageX)): This column shows the percentage change in price points for each hour, adjusted with leverage multiplier. Displayed green (+) or red (-) accordingly. For example, a value of "10%" with a leverage of 2X means the price has effectively changed by 5% due to the leverage.
4. Trading Volume Percentage (TrVol): This column shows the percentage of the daily total volume that was traded in a specific hour. For example, a value of "10%" would mean that 10% of the day's total trading volume occurred in that hour.
5. Added New! - Relevancy Check: The indicator checks the last 24 candle. If the direction of the price movement was the same in the last 24 hour as the statistical direction in that hour, the background of the relevant hour in the second column goes green.
For example: if today at 9 o'clock the price went lower, so as at 9 o'clock in the loopback period, the instrument "behaves" according to statistics . So the statistics is probably more relevant for today. The more green background row the more relevancy.
Settings:
1. Lookback period: The lookback period is the number of previous bars from which data is taken to perform calculations. In this script, it's used in a loop that iterates over a certain number of past bars to calculate the statistics. TIP: Select a period the contains a trend in one direction, because an upward and a downward trend compensate the price movement in opposite directions.
2. Timezone: This is a string input that represents the user's timezone. The default value is "UTC+2". Adjust it to your timezone in order to view the hours properly.
3. Leverage: The default value is 10(!). This input is used to adjust the hourly point change percentage. For FOREX traders (for example) the statistics can show the leveraged percentage of price change. Set that according the leverage you trade the instrument with.
Use at your own risk, provided “as is” basis!
Hope you find it useful! Cheers!
trend_switch
█ Description
Asset price data was time series data, commonly consisting of trends, seasonality, and noise. Many applicable indicators help traders to determine between trend or momentum to make a better trading decision based on their preferences. In some cases, there is little to no clear market direction, and price range. It feels much more appropriate to use a shorter trend identifier, until clearly defined market trend. The indicator/strategy developed with the notion aims to automatically switch between shorter and longer trend following indicator. There were many methods that can be applied and switched between, however in this indicator/strategy will be limited to the use of predictive moving average and MESA adaptive moving average (Ehlers), by first determining if there is a strong trend identified by calculating the slope, if slope value is between upper and lower threshold assumed there is not much price direction.
█ Formula
// predictive moving average
predict = (2*wma1-wma2)
trigger = (4*predict+3*predict +2*predict *predict)
// MESA adaptive moving average
mama = alpha*src+(1-alpha)*mama
fama = .5*alpha*mama+(1-.5-alpha)*fama
█ Feature
The indicator will have a specified default parameter of:
source = ohlc4
lookback period = 10
threshold = 10
fast limit = 0.5
slow limit = 0.05
Strategy type can be switched between Long/Short only and Long-Short strategy
Strategy backtest period
█ How it works
If slope between the upper (red) and lower (green) threshold line, assume there is little to no clear market direction, thus signal predictive moving average indicator
If slope is above the upper (red) or below the lower (green) threshold line, assume there is a clear trend forming, the signal generated from the MESA adaptive moving average indicator
█ Example 1 - Slope fall between the Threshold - activate shorter trend
█ Example 2 - Slope fall above/below Threshold - activate longer trend
Normalized Z-ScoreThe Normalized Z-Score indicator is designed to help traders identify overbought or oversold conditions in a security's price. This indicator can provide valuable signals for potential buy or sell opportunities by analyzing price deviations from their average values.
How It Works :
-- Z-Score Calculation:
---- The indicator calculates the Z-Score for both high and low prices over a user-defined period (default is 14 periods).
---- The Z-Score measures how far a price deviates from its average in terms of standard deviations.
-- Average Z-Score:
---- The average Z-Score is derived by taking the mean of the high and low Z-Scores.
-- Normalization:
---- The average Z-Score is then normalized to a range between -1 and 1. This helps in standardizing the indicator's values, making it easier to interpret.
-- Signal Line:
---- A signal line, which is the simple moving average (SMA) of the normalized Z-Score, is calculated to smooth out the data and highlight trends.
-- Color-Coding:
---- The signal line changes color based on its value: green when it is positive (indicating a potential buy signal) and red when it is negative (indicating a potential sell signal). This coloration is also used for the candle/bar coloration.
How to Use It:
-- Adding the Indicator:
---- Add the Normalized Z-Score indicator to your TradingView chart. It will appear in a separate pane below the price chart.
-- Interpreting the Histogram:
---- The histogram represents the normalized Z-Score. High positive values suggest overbought conditions, while low negative values suggest oversold conditions.
-- Using the Signal Line:
---- The signal line helps to confirm the conditions indicated by the histogram. A green signal line suggests a potential buying opportunity, while a red signal line suggests a potential selling opportunity.
-- Adjusting the Period:
---- You can adjust the period for the Z-Score calculation to suit your trading strategy. The default period is 14, but you can change this based on your preference.
Example Scenario:
-- Overbought Condition: If the histogram shows a high positive value and the signal line is green, the security may be overbought. This could indicate that it is a good time to consider selling.
-- Oversold Condition: If the histogram shows a low negative value and the signal line is red, the security may be oversold. This could indicate that it is a good time to consider buying.
By using the Normalized Z-Score indicator, traders can gain insights into price deviations and potential market reversals, aiding in making more informed trading decisions.
TanHef Ranks ScreenerTanHef Ranks Screener: A Numeric Compass to Market Tops and Bottoms
█ Simple Explanation:
The TanHef Ranks Screener illustrates the ‘TanHef Ranks’ indicator, designed to signal 'buy low and sell high' opportunities through numerical rankings. Larger numbers represent stronger signals, with negative numbers indicating potential ‘buy’ opportunities and positive numbers suggesting possible ‘sell’ moments.
█ TanHef Ranks Indicator:
View the TanHef Ranks Indicator description prior to using the screener.
█ Ticker Input Method:
Add tickers to the screener using a text area list in a CSV-styled (comma-separated values) list and/or through individual ticker inputs. The text area supports various delimiters, including commas, spaces, semicolons, apostrophes, and new lines. To ensure the expected exchange is used, the exchange prefix should be included when using a text area list.
█ Pair Configuration:
Quickly set up specific trading pairs by comparing tickers to the chart’s symbol or a specified input. This feature is useful for identifying opportunities in obscure trading pairs.
█ Total Combined Average Rank:
Compute the average rank of all tickers to highlighting overall market opportunities. When combined with the 'Pair Configuration' settings, it allows for identifying specific opportunities where one ticker may present a better trading opportunity relative to others.
█ Screener Display Settings:
Customize color-coded rank thresholds, text details, toggle visibility of numerical rankings, and other display settings. Hover over tickers for tooltips with full ticker names and rankings, ideal for small fonts or screens.
█ Alerts:
Set up alerts for individual ticker ranks or total average ranks. To avoid inconsistent or excessive alerts within a short period of time due to TradingView's alert frequency limits, it is recommended to use alerts set to occur at bar close to guarantee alerts. For immediate alerts, consider configuring them directly within the ‘TanHef Ranks’ indicator for better reliability. For the most up-to-date suggestions, hover the tooltips within the indicator’s alert settings.
█ Additional Clarity:
All the settings and functionality are described in detail within the tooltips beside each setting in the indicator’s settings. Hover over each tooltip for comprehensive explanations and guidance on how to configure and use the screener effectively.
█ How To Access:
Follow the Author's Instructions below to get access.
Global Financial IndexIntroducing the "Global Financial Index" indicator on TradingView, a meticulously crafted tool derived from extensive research aimed at providing the most comprehensive assessment of a company's financial health, profitability, and valuation. Developed with the discerning trader and investor in mind, this indicator amalgamates a diverse array of financial metrics, meticulously weighted and balanced to yield optimal results.
Financial Strength:
Financial strength is a cornerstone of a company's stability and resilience in the face of economic challenges. It encompasses various metrics that gauge the company's ability to meet its financial obligations, manage its debt, and generate sustainable profits. In our Global Financial Index indicator, the evaluation of financial strength is meticulously crafted to provide investors with a comprehensive understanding of a company's fiscal robustness. Let's delve into the key components and the rationale behind their inclusion:
1. Current Ratio:
The Current Ratio serves as a vital indicator of a company's liquidity position by comparing its current assets to its current liabilities.
A ratio greater than 1 indicates that the company possesses more short-term assets than liabilities, suggesting a healthy liquidity position and the ability to meet short-term obligations promptly.
By including the Current Ratio in our evaluation, we emphasize the importance of liquidity management in sustaining business operations and weathering financial storms.
2. Debt to Equity Ratio:
The Debt to Equity Ratio measures the proportion of a company's debt relative to its equity, reflecting its reliance on debt financing versus equity financing.
A higher ratio signifies higher financial risk due to increased debt burden, potentially leading to liquidity constraints and solvency issues.
Incorporating the Debt to Equity Ratio underscores the significance of balancing debt levels to maintain financial stability and mitigate risk exposure.
3. Interest Coverage Ratio:
The Interest Coverage Ratio assesses a company's ability to service its interest payments with its operating income.
A higher ratio indicates a healthier financial position, as it implies that the company generates sufficient earnings to cover its interest expenses comfortably.
By evaluating the Interest Coverage Ratio, we gauge the company's capacity to manage its debt obligations without compromising its profitability or sustainability.
4. Altman Z-Score:
The Altman Z-Score, developed by Edward Altman, is a composite metric that predicts the likelihood of a company facing financial distress or bankruptcy within a specific timeframe.
It considers multiple financial ratios, including liquidity, profitability, leverage, and solvency, to provide a comprehensive assessment of a company's financial health.
The Altman Z-Score categorizes companies into distinct risk groups, allowing investors to identify potential warning signs and make informed decisions regarding investment or credit exposure.
By integrating the Altman Z-Score, we offer a nuanced perspective on a company's financial viability and resilience in turbulent market conditions.
Profitability Rank:
Profitability rank is a crucial aspect of investment analysis that evaluates a company's ability to generate profits relative to its peers and industry benchmarks. It involves assessing various profitability metrics to gauge the efficiency and effectiveness of a company's operations and management. In our Global Financial Index indicator, the profitability rank segment is meticulously designed to provide investors with a comprehensive understanding of a company's profitability dynamics. Let's delve into the key components and rationale behind their inclusion:
1. Return on Equity (ROE):
Return on Equity measures a company's net income generated relative to its shareholders' equity.
A higher ROE indicates that a company is generating more profits with its shareholders' investment, reflecting efficient capital utilization and strong profitability.
By incorporating ROE, we assess management's ability to generate returns for shareholders and evaluate the overall profitability of the company's operations.
2. Gross Profit Margin:
Gross Profit Margin represents the percentage of revenue retained by a company after accounting for the cost of goods sold (COGS).
A higher gross profit margin indicates that a company is effectively managing its production costs and pricing strategies, leading to greater profitability.
By analyzing gross profit margin, we evaluate a company's pricing power, cost efficiency, and competitive positioning within its industry.
3. Operating Profit Margin:
Operating Profit Margin measures the percentage of revenue that remains after deducting operating expenses, such as salaries, rent, and utilities.
A higher operating profit margin signifies that a company is efficiently managing its operating costs and generating more profit from its core business activities.
By considering operating profit margin, we assess the underlying profitability of a company's operations and its ability to generate sustainable earnings.
4. Net Profit Margin:
Net Profit Margin measures the percentage of revenue that remains as net income after deducting all expenses, including taxes and interest.
A higher net profit margin indicates that a company is effectively managing its expenses and generating greater bottom-line profitability.
By analyzing net profit margin, we evaluate the overall profitability and financial health of a company, taking into account all expenses and income streams.
Valuation Rank:
Valuation rank is a fundamental aspect of investment analysis that assesses the attractiveness of a company's stock price relative to its intrinsic value. It involves evaluating various valuation metrics to determine whether a stock is undervalued, overvalued, or fairly valued compared to its peers and the broader market. In our Global Financial Index indicator, the valuation rank segment is meticulously designed to provide investors with a comprehensive perspective on a company's valuation dynamics. Let's explore the key components and rationale behind their inclusion:
1. Price-to-Earnings (P/E) Ratio:
The Price-to-Earnings ratio is a widely used valuation metric that compares a company's current stock price to its earnings per share (EPS).
A lower P/E ratio may indicate that the stock is undervalued relative to its earnings potential, while a higher ratio may suggest overvaluation.
By incorporating the P/E ratio, we offer insight into market sentiment and investor expectations regarding a company's future earnings growth prospects.
2. Price-to-Book (P/B) Ratio:
The Price-to-Book ratio evaluates a company's market value relative to its book value, which represents its net asset value per share.
A P/B ratio below 1 may indicate that the stock is trading at a discount to its book value, potentially signaling an undervalued opportunity.
Conversely, a P/B ratio above 1 may suggest overvaluation, as investors are paying a premium for the company's assets.
By considering the P/B ratio, we assess the market's perception of a company's tangible asset value and its implications for investment attractiveness.
3. Dividend Yield:
Dividend Yield measures the annual dividend income received from owning a stock relative to its current market price.
A higher dividend yield may indicate that the stock is undervalued or that the company is returning a significant portion of its profits to shareholders.
Conversely, a lower dividend yield may signal overvaluation or a company's focus on reinvesting profits for growth rather than distributing them as dividends.
By analyzing dividend yield, we offer insights into a company's capital allocation strategy and its implications for shareholder returns and valuation.
4. Discounted Cash Flow (DCF) Analysis:
Discounted Cash Flow analysis estimates the present value of a company's future cash flows, taking into account the time value of money.
By discounting projected cash flows back to their present value using an appropriate discount rate, DCF analysis provides a fair value estimate for the company's stock.
Comparing the calculated fair value to the current market price allows investors to assess whether the stock is undervalued, overvalued, or fairly valued.
By integrating DCF analysis, we offer a rigorous framework for valuing stocks based on their underlying cash flow generation potential.
Earnings Transparency:
Mitigating the risk of fraudulent financial reporting is crucial for investors. The indicator incorporates the Beneish M-Score, a robust model designed to detect earnings manipulation or financial irregularities. By evaluating various financial ratios and metrics, this component provides valuable insights into the integrity and transparency of a company's financial statements, aiding investors in mitigating potential risks.
Overall Score:
The pinnacle of the "Global Financial Index" is the Overall Score, a comprehensive amalgamation of financial strength, profitability, valuation, and manipulation risk, further enhanced by the inclusion of the Piotroski F-Score. This holistic score offers investors a succinct assessment of a company's overall health and investment potential, facilitating informed decision-making.
The weighting and balancing of each metric within the indicator have been meticulously calibrated to ensure accuracy and reliability. By amalgamating these diverse metrics, the "Global Financial Index" empowers traders and investors with a powerful tool for evaluating investment opportunities with confidence and precision.
This indicator is provided for informational purposes only and does not constitute financial advice, investment advice, or any other type of advice. The information provided by this indicator should not be relied upon for making investment decisions. Trading and investing in financial markets involves risk, and you should carefully consider your financial situation and consult with a qualified financial advisor before making any investment decisions. Past performance is not necessarily indicative of future results. The creator of this indicator makes no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability, or availability with respect to the indicator or the information contained herein. Any reliance you place on such information is therefore strictly at your own risk. By using this indicator, you agree to assume full responsibility for any and all gains and losses, financial, emotional, or otherwise, experienced, suffered, or incurred by you.
Alert Before Bar Closei.imgur.com
Alert Before Bar Close
==========================
Example Figure
Originality and usefulness
This indicator/alert mechanism is unique in two ways. First, it provides alerts before the close of a candlestick, allowing time-based traders to prepare early to determine if the market is about to form a setup. Second, it introduces an observation time mechanism, enabling time-based traders to observe when the market is active, thereby avoiding too many false signals during electronic trading or when trading is light.
Detail
Regarding the settings (Arrow 1). The first input is to select the candlestick period you want to observe. The second is to notify a few seconds in advance. The third input sets the observation time. For example, if you set "1,2,3,4,5," the alert mechanism will only be activated during the period from 01:00:00 to 05:59:59, consistent with the time zone you set in TradingView. Additionally, I have set it so that the alert will only trigger once per candlestick, so don't worry about repeated alerts.
The alert setup is very simple, too. Follow the steps (Arrow 2, 3) to complete the setup. I have tested several periods and successfully received alerts on both mobile and computer. If anyone encounters any issues, feel free to let me know.
Buffett Quality Score [Communication Services]Buffett Quality Score "Communication Services": Analyzing Communication Companies with Precision
The communication services sector encompasses a diverse range of companies involved in telecommunications, media, and entertainment. To assess the financial strength and performance of companies within this sector, the Buffett Quality Score employs a tailored set of financial metrics. This scoring system, inspired by the Piotroski F-Score methodology, assigns points based on specific financial criteria to provide a comprehensive quality assessment.
Scoring Methodology
The Buffett Quality Score is designed to evaluate the overall financial health and quality of companies operating within the communication services sector. Each selected financial metric is chosen for its relevance and importance in evaluating a company's performance and potential for sustainable growth. The score is computed by assigning points based on the achievement of specific thresholds for each indicator, with the total points determining the final score. This methodology ensures a nuanced analysis that captures the unique dynamics of the communication services industry.
Selected Financial Metrics and Criteria
1. Return on Invested Capital (ROIC) > 10.0%
Relevance: ROIC measures a company's efficiency in allocating capital to profitable investments. For communication companies, a ROIC above 10.0% indicates effective capital utilization, crucial for sustaining growth and innovation.
2. Return on Equity (ROE) > 15.0%
Relevance: ROE evaluates the return generated on shareholders' equity. A ROE exceeding 15.0% signifies robust profitability and effective management of shareholder funds, essential for investor confidence in communication companies.
3. Revenue One-Year Growth > 10.0%
Relevance: High revenue growth indicates strong market demand and successful business strategies. For communication services, where innovation and content delivery are paramount, growth exceeding 10.0% reflects market leadership and competitive positioning.
4. Gross Margin > 40.0%
Relevance: Gross margin measures profitability after accounting for production costs. In the communication services sector, a gross margin above 40.0% demonstrates efficient operations and high-value content offerings, critical for maintaining competitive advantage.
5. Net Margin > 10.0%
Relevance: Net margin assesses overall profitability after all expenses. A net margin exceeding 10.0% indicates effective cost management and operational efficiency, fundamental for sustained profitability in communication companies.
6. EPS One-Year Growth > 10.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share. For communication firms, where content monetization and subscription models are prevalent, EPS growth above 10.0% signals successful business expansion and value creation.
7. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score evaluates fundamental strength across various financial metrics. A score above 6.0 suggests strong financial health and operational efficiency, crucial for navigating competitive pressures in the communication services industry.
8. Price/Earnings Ratio (Forward) < 25.0
Relevance: The forward P/E ratio compares current share price to expected future earnings. A ratio below 25.0 indicates reasonable valuation relative to growth prospects, important for investors seeking value opportunities in communication stocks.
9. Current Ratio > 1.5
Relevance: The current ratio assesses short-term liquidity by comparing current assets to current liabilities. In communication companies, a ratio above 1.5 ensures financial flexibility and the ability to meet short-term obligations, vital for operational stability.
10. Debt to Equity Ratio < 1.0
Relevance: A lower debt to equity ratio indicates prudent financial management and reduced reliance on debt financing. For communication firms, maintaining a ratio below 1.0 signifies a healthy balance sheet and lower financial risk.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, suggesting higher risk.
5 Points: Represents average performance, warranting further analysis to understand underlying factors.
6-10 Points: Reflects strong financial health and quality, positioning the company favorably within the competitive communication services industry.
Conclusion
The Buffett Quality Score provides a robust framework for evaluating communication companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, investors and analysts can make informed decisions, identifying companies poised for sustainable growth and performance in the ever-evolving communication services landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Information Technology]Buffett Quality Score 'Information Technology': Assessing Tech Companies with Precision
The information technology sector is characterized by rapid innovation, high growth potential, and significant competition. To evaluate the financial health and performance of companies within this dynamic industry, the Buffett Quality Score employs a tailored set of financial metrics. This scoring system, inspired by the Piotroski F-Score methodology, assigns points based on specific financial criteria to provide a comprehensive quality assessment.
Scoring Methodology
The Buffett Quality Score is designed to assess the overall financial strength and quality of companies within the tech sector. Each selected financial metric is chosen for its relevance and importance in evaluating a company's performance and potential for sustainable growth. The score is computed by assigning points based on the achievement of specific thresholds for each indicator, with the total points determining the final score. This methodology ensures a nuanced analysis that captures the unique dynamics of the information technology industry.
Selected Financial Metrics and Criteria
1. Return on Invested Capital (ROIC) > 10.0%
Relevance: ROIC measures a company's efficiency in allocating capital to profitable investments. For tech companies, a ROIC above 10.0% indicates effective use of investment capital to generate strong returns, crucial for sustaining innovation and growth.
2. Return on Assets (ROA) > 5.0%
Relevance: ROA assesses how efficiently a company utilizes its assets to generate earnings. A ROA above 5.0% signifies that the company is effectively leveraging its assets, which is vital in the capital-intensive tech sector.
3. Revenue One-Year Growth > 10.0%
Relevance: High revenue growth indicates robust market demand and successful product or service offerings. For tech companies, where rapid scalability is common, growth exceeding 10.0% demonstrates significant market traction and expansion potential.
4. Gross Margin > 40.0%
Relevance: Gross margin reflects the proportion of revenue remaining after accounting for the cost of goods sold. In the tech sector, a gross margin above 40.0% indicates efficient production and high-value offerings, essential for maintaining competitive advantage.
5. Net Margin > 15.0%
Relevance: Net margin measures overall profitability after all expenses. A net margin above 15.0% demonstrates strong financial health and the ability to convert revenue into profit, highlighting the company's operational efficiency.
6. EPS One-Year Growth > 10.0%
Relevance: Earnings per share (EPS) growth indicates the company's ability to increase profitability per share. For tech firms, EPS growth above 10.0% signals positive earnings momentum, reflecting successful business strategies and market adoption.
7. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score assesses fundamental strength, including profitability, leverage, liquidity, and operational efficiency. A score above 6.0 suggests solid financial fundamentals and resilience in the competitive tech landscape.
8. Price/Earnings Ratio (Forward) < 25.0
Relevance: The forward P/E ratio compares current share price to expected future earnings. A ratio below 25.0 indicates reasonable valuation relative to growth expectations, important for identifying undervalued opportunities in the fast-paced tech sector.
9. Current Ratio > 1.5
Relevance: The current ratio evaluates short-term liquidity by comparing current assets to current liabilities. In the tech industry, a ratio above 1.5 ensures the company can meet its short-term obligations, essential for operational stability.
10. Debt to Equity Ratio < 1.0
Relevance: A lower debt to equity ratio signifies prudent financial management and reduced reliance on debt. For tech companies, which often require significant investment in R&D, a ratio below 1.0 highlights a strong financial structure.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, suggesting higher risk.
5 Points: Represents average performance, warranting further analysis to understand underlying factors.
6-10 Points: Reflects strong financial health and quality, positioning the company favorably within the competitive tech industry.
Conclusion
The Buffett Quality Score provides a strategic framework for evaluating tech companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, investors and analysts can make informed decisions, identifying companies poised for sustainable growth and performance in the ever-evolving tech landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Financials]Evaluating Financial Companies with the Buffett Quality Score 'Financials'
The financial sector, with its unique regulatory environment and market dynamics, requires a tailored approach to financial evaluation. The Buffett Quality Score is meticulously designed to assess the financial robustness and quality of companies within this sector. By focusing on industry-specific financial metrics, this scoring system provides valuable insights for investors and analysts navigating the complexities of the financial industry.
Scoring Methodology
Each selected financial metric contributes a point to the overall score if the specified condition is met. The combined score is a summation of points across all criteria, providing a comprehensive assessment of financial health and quality.
Selected Financial Metrics and Criteria
1. Altman Z-Score > 2.0
Relevance: The Altman Z-Score evaluates bankruptcy risk based on profitability, leverage, liquidity, solvency, and activity. In the financial sector, where market stability and solvency are critical, a score above 2.0 signifies a lower risk of financial distress.
2. Debt to Equity Ratio < 2.0
Relevance: A lower Debt to Equity Ratio signifies prudent financial management and reduced reliance on debt financing. This is particularly important for financial companies, which need to manage leverage carefully to avoid excessive risk.
3. Interest Coverage > 3.0
Relevance: The Interest Coverage Ratio measures a company's ability to meet its interest obligations from operating earnings. A ratio above 3.0 indicates that the company can comfortably cover its interest expenses, reducing the risk of default.
4. Return on Equity (ROE) > 10.0%
Relevance: ROE indicates the company's ability to generate profits from shareholder equity. An ROE above 10.0% suggests efficient use of capital and strong returns for investors, which is a key performance indicator for financial companies.
5. Return on Assets (ROA) > 1.0%
Relevance: ROA measures the company's ability to generate earnings from its assets. In the financial sector, where asset management is crucial, an ROA above 1.0% indicates effective use of assets to generate profits.
6. Net Margin > 10.0%
Relevance: Net Margin measures overall profitability after all expenses. A margin above 10.0% demonstrates strong financial performance and the ability to convert revenue into profit effectively.
7. Revenue One-Year Growth > 5.0%
Relevance: Revenue growth reflects market demand and company expansion. In the financial sector, where growth can be driven by new products and services, revenue exceeding 5.0% indicates successful market penetration and business expansion.
8. EPS One-Year Growth > 5.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share over the past year. For financial companies, growth exceeding 5.0% signals positive earnings momentum and potential market strength.
9. Price/Earnings Ratio (Forward) < 20.0
Relevance: The Forward P/E Ratio reflects investor sentiment and earnings expectations. A ratio below 20.0 suggests reasonable valuation relative to earnings projections, which is important for investors seeking value and growth opportunities in the financial sector.
10. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score assesses fundamental strength, emphasizing profitability, leverage, liquidity, and operating efficiency. For financial companies, a score above 6.0 indicates strong financial health and operational efficiency.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, warranting careful consideration and risk assessment.
5 Points: Suggests average performance based on sector-specific criteria, requiring further analysis to determine investment viability.
6-10 Points: Signifies strong financial health and quality, positioning the company favorably within the competitive financial industry.
Conclusion
The Buffett Quality Score offers a strategic framework for evaluating financial companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, stakeholders can make informed decisions and identify companies poised for sustainable growth and performance in the evolving financial landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Health Care]Evaluating Health Care Companies with the Buffett Quality Score "Health Care"
The health care sector presents unique challenges and opportunities, demanding a specialized approach to financial evaluation. The Buffett Quality Score is meticulously designed to assess the financial robustness and quality of companies within this dynamic industry. By focusing on industry-specific financial metrics, this scoring system provides valuable insights for investors and analysts navigating the complexities of the health care sector.
Scoring Methodology
Each selected financial metric contributes a point to the overall score if the specified condition is met. The combined score is a summation of points across all criteria, providing a comprehensive assessment of financial health and quality.
Selected Financial Metrics and Criteria
1. Altman Z-Score > 2.0
Relevance: The Altman Z-Score evaluates bankruptcy risk based on profitability, leverage, liquidity, solvency, and activity. In the health care sector, where regulatory changes and technological advancements can impact financial stability, a score above 2.0 signifies a lower risk of financial distress.
2. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score assesses fundamental strength, emphasizing profitability, leverage, liquidity, and operating efficiency. For health care companies, which often face regulatory challenges and R&D expenses, a score above 6.0 indicates strong financial health and operational efficiency.
3. Current Ratio > 1.5
Relevance: The Current Ratio evaluates short-term liquidity by comparing current assets to current liabilities. In the health care sector, where cash flow stability is essential for ongoing operations, a ratio above 1.5 ensures the company's ability to meet near-term obligations.
4. Debt to Equity Ratio < 1.0
Relevance: A lower Debt to Equity Ratio signifies prudent financial management and reduced reliance on debt financing. This is critical for health care companies, which require significant investments in research and development without overleveraging.
5. EBITDA Margin > 15.0%
Relevance: The EBITDA Margin measures operating profitability, excluding non-operating expenses. A margin above 15.0% indicates efficient operations and the ability to generate substantial earnings from core activities.
6. EPS One-Year Growth > 5.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share over the past year. For health care companies, which often face pricing pressures and regulatory changes, growth exceeding 5.0% signals positive earnings momentum and potential market strength.
7. Net Margin > 10.0%
Relevance: Net Margin measures overall profitability after all expenses. A margin above 10.0% demonstrates strong financial performance and the ability to convert revenue into profit effectively.
8. Return on Equity (ROE) > 15.0%
Relevance: ROE indicates the company's ability to generate profits from shareholder equity. An ROE above 15.0% suggests efficient use of capital and strong returns for investors.
9. Revenue One-Year Growth > 5.0%
Relevance: Revenue growth reflects market demand and company expansion. In the health care sector, where innovation drives growth, revenue exceeding 5.0% indicates successful market penetration and product adoption.
10. Price/Earnings Ratio (Forward) < 20.0
Relevance: The Forward P/E Ratio reflects investor sentiment and earnings expectations. A ratio below 20.0 suggests reasonable valuation relative to earnings projections, which is important for investors seeking value and growth opportunities in the health care sector.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, warranting careful consideration and risk assessment.
5 Points: Suggests average performance based on sector-specific criteria, requiring further analysis to determine investment viability.
6-10 Points: Signifies strong financial health and quality, positioning the company favorably within the competitive health care industry.
Conclusion
The Buffett Quality Score offers a strategic framework for evaluating health care companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, stakeholders can make informed decisions and identify companies poised for sustainable growth and performance in the evolving health care landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Consumer Discretionary]Evaluating Consumer Discretionary Companies with the Buffett Quality Score
The consumer discretionary sector, characterized by its sensitivity to economic cycles and consumer spending patterns, demands a robust framework for financial evaluation. The Buffett Quality Score offers a comprehensive assessment of financial health and performance specifically tailored to this dynamic industry. This scoring system combines critical financial ratios uniquely relevant to consumer discretionary companies, providing investors and analysts with a reliable tool for evaluation.
Selected Financial Metrics and Criteria
1. Altman Z-Score > 2.0
Relevance: The Altman Z-Score assesses bankruptcy risk, combining profitability, leverage, liquidity, solvency, and activity ratios. For consumer discretionary companies, which often face volatile market conditions, a score above 2.0 indicates financial stability and the ability to withstand economic downturns. This metric is particularly important in this sector due to the high variability in consumer spending.
2. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score evaluates fundamental strength based on profitability, leverage, liquidity, and operating efficiency. In the consumer discretionary sector, where rapid changes in consumer preferences can impact performance, a score above 6.0 highlights strong fundamental performance and resilience. This score is crucial for identifying companies with robust financial foundations in a highly competitive environment.
3. Asset Turnover > 1.0
Relevance: Asset Turnover measures the efficiency of asset use in generating sales. For consumer discretionary companies, a ratio above 1.0 signifies effective utilization of assets to drive revenue growth. Given the sector's reliance on high sales volumes and rapid inventory turnover, this metric is key to assessing operational efficiency.
4. Current Ratio > 1.5
Relevance: The Current Ratio assesses liquidity by comparing current assets to current liabilities. A ratio above 1.5 ensures that consumer discretionary companies can meet short-term obligations. This liquidity is essential for maintaining operational stability and flexibility to adapt to market changes, especially during economic fluctuations.
5. Debt to Equity Ratio < 1.0
Relevance: A lower Debt to Equity Ratio indicates prudent financial management and reduced reliance on debt. This is particularly important for consumer discretionary companies, which need to maintain financial flexibility to invest in new trends and innovations without overleveraging. Lower debt levels also reduce risk during economic downturns.
6. EBITDA Margin > 15.0%
Relevance: The EBITDA Margin measures operating profitability. A margin above 15.0% indicates efficient operations and the ability to generate sufficient earnings before interest, taxes, depreciation, and amortization. This is crucial for sustaining profitability in a competitive and fluctuating market, ensuring the company can reinvest in growth and innovation.
7. EPS One-Year Growth > 5.0%
Relevance: EPS growth reflects the company’s ability to increase earnings per share over the past year. For consumer discretionary companies, growth exceeding 5.0% signals positive earnings momentum, which is vital for investor confidence and the ability to fund future growth initiatives. This metric highlights companies that are successfully increasing profitability.
8. Gross Margin > 25.0%
Relevance: Gross Margin represents the profitability of sales after production costs. A margin exceeding 25.0% indicates strong pricing power and effective cost management, crucial for maintaining profitability while adapting to changing consumer demands. High gross margins are indicative of a company’s ability to control costs and price products competitively.
9. Net Margin > 10.0%
Relevance: Net Margin measures overall profitability after all expenses. A margin above 10.0% highlights the company’s ability to maintain strong profit levels, ensuring financial health and stability. This is essential for sustaining operations and investing in new opportunities, reflecting the company's efficiency in converting revenue into actual profit.
10.Return on Equity (ROE) > 15.0%
Relevance: ROE indicates how effectively a company uses equity to generate profits. An ROE above 15.0% signifies strong shareholder value creation. This metric is key for evaluating long-term performance in the consumer discretionary sector, where investor returns are closely tied to the company’s ability to innovate and grow. High ROE demonstrates effective management and profitable use of equity capital.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, warranting further investigation and risk assessment.
5 Points: Suggests average performance based on sector-specific criteria, indicating a need for cautious optimism.
6-10 Points: Signifies strong financial health and quality, meeting or exceeding most performance thresholds, making the company a potentially attractive investment.
Conclusion
The Buffett Quality Score provides a structured approach to evaluating financial health and performance. By focusing on these essential financial metrics, stakeholders can make informed decisions, identifying companies that are well-positioned to thrive in the competitive and economically sensitive consumer discretionary sector.
Disclaimer: The Buffett Quality Score serves as a tool for financial evaluation and analysis. It is not a substitute for professional financial advice or investment recommendations. Investors should conduct thorough research and seek personalized guidance based on individual circumstances.
Buffett Quality Score [Consumer Staples]Evaluating Consumer Staples Companies with the Buffett Quality Score
In the world of consumer staples, where stability and consistent performance are paramount, the Buffett Quality Score provides a comprehensive framework for assessing financial health and quality. This specialized scoring system is tailored to capture key aspects that are particularly relevant in the consumer staples sector, influencing investment decisions and strategic evaluations.
Selected Financial Metrics and Criteria
1. Gross Margin > 25.0%
Relevance: Consumer staples companies often operate in competitive markets. A Gross Margin exceeding 25.0% signifies efficient cost management and pricing strategies, critical for sustainable profitability amidst market pressures.
2. Net Margin > 5.0%
Relevance: Net Margin > 5.0% reflects the ability of consumer staples companies to generate bottom-line profits after accounting for all expenses, indicating operational efficiency and profitability.
3. Return on Assets (ROA) > 5.0%
Relevance: ROA > 5.0% measures how effectively consumer staples companies utilize their assets to generate earnings, reflecting operational efficiency and resource utilization.
4. Return on Equity (ROE) > 10.0%
Relevance: ROE > 10.0% indicates efficient capital deployment and shareholder value creation, fundamental for sustaining growth and competitiveness in the consumer staples industry.
5. Current Ratio > 1.5
Relevance: Consumer staples companies require strong liquidity to manage inventory and operational expenses. A Current Ratio > 1.5 ensures sufficient short-term liquidity to support ongoing operations.
6. Debt to Equity Ratio < 1.0
Relevance: With the need for stable finances, a Debt to Equity Ratio < 1.0 reflects prudent financial management and reduced reliance on debt financing, essential for long-term sustainability.
7. Interest Coverage Ratio > 3.0
Relevance: Consumer staples companies with an Interest Coverage Ratio > 3.0 demonstrate their ability to comfortably meet interest obligations, safeguarding against financial risks.
8. EPS One-Year Growth > 5.0%
Relevance: EPS growth > 5.0% indicates positive momentum and adaptability to changing market dynamics, crucial for consumer staples companies navigating evolving consumer preferences.
9. Revenue One-Year Growth > 5.0%
Relevance: Consistent revenue growth > 5.0% reflects market adaptability and consumer demand, highlighting operational resilience and strategic positioning.
10. EV/EBITDA Ratio < 15.0
Relevance: The EV/EBITDA Ratio < 15.0 reflects favorable valuation and earnings potential relative to enterprise value, offering insights into investment attractiveness and market competitiveness.
Interpreting the Buffett Quality Score
0-4 Points: Signals potential weaknesses across critical financial areas, warranting deeper analysis and risk assessment.
5 Points: Indicates average performance based on sector-specific criteria.
6-10 Points: Highlights strong financial health and quality, aligning with the stability and performance expectations of the consumer staples industry.
Conclusion
The Buffett Quality Score for consumer staples provides investors and analysts with a structured approach to evaluate and compare companies within this sector. By focusing on these essential financial metrics, stakeholders can make informed decisions and identify opportunities aligned with the stability and growth potential of consumer staples businesses.
Disclaimer: The Buffett Quality Score serves as a tool for financial evaluation and analysis. It is not a substitute for professional financial advice or investment recommendations. Investors should conduct thorough research and seek personalized guidance based on individual circumstances.
Buffett Quality Score [Materials]The Buffett Quality Score tailored for the Materials sector aims to assess the financial strength and quality of companies within this industry. Each selected financial ratio is strategically chosen to align with the unique characteristics and challenges prevalent in the Materials sector.
Selected Financial Ratios and Criteria:
1. Asset Turnover > 0.8
Relevance: In the Materials sector, efficient asset utilization is crucial for productivity and profitability. A high Asset Turnover (>0.8) indicates effective management of resources and operational efficiency.
2. Current Ratio > 1.5
Relevance: Materials companies often require adequate liquidity to manage inventory and operational expenses. A Current Ratio > 1.5 ensures sufficient short-term liquidity to support ongoing operations and investments.
3. Debt to Equity Ratio < 1.0
Relevance: Given the capital-intensive nature of Materials projects, maintaining a low Debt to Equity Ratio (<1.0) signifies prudent financial management with reduced reliance on debt financing, essential for stability amid industry fluctuations.
4. Gross Margin > 25.0%
Relevance: Materials companies deal with varying production costs and market pricing. A Gross Margin exceeding 25.0% reflects effective cost management and pricing strategies, critical for profitability in a competitive market.
5. EBITDA Margin > 15.0%
Relevance: Strong EBITDA margins (>15.0%) indicate robust operational performance and profitability, essential for sustaining growth and weathering industry-specific challenges.
6. Interest Coverage Ratio > 3.0
Relevance: The Materials sector is subject to market cyclicality and commodity price fluctuations. An Interest Coverage Ratio > 3.0 ensures the company's ability to service debt obligations, safeguarding against financial risks.
7. EPS One-Year Growth > 5.0%
Relevance: EPS growth > 5.0% demonstrates the company's ability to generate sustainable earnings amidst industry dynamics, reflecting positive investor sentiment and potential future prospects.
8. Revenue One-Year Growth > 5.0%
Relevance: Materials companies require consistent revenue growth (>5.0%) to support expansion initiatives and capitalize on market opportunities, indicative of operational resilience and adaptability.
9. Return on Assets (ROA) > 5.0%
Relevance: ROA > 5.0% showcases efficient asset utilization and profitability, essential metrics for evaluating performance and competitive positioning within the Materials industry.
10. Return on Equity (ROE) > 10.0%
Relevance: ROE > 10.0% reflects effective capital deployment and shareholder value creation, crucial for sustaining long-term growth and investor confidence in Materials sector investments.
Score Interpretation:
0-4 Points: Signals potential weaknesses across critical financial aspects, requiring in-depth analysis and risk assessment.
5 Points: Represents average performance based on sector-specific criteria.
6-10 Points: Indicates strong financial health and quality, demonstrating robustness and resilience within the demanding Materials industry landscape.
Development and Context:
The selection and weighting of these specific financial metrics underwent meticulous research and consideration to ensure relevance and applicability within the Materials sector. This scoring framework aims to provide actionable insights for stakeholders navigating investment decisions and evaluating company performance in the Materials industry.
Disclaimer: This information serves as an educational resource on financial evaluation methodology tailored for the Materials sector. It does not constitute financial advice or a guarantee of future performance. Consult qualified professionals for personalized financial guidance based on your specific circumstances and investment objectives.
Buffett Quality Score [Energy]The Buffett Quality Score for the Energy sector is designed to meticulously evaluate the financial health and quality of companies operating within this dynamic industry. Each selected financial ratio is specifically chosen based on its relevance and significance within the Energy sector context.
Selected Financial Ratios and Criteria:
1. Return on Assets (ROA) > 5%
Relevance: In the Energy sector, where asset-intensive operations are common (e.g., oil exploration and infrastructure), a robust ROA above 5% indicates efficient asset utilization, crucial for profitability.
2. Debt to Equity Ratio < 1.0
Relevance: Energy companies often require substantial capital for projects and operations. A low Debt to Equity Ratio (<1.0) suggests prudent financial management with less reliance on debt financing, vital in a capital-intensive industry vulnerable to economic cycles.
3.Interest Coverage Ratio > 3.0
Relevance: Given the capital-intensive nature of Energy projects, maintaining a healthy Interest Coverage Ratio (>3.0) ensures the company's ability to service debt obligations, particularly important during periods of economic volatility affecting commodity prices.
4. Gross Margin % > 25%
Relevance: Energy companies face varying production costs and pricing pressures. A Gross Margin exceeding 25% reflects efficient cost management and pricing power, critical in mitigating volatility in commodity prices.
5. Current Ratio > 1.5
Relevance: Energy projects often require substantial working capital. A Current Ratio > 1.5 indicates sufficient liquidity to cover short-term obligations, essential for operational continuity in an industry susceptible to market fluctuations.
6. EBITDA Margin % > 15%
Relevance: Energy companies must manage operating costs effectively. An EBITDA Margin > 15% signifies strong operational efficiency and profitability, crucial for sustaining growth amidst market uncertainties.
7. Altman Z-Score > 2.0
Relevance: The Energy sector experiences cyclical downturns and price volatility. An Altman Z-Score > 2.0 indicates financial stability and resilience, vital for weathering industry-specific challenges.
8. EPS Basic One-Year Growth % > 5%
Relevance: Energy companies' earnings growth is closely tied to commodity prices and market demand. EPS growth > 5% indicates positive momentum and adaptability to industry shifts.
9. Revenue One-Year Growth % > 5%
Relevance: Energy companies operate in a dynamic market influenced by geopolitical factors and global demand. Revenue growth > 5% reflects market adaptability and expansion potential.
10. Piotroski F-Score > 6
Relevance: Fundamental strength is paramount in the Energy sector, characterized by capital-intensive projects. A Piotroski F-Score > 6 highlights solid operational and financial performance, critical for long-term sustainability.
Score Interpretation:
0-4 Points: Indicates potential weaknesses across critical financial areas, necessitating closer scrutiny.
5 Points: Suggests average performance based on industry-specific criteria.
6-10 Points: Signifies strong overall financial health and quality, aligning with the demanding requirements of the Energy sector.
Development and Context:
The selection and weighting of these specific financial metrics underwent rigorous industry-specific research to ensure their applicability and reliability within the unique operational environment of the Energy sector. This scoring framework aims to provide actionable insights for stakeholders navigating the complexities of Energy industry investments and operations.
Disclaimer: This information serves as an educational resource on financial evaluation methodology tailored for the Energy sector. It does not constitute financial advice or a guarantee of future performance. Consult qualified professionals for personalized financial guidance based on your specific circumstances and investment objectives.
Buffett Quality Score [Industry]The Buffett Quality Score is a composite indicator developed to assess the financial health and quality of companies operating within the Industrial sector. It combines a carefully selected set of financial ratios, each weighted with specific thresholds, to provide a comprehensive evaluation of company performance.
Selected Financial Ratios and Criteria:
1. Return on Assets (ROA) > 5%
ROA measures a company's profitability by evaluating how effectively it utilizes its assets. An ROA exceeding 5% earns 1 point.
2. Debt to Equity Ratio < 1.0
The Debt to Equity Ratio reflects a company's leverage. A ratio below 1.0 earns 1 point, indicating lower reliance on debt financing.
3. Interest Coverage Ratio > 3.0
The Interest Coverage Ratio assesses a company's ability to meet interest payments. A ratio above 3.0 earns 1 point, indicating strong financial health.
4. Gross Margin % > 25%
Gross Margin represents the profitability of sales after deducting production costs. A margin exceeding 25% earns 1 point, indicating better pricing power.
5. Current Ratio > 1.5
The Current Ratio evaluates a company's liquidity by comparing current assets to current liabilities. A ratio above 1.5 earns 1 point, indicating sufficient short-term liquidity.
6. EBITDA Margin % > 15%
EBITDA Margin measures operating profitability, excluding non-operating expenses. A margin exceeding 15% earns 1 point, indicating efficient operations.
7. Altman Z-Score > 2.0
The Altman Z-Score predicts bankruptcy risk based on profitability, leverage, liquidity, solvency, and activity. A score above 2.0 earns 1 point, indicating financial stability.
8. EPS Basic One-Year Growth % > 5%
EPS One-Year Growth reflects the percentage increase in earnings per share over the past year. Growth exceeding 5% earns 1 point, indicating positive earnings momentum.
9. Revenue One-Year Growth % > 5%
Revenue One-Year Growth represents the percentage increase in revenue over the past year. Growth exceeding 5% earns 1 point, indicating healthy sales growth.
10. Piotroski F-Score > 6
The Piotroski F-Score evaluates fundamental strength based on profitability, leverage, liquidity, and operating efficiency. A score above 6 earns 1 point, indicating strong fundamental performance.
Score Calculation Process:
Each company is evaluated against these criteria.
For every criterion met or exceeded, 1 point is assigned.
The total points accumulated determine the Buffett Quality Score out of a maximum of 10.
Interpretation of Scores:
0-4 Points: Indicates potential weaknesses across multiple financial areas.
5 Points: Suggests average performance based on the selected criteria.
6-10 Points: Signifies strong overall financial health and quality, meeting or exceeding most of the performance thresholds.
Research and Development:
The selection and weighting of these specific financial ratios underwent extensive research to ensure relevance and applicability to the Industrial sector. This scoring methodology aims to provide valuable insights for investors and analysts seeking to evaluate company quality and financial robustness within the Industrial landscape.
The information provided about the Buffett Quality Score is for educational purposes only. This document serves as an illustrative example of financial evaluation methodology and should not be construed as financial advice, investment recommendation, or a guarantee of future performance. Actual results may vary based on individual circumstances and specific factors affecting each company. We recommend consulting qualified professionals for personalized financial advice tailored to your individual situation.
Seasonality Widget [LuxAlgo]The Seasonality Widget tool allows users to easily visualize seasonal trends from various data sources.
Users can select different levels of granularity as well as different statistics to express seasonal trends.
🔶 USAGE
Seasonality allows us to observe general trends occurring at regular intervals. These intervals can be user-selected from the granularity setting and determine how the data is grouped, these include:
Hour
Day Of Week
Day Of Month
Month
Day Of Year
The above seasonal chart shows the BTCUSD seasonal price change for every hour of the day, that is the average price change taken for every specific hour. This allows us to obtain an estimate of the expected price move at specific hours of the day.
Users can select when data should start being collected using the "From Date" setting, any data before the selected date will not be included in the calculation of the Seasonality Widget.
🔹 Data To Analyze
The Seasonality Widget can return the seasonality for the following data:
Price Change
Closing price minus the previous closing price.
Price Change (%)
Closing price minus the previous closing price, divided by the
previous closing price, then multiplied by 100.
Price Change (Sign)
Sign of the price change (-1 for negative change, 1 for positive change), normalized in a range (0, 100). Values above 50 suggest more positive changes on average.
Range
High price minus low price.
Price - SMA
Price minus its simple moving average. Users can select the SMA period.
Volume
Amount of contracts traded. Allow users to see which periods are generally the most /least liquid.
Volume - SMA
Volume minus its simple moving average. Users can select the SMA period.
🔹 Filter
In addition to the "From Date" threshold users can exclude data from specific periods of time, potentially removing outliers in the final results.
The period type can be specified in the "Filter Granularity" setting. The exact time to exclude can then be specified in the "Numerical Filter Input" setting, multiple values are supported and should be comma separated.
For example, if we want to exclude the entire 2008 period we can simply select "Year" as filter granularity, then input 2008 in the "Numerical Filter Input" setting.
Do note that "Sunday" uses the value 1 as a day of the week.
🔶 DETAILS
🔹 Supported Statistics
Users can apply different statistics to the grouped data to process. These include:
Mean
Median
Max
Min
Max-Min Average
Using the median allows for obtaining a measure more robust to outliers and potentially more representative of the actual central tendency of the data.
Max and Min do not express a general tendency but allow obtaining information on the highest/lowest value of the analyzed data for specific periods.
🔶 SETTINGS
Granularity: Periods used to group data.
From Data: Starting point where data starts being collected
🔹 Data
Analyze: Specific data to be processed by the seasonality widget.
SMA Length: Period of the simple moving average used for "Price - SMA" and "Volume - SMA" options in "Analyze".
Statistic: Statistic applied to the grouped data.
🔹 Filter
Filter Granularity: Period type to exclude in the processed data.
Numerical Filter Input: Determines which of the selected hour/day of week/day of month/month/year to exclude depending on the selected Filter Granularity. Only numerical inputs can be provided. Multiple values are supported and must be comma-separated.
Simple Volatility MomentumOverview:
The Simple Volatility Momentum indicator calculates the mean and standard deviation of the changes of price (returns) using various types of moving averages (Incremental, Rolling, and Exponential). With quantifying the dispersion of price data around the mean, statistical insights are provided on the volatility and the movements of price and returns. The indicator also ranks the mean absolute value of the changes of price over a specified time period which helps you assess the strength of the "trend" and "momentum" regardless of the direction of returns.
Simple Volatility Momentum
This indicator can be used for mean reversion strategies and "momentum" or trend based strategies.
The indicator calculates the average return as the momentum metric and then gets the moving average of the average return and standard deviations from average return average. On the options you can determine if you want to use 1 or 2 standard deviation bands or have both of them enabled.
Settings:
Source: By default it's at close.
M Length: This is the length of the "momentum".
Rank Length: This is the length of the rank calculation of absolute value of the average return
MA Type: This is the different type of calculations for the mean and standard deviation. By default its at incremental.
Smoothing factor: (Only used if you choose the exponential MA type.)
The absolute value of the average return helps you see the strength of the "momentum" and trend. If there is a low ranking of the absolute value of the average return then you can eventually expect it to increase which means that the average return is trending, leading to trending price moves. If the Mean ABS rank value is at or near the maximum value 100 and the average return is at -2 standard deviation from the mean, you can see it as the negative momentum or trend being "finished". Similarly, if the Mean ABS value is near or at the maximum value 100 and the average return is at +2 standard deviation from the mean, you can view the uptrend, as "finished" and the Mean ABS rank can't really go higher than 100.
Moving Average Calculations type:
Incremental: Incremental moving averages use an incremental approach to update the moving average by adding the newest data point and subtracting the oldest one.
Exponential: The exponential moving average gives more weight to recent data points while still considering older ones. This is achieved by applying a smooth factor to the previous EMA value and the current data point. EMA's react more quickly to recent changes in the data compared to simple moving averages, making them useful for short term trends and momentum in financial markets.
Rolling: The moving average is calculated by taking the average of a fixed number of data points within a defined window. As new data becomes available, the window moves forward and the average is recalculated. Rolling Moving Averages are useful for smoothing out short-fluctuations and identifying trends over time.
Important thing to note about indicators involving bands and "momentum" or "trend" or prices:
For the explanation we will assume that stock returns follow a normal distribution and price follows a log normal distribution. Please note that in the live market this assumption isn't always true. Many people incorrectly use standard deviations on prices and trade them as mean reversion strategies or overbought or oversold levels which is not what standard deviations are meant for. Assuming you have applied the log transformation on the standard deviation bands (if your input is raw price then you should use a log transformation to remove the skewness of price), and you have a range of 2 standard deviations from the mean, under the empirical rule with enough occurrences 95% of the values will be within the 2 standard deviation range. This doesn't mean that if price falls to the bottom of the 2 standard deviation bound, there is a 95% chance it will revert back to mean, this is incorrect and not how standard deviations or mean reversion works.
"MOMENTUM"
In finance "momentum" refers to the rate of change of a time series data point. It shows the persistence or tendency for a data series to continue moving in its current direction. In finance, "momentum" based strategies capitalize on the observed tendency of assets that have performed well (or poorly) in the recent past to continue performing well (or poorly) in the near future. This persistence is often observed in various financial instruments including stocks, currencies and commodities.
"Momentum" is commonly calculated with the average return, and relies on the assumption that assets with positive "momentum" or a positive average return will likely continue to perform well in the short to medium term, while assets with a negative average return are expected to continue underperforming. This average return or expected value is derived from historical observations and statistical analysis of previous price movements. However, real markets are subject to levels of efficiencies, market fluctuations, randomness, and may not always produce consistent returns over time involving momentum based strategies.
Mean Reversion:
In finance, the average return is an important parameter in mean reversion strategies. Using statistical methodologies, mean reversion strategies aim to exploit the deviations from the historical average return by identifying instances where current prices and their changes diverge from their expected levels based on past performance. This approach involves statistical analysis and predictive modelling techniques to check where and when the average rate of change is likely to revert towards the mean. It's important to know that mean reversion is a temporary state and will not always be present in a specific timeseries.
Using the average return over price offers several advantages in finance and trading since it is less sensitive to extreme price movements or outliers compared to raw price data. Price itself contains a distribution that is usually positively-skewed and has no upper bound. Mean reversion typically occurs in distributions where extreme values are followed by a tendency for the variable to return towards its mean over time, however the probability distribution of price has no tendency for values to revert towards any specific level. Instead, values may continue to increase without a bound. Returns themself contain more stationary behavior than price levels. Mean reversion strategies rely on the assumption that deviations from the mean will eventually revert back to the mean. Returns, being more likely to exhibit stationary, are better suited for mean reversion based strategies.
The distribution of returns are often more symmetrically distributed around their mean compared to price distributions. This symmetry makes it easier to identify deviations from the mean and assess the likelihood of mean reversion occurrence. Returns are also less sensitive to trends and long-term price movements compared to price levels. Mean reversion strategies aim to exploit deviations from mean, which can be obscured when analyzing raw price data since raw price is almost always trending. Returns can filter out the trend component of price movements, making it easier to identify opportunities.
Stationary Process: Implication that properties like mean and variance remain relatively constant over time.
Profitability Power RatioProfitability Power Ratio
The Profitability Power Ratio is a financial metric designed to assess the efficiency of a company's operations by evaluating the relationship between its Enterprise Value (EV) and Return on Equity (ROE). This ratio provides insights into how effectively a company generates profits relative to its equity and overall valuation.
Qualities and Interpretations:
1. Efficiency Benchmark: The Profitability Power Ratio serves as a benchmark for evaluating how efficiently a company utilizes its equity capital to generate profits. A higher ratio indicates that the company is generating significant profits relative to its valuation, reflecting efficient use of invested capital.
2. Financial Health Indicator: This ratio can be used as an indicator of financial health. A consistently high or improving ratio over time suggests strong operational efficiency and sustainable profitability.
3. Investment Considerations: Investors can use this ratio to assess the attractiveness of an investment opportunity. A high ratio may signal potential for good returns, but it's important to consider the underlying reasons for the ratio's level to avoid misinterpretation.
4. Risk Evaluation: An excessively high Profitability Power Ratio could also signal elevated risk. It may indicate aggressive financial leveraging or unsustainable growth expectations, which could pose risks during economic downturns or market fluctuations.
Interpreting the Ratio:
1. Higher Ratio: A higher Profitability Power Ratio typically signifies efficient capital utilization and strong profitability relative to the company's valuation.
2. Lower Ratio: A lower ratio may suggest inefficiencies in capital allocation or lower profitability relative to enterprise value.
3. Benchmarking: Compare the company's ratio with industry peers and historical performance to gain deeper insights into its financial standing and operational efficiency.
Using the Indicator:
The Profitability Power Ratio is plotted on a chart to visualize trends and fluctuations over time. Users can customize the color of the plot to emphasize this metric and integrate it into their financial analysis toolkit for comprehensive decision-making.
Disclaimer: The Profitability Power Ratio is a financial metric designed for informational purposes only and should not be considered as financial or investment advice. Users should conduct thorough research and analysis before making any investment decisions based on this indicator. Past performance is not indicative of future results. All investments involve risks, and users are encouraged to consult with a qualified financial advisor or professional before making investment decisions.
Dividend-to-ROE RatioDividend-to-ROE Ratio Indicator
The Dividend-to-ROE Ratio indicator offers valuable insights into a company's dividend distribution relative to its profitability, specifically comparing the Dividend Payout Ratio (proportion of earnings as dividends) to the Return on Equity (ROE), a measure of profitability from shareholder equity.
Interpretation:
1. Higher Ratio: A higher Dividend-to-ROE Ratio suggests a stable dividend policy, where a significant portion of earnings is returned to shareholders. This can indicate consistent dividend payments, often appealing to income-seeking investors.
2. Lower Ratio: Conversely, a lower ratio implies that the company retains more earnings for growth, potentially signaling a focus on reinvestment for future expansion rather than immediate dividend payouts.
3. Excessively High Ratio: An exceptionally high ratio may raise concerns. While it could reflect a generous dividend policy, excessively high ratios might indicate that a company is distributing more earnings than it can sustainably afford. This could potentially hinder the company's ability to reinvest in its operations, research, or navigate economic downturns effectively.
Utility and Applications:
The Dividend-to-ROE Ratio can be particularly useful in the following scenarios:
1. Income-Oriented Investors: For investors seeking consistent dividend income, a higher ratio signifies a company's commitment to distributing profits to shareholders, potentially aligning with income-oriented investment strategies.
2. Financial Health Assessment: Analysts and stakeholders can use this ratio to gauge a company's financial health and dividend sustainability. It provides insights into management's capital allocation decisions and strategic focus.
3. Comparative Analysis: When comparing companies within the same industry, this ratio helps in benchmarking dividend policies and identifying outliers with unusually high or low ratios.
Considerations:
1. Contextual Analysis: Interpretation should be contextualized within industry standards and the company's financial history. Comparing the ratio with peers in the same sector can provide meaningful insights.
2. Financial Health: It's crucial to evaluate this indicator alongside other financial metrics (like cash flow, debt levels, and profit margins) to grasp the company's overall financial health and sustainability of its dividend policy.
Disclaimer: This indicator is for informational purposes only and does not constitute financial advice. Investors should conduct thorough research and consult with financial professionals before making investment decisions based on this ratio.
Fourier Adjusted Average True Range [BackQuant]Fourier Adjusted Average True Range
1. Conceptual Foundation and Innovation
The FA-ATR leverages the principles of Fourier analysis to dissect market prices into their constituent cyclical components. By applying Fourier Transform to the price data, the FA-ATR captures the dominant cycles and trends which are often obscured in noisy market data. This integration allows the FA-ATR to adapt its readings based on underlying market dynamics, offering a refined view of volatility that is sensitive to both market direction and momentum.
2. Technical Composition and Calculation
The core of the FA-ATR involves calculating the traditional ATR, which measures market volatility by decomposing the entire range of price movements. The FA-ATR extends this by incorporating a Fourier Transform of price data to assess cyclical patterns over a user-defined period 'N'. This process synthesizes both the magnitude of price changes and their rhythmic occurrences, resulting in a more comprehensive volatility indicator.
Fourier Transform Application: The Fourier series is calculated using price data to identify the fundamental frequency of market movements. This frequency helps in adjusting the ATR to reflect more accurately the current market conditions.
Dynamic Adjustment: The ATR is then adjusted by the magnitude of the dominant cycle from the Fourier analysis, enhancing or reducing the ATR value based on the intensity and phase of market cycles.
3. Features and User Inputs
Customizability: Traders can modify the Fourier period, ATR period, and the multiplication factor to suit different trading styles and market environments.
Visualization : The FA-ATR can be plotted directly on the chart, providing a visual representation of volatility. Additionally, the option to paint candles according to the trend direction enhances the usability and interpretative ease of the indicator.
Confluence with Moving Averages: Optionally, a moving average of the FA-ATR can be displayed, serving as a confluence factor for confirming trends or potential reversals.
4. Practical Applications
The FA-ATR is particularly useful in markets characterized by periodic fluctuations or those that exhibit strong cyclical trends. Traders can utilize this indicator to:
Adjust Stop-Loss Orders: More accurately set stop-loss orders based on a volatility measure that accounts for cyclical market changes.
Trend Confirmation: Use the FA-ATR to confirm trend strength and sustainability, helping to avoid false signals often encountered in volatile markets.
Strategic Entry and Exit: The indicator's responsiveness to changing market dynamics makes it an excellent tool for planning entries and exits in a trend-following or a breakout trading strategy.
5. Advantages and Strategic Value
By integrating Fourier analysis, the FA-ATR provides a volatility measure that is both adaptive and anticipatory, giving traders a forward-looking tool that adjusts to changes before they become apparent through traditional indicators. This anticipatory feature makes it an invaluable asset for traders looking to gain an edge in fast-paced and rapidly changing market conditions.
6. Summary and Usage Tips
The Fourier Adjusted Average True Range is a cutting-edge development in technical analysis, offering traders an enhanced tool for assessing market volatility with increased accuracy and responsiveness. Its ability to adapt to the market's cyclical nature makes it particularly useful for those trading in highly volatile or cyclically influenced markets.
Traders are encouraged to integrate the FA-ATR into their trading systems as a supplementary tool to improve risk management and decision-making accuracy, thereby potentially increasing the effectiveness of their trading strategies.
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