FOREX MASTER PATTERN Value Lines by nnamThe Forex Master Pattern is form of technical analysis that provides a framework for spotting hidden price patterns that reveal the true movement of the market. The Forex Master Pattern Value Lines Indicator helps to identify this Phase 1 contraction of the Forex Master Pattern cycle.
HOW THIS INDICATOR WORKS
This indicator looks for a sustained contraction in price initially indicated by TWO contraction bars in a row, thus detecting a contraction point and a potential new master pattern origin point.
Once a contraction point is detected, a blue box will appear on the chart with a thick solid blue line projecting from its center. These are potential "Points of Origin" and "Value Lines" that institutional traders use to balance their books.
As shown above, when price begins to move (detected by engulfing and/or expansion candles), an Arrow is plotted to the chart identifying a possible expansion.
As shown above, previous Value Lines typically serve as future support / resistance points, however, due to the unique location of these lines, they are not typically identified as support or resistance levels on standard S/R indicators.
Color Coded Candles assist the user in quickly identifying contraction and expansion areas as well as trends away from the value-line. The expansion candles, Up/Down candles, and contraction BARS are all inspired by the STRAT (Rob Smith) and are specifically incorporated into this indicator to assist the user in finding potential reversals during the expansion phase. This helps to avoid the whiplash typically associated with the first phase of Forex Master Pattern.
USER DEFINED SETTINGS
- Line Settings Section -
#Max Lines to Show
This limits or extends the total number of lines shown on the chart. The Default is 12 (minimum is 1, maximum is 499).
#Show Lines on Chart
This setting turns all lines ON or OFF on the chart
#Show Value-Lines on Chart
This setting turns the Value Lines ON or OFF on the chart
#Set Value-Line Width
This setting sets the width of the value-line displayed on the chart
#Only show last value-line on the chart
This setting removes all but the most recent value-line from the chart
- Box Settings Section -
#Show Last Box Only
This setting turns OFF all previous boxes and only shows the most recent contraction box on the chart
- Expansion Area Settings Section -
#Show Expansion Area
This setting turns ON or OFF the expansion area fill
#Show Expansion Guidelines on Chart
This setting turns ON or OFF the guidelines that show the current direction of the price via an extended line.
- Candle Colors Section -
#Color Code the Candles
This setting turns on Color Coding for the Candles which changes the colors of each candle type:
1. Contraction Candle
2. Expansion Candle
3. Up Candle
4. Down Candle
5. Engulfing Candles (engulfing candles override other candle settings if turned ON)
- Engulfing Patterns Section -
#Show Engulfing Patterns
This setting turns ON or OFF engulfing candle plots globally
#Show Bullish Engulfing Candles
This setting allows the user to turn Bullish Engulfing signals ON or OFF
#Show Bearish Engulfing Candles
This setting allows the user to turn Bearish Engulfing signals ON or OFF
I hope you enjoy this indicator and that it provides some value. Please reach out to me with any suggestions or need training on the indicator.
Nilai
Outliers Detector with N-Sigma Confidence Intervals (TG fork)Display outliers in either value change, volume or volume change that significantly deviate from the past.
This uses the standard deviation calculation and the n-sigmas statistical rule of significance, with 2-sigma (a value of 2) signifying that the observed value is stronger than 95% of past values, and 3-sigma 98.5% of past values, and so on for higher sigma values.
Outliers in price action or in volume can indicate a strong support for the move, and hence potentially more moves in the same direction in the future. Inversely, an insignificant move is less likely to be supported. And of course the stronger, the more support.
This indicator also doubles as a standard volume indicator if volume is selected as the source, but with the option of highlighting outliers.
Bars below significance can be uncolored (gray) to unclutter the visuals.
Differently to almost all other similar indicators, the background highlighting is dynamical, so that all values will be highlighted differently, not just 2-sigma or 3-sigma, but also 4-sigma, 5-sigma, etc, with a different value of transparency.
The dynamical transparency value can be calculated in two ways: either statically proportionally to the n-sigma but capped at 10-sigma, or either as a ratio relative to the highest observed sigma value over the defined lookback period (default: 300).
If you like this indicator, which is an extension of previously published indicators, please give some love to the original authors:
* tvjvzl :
* vnhilton :
This extension, authored by Tartigradia, extends tvjvzl's indi, implements vnhilton's idea of highlighting the background, and go further by adding dynamical background highlighting for any value of sigma, add support for volume and volume change (VolumeDiff) as inputs, add option to uncolor insignificant bars, allow plotting in both directions and more.
Rule Of 20 - Fair Value Estimation by Inflation & Earnings (TG)The Rule Of 20 is a heuristic calculation to find the fair value of an asset or market given its earnings and current inflation.
Its calculation is straightforward: the fair multiple of the price or price-to-earnings ratio of a stock should be 20 minus the rate of inflation.
In math terms: fair_price-to-earnings_ratio = (20 - inflation) ; fair_value = current_price * fair_price-to-earnings_ratio / real_price-to-earnings_ratio
For example, if a stock or index was trading on 11 times earnings and inflation was 2%, then the theory would be that the fair price-to-earnings ratio would be 20-2 = 18, which is much higher than the real price-to-earnings ratio of 11, and hence the asset would be undervalued.
Conversely, a market or company that was trading on 18 times price-to-earnings ration when inflation was 8% was seen as overvalued, because of the fair price-to-earnings ratio being 20-8=12, hence much lower than the real price-to-earnings ratio of 18.
We can then project the delta between the fair PE and real PE onto the asset's value to obtain the projected fair value, which may be a target of future value the asset may reach or hover around.
For example, as of 1st November 2022, SPX stood at 3871.97, with a PE ratio of 20.14 and an inflation in the US of 7.70. Using the Rule Of 20, we find that the fair PE ratio is 20-7.7=12.3, which is much lower than the current PE ratio of 20.14 by 39%! This may indicate a future possibility of a further downside risk by 39% from current valuation levels.
The origins of this rule are unknown, although the legendary US fund manager Peter Lynch is said to have been an active proponent when he was directing the Fidelity’s Magellan fund from 1977 to 1990.
For more infos about the Rule Of 20, reading this article is recommended: www.sharesmagazine.co.uk
This indicator implements the Rule Of 20 on any asset where the Financials are availble to TradingView, and also for the entire SP:SPX index as a way to assess the wider US stock market. Technically, the calculation is a bit different for the latter, as we cannot access earnings of SPX through Financials on TradingView, so we access it using the QUANDL:MULTPL/SP500_PE_RATIO_MONTH ticker instead.
By default are displayed:
current asset value in red
fair asset value according to the Rule Of 20 in white for SPX, or different shades of purple/maroon for other assets. Note that for SPX there is only one calculation, whereas for other assets there are multiple different ways to calculate earnings, so different fair values can be computed.
fair price-to-earnings ratio (PE ratio) in light grey.
real price-to-earnings ratio in darker grey.
This indicator can be used on SP:SPX ticker, and on most NASDAQ:* tickers, since they have Financials integrated in TradingView. Stocks tickers from other exchanges may not provide Financials data, so this indicator won't work then. If this happens, try to find the same ticker on NASDAQ instead.
Note that by default, only the US stock market is considered. If you want to consider stocks or assets in other regions of the world, please change the inflation ticker to a ticker that reflect the target region's inflation.
Also adding a table to ease interpretation was considered, but then the Timeframe MTF parameter would not work, and since the big advantage of this indicator is to allow for historical comparisons, the table was dropped.
Enjoy, and keep in mind that all models are wrong, but some are useful.
Trade safely!
TG
CROCEUsing free cash flow instead of ebit, to be able to evaluate stocks that are not yet profitable.
the formulas are
fcf ttm / (not financial operating working capital - Cash + Net Property Plant and Equipment)
and
fcf yield on Enterprice Value
Example CRWD negative ebit, but cash creation, in this case the expenses in research and development go to affect the ebit.
Capital Asset Pricing Model (CAPM) [Loxx]Capital Asset Pricing Model (CAPM) demonstrates how to calculate the Cost of Equity for an underlying asset using Pine Script. This script will only work on the monthly timeframe. While you can change the default inputs, you should study what CAPM is and how this works before doing so. This indicator pulls various types of data from SPY from various timeframes to calculate risk-free rates, market premiums, and log returns. Alpha and Beta are computed using the regression between underlying asset and SPY. This indicator only calculates on the most recent data. If you wish to change this, you'll have to save the script and make adjustments. A few examples where CAPM is used:
Used as the mu factor Geometric Brownian Motion models for options pricing and forecasting price ranges and decay
Calculating the Weighted Average Cost of Capital
Asset pricing
Efficient frontier
Risk and diversification
Security market line
Discounted Cashflow Analysis
Investment bankers use CAPM to value deals
Account firms use CAPM to verify asset prices and assumptions
Real estate firms use variations of CAPM to value properties
... and more
Details of the calculations used here
Rm is calculated using yearly simple returns data from SPY, typically this is just hard coded as 10%.
Rf is pulled from US 10 year bond yields
Beta and Alpha are pulled form monthly returns data of the asset and SPY
In the past, typically this data is purchased from investments banks whose research arms produce values for beta, alpha, risk free rate, and risk premiums. In 2022 ,you can find free estimates for each parameter but these values might not reflect the most current data or research.
History
The CAPM was introduced by Jack Treynor (1961, 1962), William F. Sharpe (1964), John Lintner (1965) and Jan Mossin (1966) independently, building on the earlier work of Harry Markowitz on diversification and modern portfolio theory. Sharpe, Markowitz and Merton Miller jointly received the 1990 Nobel Memorial Prize in Economics for this contribution to the field of financial economics. Fischer Black (1972) developed another version of CAPM, called Black CAPM or zero-beta CAPM, that does not assume the existence of a riskless asset. This version was more robust against empirical testing and was influential in the widespread adoption of the CAPM.
Usage
The CAPM is used to calculate the amount of return that investors need to realize to compensate for a particular level of risk. It subtracts the risk-free rate from the expected rate and weighs it with a factor – beta – to get the risk premium. It then adds the risk premium to the risk-free rate of return to get the rate of return an investor expects as compensation for the risk. The CAPM formula is expressed as follows:
r = Rf + beta (Rm – Rf) + Alpha
Therefore,
Alpha = R – Rf – beta (Rm-Rf)
Where:
R represents the portfolio return
Rf represents the risk-free rate of return
Beta represents the systematic risk of a portfolio
Rm represents the market return, per a benchmark
For example, assuming that the actual return of the fund is 30, the risk-free rate is 8%, beta is 1.1, and the benchmark index return is 20%, alpha is calculated as:
Alpha = (0.30-0.08) – 1.1 (0.20-0.08) = 0.088 or 8.8%
The result shows that the investment in this example outperformed the benchmark index by 8.8%.
The alpha of a portfolio is the excess return it produces compared to a benchmark index. Investors in mutual funds or ETFs often look for a fund with a high alpha in hopes of getting a superior return on investment (ROI).
The alpha ratio is often used along with the beta coefficient, which is a measure of the volatility of an investment. The two ratios are both used in the Capital Assets Pricing Model (CAPM) to analyze a portfolio of investments and assess its theoretical performance.
To see CAPM in action in terms of calculate WACC, see here for an example: finbox.com
Further reading
en.wikipedia.org
CPI and PPIMarket tracker of the year-on-year (YoY) change in inflation (both PPI Finished Goods and CPI).
Useful for identifying the turns in market conditions, and therefore helps with anticipation of changes in monitory policy.
This metric can be used to inform about current market conditions and potential risk=reward outcomes in the future.
MQ ValueCharts(R)What does ValueCharts(R) do?
There are three primary attributes that help determine price, and that's Cost, Momentum and Value. ValueCharts(R) provides the value component in helping to understand whether price is overpriced or underpriced, which can help determine the optimal time to get into or out of a market. ValueCharts(R) is designed to identify when a stock, option, futures, forex, crypto, index, etc. is overvalued, fairly valued, or undervalued. If a market is overvalued, then it's less likely to keep rising in price. If a market is undervalued, then it's less likely for its price to continue falling.
How does ValueCharts(R) work?
ValueCharts(R) calculates value based on price variability. It analyzes price ranges and movement over a user-specified number of bars to identify when price is at a value extreme relative to a longer-term view of price variability. ValueCharts(R) is an original indicator based on the patented ValueCharts concept (U.S. Patent No. 7,461,023), which is held by the script author. The validity of the ValueCharts algorithm has been vetted by leading experts at Wharton School of Business, the University of Michigan, and UCLA.
Since value is often related to recent price action, two equal adjacent bars with identical open, high, low, and close may have different value scores, since an equal prior bar can affect the value of the current bar. Thus, value can vary even when price does not move. Value varies by timeframe as well, allowing users to identify value correlation between timeframes within the same market. Users can identify being significantly overvalued on a daily chart and adjust their intraday trading with the daily value in mind. Users can adjust the number of bars considered in the calculations to provide a shorter-time view with higher responsiveness, or a longer-term view that reflects a more gradual value scoring. Smaller AnalysisPeriod input values, such as 5, result in greater responsiveness of the indicator to reflect more immediate value extremes. Larger values, such as 14, are more applicable to longer multi-day trades and longer value trends, while shorter inputs are more useful for day trading, for example. A second input, ScalingMultiplier, is a multiplying factor that is generally left unchanged at 0.2, but can be used to linearly expand or contract the subgraph plot values.
We generally find lower AnalysisPeriod values to work best as they provide the greatest responsiveness, even across higher timeframes. ValueCharts(R) determines a mathematical score for each bar's open, high, low and close, and plots the results on a subgraph as an OHLC bar atop color ranges drawn as regions on the subpanel. The color ranges depict 5 different states: Significantly Overvalued (Upper Red), Moderately Overvalued (Upper Yellow), Fairly Valued (Middle Green), Moderately Undervalued (Lower Yellow), and Significantly Undervalued (Lower Red). This makes it simple for users to identify when value is in any of these 5 states so they can make informed decisions about where price may go next, helping to determine when to get in or out of trades.
How is ValueCharts(R) best used?
ValueCharts(R) scores its results and maps them onto a color-coded subgraph to inform the user of the current Value status. Users typically monitor the high point and low points of the bar plot within the indicator to identify what color band each bar reaches. If a bar reaches into a color band, then we consider that bar to be in that state. For example, if a ValueCharts bar reaches into the upper red zone, then it's considered "Significantly Overvalued", and the corresponding price bar is considered "significantly overvalued". Our analysis has shown that when a price bar is significantly overvalued, there's a greater than 90% chance that price will not continue much further, and could possibly reverse at that point. Similarly, when a bar is considered Significantly Undervalued, there's a greater than 90% chance that price will stop falling, perhaps moving sideways, or even reverse higher. This doesn't happen all time, of course, and some markets respond more faithfully than others. Users can see the historical plots to determine whether the current market is aligning well with the signals in the currently selected timeframe. While no one can guarantee what the next bar will do, we can quickly see whether previous ValueCharts(R) signals have worked well for this symbol and timeframe.
Value Zones are as follows:
Significantly Overvalued (red)
Moderately Overvalued (yellow)
Fairly Valued (green)
Moderately Undervalued (yellow)
Significantly Undervalued (red)
The yellow zones depict moderately over- and undervalued zones, where there's a roughly 67% chance that a market will stop moving in that direction. In the center, the green "Fairly Valued" zone is when a market is neither over- nor undervalued. We can sometimes use this zone as a "Value Reset" area, where we move back to a neutral value position, and can move in either an over- or undervalued direction from there. We often see that momentum will continue to push value into the opposite extreme rather than reverse. This works well, as we can sometimes experience markets that are cycling from overvalued to undervalued and back again, which is especially applicable to non-trending markets.
Multi-timeframe Convergence
We can also use ValueCharts(R) across multiple timeframes for the same symbol to identify Multi-Timeframe Value Convergence. If we are significantly Overvalued on more than one timeframe, it creates a more compelling value case than one timeframe alone. In addition, Value state can be more significant on a higher timeframe. We use this concept in implementing a no-trade filter, for example, where if we're significantly undervalued on the 240-minute chart, we refrain from taking bearish trades for the remainder of that trading day, since there's a greater than 90% chance that price will not move lower once it's Value is significantly undervalued.
Inputs:
AnalysisPeriod Value from 5 to n, identifies how many bars of history to consider in value determination, defaults to 5 for fastest responsiveness, though some longer-term traders prefer 14.
Mult A scaling multiplier to amplify the results. Typically keep this at 0.2
SignificantColor Color of the Significantly Overvalued and Significantly Undervalued color ranges, defaults to Red
ModerateColor Color of the Moderately Overvalued and Moderately Undervalued color ranges, defaults to Yellow
FairColor Color of the Fairly Valued color range, defaults to Green
BarColor Color of the bar that overlays the Value color bands within the indicator plot. Defaults to Gray so it appears on both light and dark charts. Suggest using White or Black depending on dark or light colored charts.
Transparency The % transparency level of the indicator's color regions, making it easier to see the Value OHLC bar that appears in front of it. Defaults to 60 for 60%. 0 is opaque, 100 is fully transparent.
Version Provides the version number / ID of the indicator
Additional usage suggestions
Visibility: ValueCharts(R) works on either a light or dark color theme. By default, the indicator's OHLC bars are gray, which is visible on either color theme. You can increase the contrast by changing the Bar Color input to Black on a light background, or to White on a dark background. You can also enhance the visibility by setting the input, Color Transparency to a larger number, such as 60. This will mute the colors, allowing the OHLC bars to stand out more.
PEG Ratio (Most Accurate)Price Earnings To Growth (PEG) Ratio
PEG ratio is a stock's PE ratio divided by the growth rate of its earnings for a specified time period.
The PEG ratio is used to determine a stock's value while also factoring in the company's expected earnings growth, and it is thought to provide a more complete picture than the more standard P/E ratio.
PEG ratio 1 is fair value.
PEG ratio above > 2 is are generally considered overvalued.
PEG ratio below < 1 is Undervalued.
Negative PEG ratio indicate the company no growing in specified time period.
Example of How to Use the PEG Ratio
The PEG ratio provides useful information to compare competitive companies and see which stock might be the better choice for an investor's needs, as follows.
Google (13-Sep-2022) 👍
PEG ratio = 0.38%
P/E ratio = 19.17%
Meta (13-Sep-2022) 👎
PEG ratio = 0.63%
P/E ratio = 12.55%
Many investors may look at Meta and find it more attractive since it has a lower P/E ratio. But compared to Google, it doesn't have a high enough growth rate to justify its current P/E.
Google is trading at a discount to its growth rate and investors purchasing it are paying less per unit of earnings growth. Based on its lower PEG, Google may be relatively the better buy.
Blockchain Fundamentals - Active Address Sentiment Osc. [CR]Blockchain Fundamentals: Active Address Sentiment Oscillator AASO
Back with another script today, this one is a useful tool in helping to determine bitcoins value. We are looking at 2 data sources: the daily active addresses on the BTC blockchain, and the daily returns of BTC.
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
There is an interesting relationship that you can see by comparing the two timeseries. But for us to create a good indicator we first need to normalize the data. So we look at the percent change over the past 28 days for each metric (DAA and price).
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
We then calculate standard deviation bands around the DAA metric. We finalize them by averaging the bands over a 28 day period.
When the Price series (yellow line) is higher than the SD bands BTC is considered overvalued or price is overheated. A pullback could be expected soon. When the Price series is below the SD bands BTC is considered undervalued or price is oversold.
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
This tool doesnt give signals on the one minute chart or tell you exactly when to buy or sell. BUT what it does do is act as a convenient macro sentiment indicator that is not based completely upon price.
In an attempt to narrow down the really juicy areas, if you seen the background color highlights with white, that means its likely a top or bottom. At the very least on a local sense and many times in a cyclical macro sense as well. It also narrows down the signal to a generally more profitable area.
This indicator is not meant to be used on timeframes other than daily (did I mention that already?). I am lazy and did not code the calculations to be MTF (which is why you have to use on the daily chart). If you want to code this, please forward it on to me and I will post an update with a heartfelt credit to you.
Blockchain Fundamentals: Electricity Cost of BTC [CR] Blockchain Fundamentals: Electricity Cost of BTC
After a hiatus, now a return to publishing tools and scripts for the community. This is my first script in over and year, and I have a number more coming soon as well! (so Stay Tuned!)
This is a simple calculator to estimate the cost of Bitcoin miners to mine one bitcoin. It works on all timeframes (doesnt have to be on daily).
By entering the inputs of total TH's, kWh used, cost of electricity per kWh (in USD cents) we can generate the electricity cost.
But miners also have other costs of operation including HVAC, maintenance, rent, etc. In light of that we include a multiplier that accounts for these extra costs. First, type in what percent of your total operating costs come from the electricity. Then check the enable total cost plot option and you will also see total costs in addition to electricity costs.
Its a simple model and gives anyone curious a starting point for their own testing and research.
Close Combination Lock Style - Visual AppealThis creates a combination style closing price change on each tick.
It has two theme options, one as silver dials for Dark Theme and the other as black dials for White Theme.
We get fixated to watching closing prices on charts and it gets visually daunting. This creates a combination style price change which updates on each tick, which is quite pleasing to the eye.
When new price is above current center line, it shift the above prices showing ▲ arrow, and if new price is lower, it will shift the bottom prices showing ▼ arrow. If there is no change in price between the ticks, it will show =.
Financial Intelligent Eval [Fundamental] (MYTRIC)█ OVERVIEW
Financial Algorithm is a system to quickly understanding company fundamental, and judge the company type based on their financial condition.
All evaluation from the system is the result of combination with Balancing Calculation and Company Historical Financial Data(Financial Report) by using over than 30 financial ratios.
This indicator are classified into 5 level (Very Weak, Weak, Moderate, Good, Excellent)
Advantages of Financial Algorithm
• By combining and calculating company's latest 4 quarterly report, provide rating to help investor quickly know about company's fundamentals and financial performance.
• Able to identify company have what kind of strength, weakness, chance and threat. For instance, according to current economic situation, is it an advantages or a threat for a company, investor can identify it via Financial Algorithm.
• Able to identify which company have better business management by keep following the company rating, observe the improvement level of company's.
Application
*When notice there are not improvement on a company's fundamentals or financial performance which is profitable without further developing, it usually reveals the lack of management capability to generate more value, company unable to fully utilise its profit, reinvest and expanding its business to become more competitive. Sometimes this kind of company may be suspected accounting fraud.
█ BENEFITS
• Avoid investing in companies suspected of financial fraud.
• To quickly understanding company's fundamental and financial structure.
• Able to analyze whether the company build profit after it is used to optimize the company's internal
█ FEATURES
You can configure the following attributes of the display:
• Table position on your chart.
• The size and colour of text.
• Language between English and Chinese.
• Rating bar chart colour.
• On / Off Statement Review Helper Function
• On / Off 3 Years Evaluation Function
• On / Off Basic Information
• Full descriptions of each evaluation and content are included in the settings
█ LIMITATIONS
• When changing the indicator's inputs, allow around 20 seconds calculation for the change to be reflected in the display.
• This system only able to evaluate non-financial industry.
• This system is based on company's historical financial report data to generate the results and rating, it does not includes prediction from any external factor.
(External Factor: Business Model, Business Distribution & Geography, Corporate Structure, Competitor and Peer company's, Prospect, Costing Breakdown, Disaster and etc)
• Any results calculated by this system all is based on data provided by Tradingview, Data may have some tolerance, we recommend that users pay attention to the official quarterly/annual report.
█ FINANCIALS INTELLIGENT ALGORITHM FUNCTION
This lists all combination calculate financials.
01. Total Revenue
02. Earnings before interest and tax
03. Net Income
04. Property, Plant, and Equipment
05. Total Receivables
06. Cash and short-term Investments
07. Cash & Cash equivalents
08. Total Liability
09. Working Capital
10. Total Debt
11. Total Equity
12. Retained Earnings
13. Total Asset
14. Cash From Operating Activities
15. Income before extraordinary items
16. Total depreciation and amortization
17. Free Cash Flow
18. Altman Z-score
19. Cash to Debt Ratio
20. Current Ratio
21. Debt to Assets Ratio
22. Debt to Equity ratio
23. EBITDA Margin
24. Free Cash Flow Margin
25. Grahams Number
26. Net Margin
27. Price Book Ratio
28. Piotroski-F Score
29. Quick Ratio
30. Return on Assets
31. Return on Equity
32. Return on Invested Capital
33. Float Shares Outstanding
34. Total Common Shares Outstanding
35. Cash to Revenue
36. Cash to Market Capital
37. Cash to Debt
38. Receivable Turnover
39. Quality of Earning
40. Market Capital
8 financial evaluation :
3 years financial evaluation tracking :
Statement Review Helper :
█ HOW TO MAKE THE RIGHT INVESMENT OR TREND TRADING DECISION BASED ON OUR EVALUATION
Avoid mid/long term invest in companies with poor financial evaluation, only suite for trend trading. The below following assessments need to be focused.
• Comprehensive rating is poor or below.
• Quality of Earning is very poor or below.
• Receivability is very poor or below (Total Receivable is too high)
• Before : Poor Financial Strength with revenue growth
• After : The price dropped by about -80% within 2 months
███████████████████████████████████████████████████████████████████████████████████████████
• Before : Poor Financial Strength with revenue growth
• After : The price dropped by about -90% within 1 year
███████████████████████████████████████████████████████████████████████████████████████████
• Before : Excellent Financial Strength
• After : Steady growth
Steady growth
• Conclusion :
Do not judge it as a good company just because it has continuous income.
When we analyze the company's financial report, we should not only look at the company's revenue,
we should pay more attention to the company's finances and weaknesses.
Only companies with strong financial strength that can expand their business in a stable manner.
Disclaimer :
*The following conclusion are purely based on my personal opinions and views, it’s only for study and research, without any trading and investment advice.
Outlier Detector with N-Sigma Confidence IntervalsA detrended series that oscilates around zero is obtained after first differencing a time series (i.e. subtracting the closing price for a candle from the one immediately before, for example). Hypothetically, assuming that every detrended closing price is independent of each other (what might not be true!), these values will follow a normal distribution with mean zero and unknown variance sigma squared (assuming equal variance, what is also probably not true as volatility changes over time for different pairs). After studentizing, they follow a Student's t-distribution, but as the sample size increases (back periods > 30, at least), they follow a standard normal distribution.
This script was developed for personal use and the idea is spotting candles that are at least 99% bigger than average (using N = 3) as they will cross the upper and lower confidence interval limits. N = 2 would roughly provide a 95% confidence interval.
Stock Value Display//This study is designed to plot estimates for a stock's value:
//1) the Price to earnings ratio (PE) value based on the trailing twelve months of data
//2) the PE value based future data
//3) the Benjamin Graham value based trailing data
//4) the Dividend Discount value based on trailing data
You can adjust the period of data used to calculate the value between Fiscal Quarter "FQ" and Fiscal Year "FY."
The values displayed on the chart are subject to the financial information provided to TradingView. This is intended to be used as a quick reference and should be viewed in context with other analysis prior to making any transaction decisions.
As always, happy trading!
Compound Value @ annual rateBy studying historical data we can know the compounded growth rate of an investment from the inception date. For example if we know that an investment has grown at the rate of 6% in the past and if we expect similar growth in the future also, We can plot this graph to understand whether the current price is underpriced or overpriced as per projected return.
In this graph, it takes the initial close price as a principle and rate from the input and calculates the compound amount at each interval.
Intrinsic value calculation Intrinsic value calculator based on Warren Buffet's and Ben Graham's work
In value investing determing the true value of a COMPANY instead of a stock price is crucial.
This little indicator shows the "Intrinsic value" of the choosen stock meaning the value of the stock in 10 years time. Calculation is based on historical book value's average annual growth rate and dividends paid.
Since this is about long therm investing, use monthly charts.
"Intrinsic value can be defined simply: It is the discounted value of the cash that can be taken out of a business during its remaining life.”
– Warren Buffett
One way to calculate that is by the growth in per share book value and dividends taken in the forseeable future (10 years) than discount it with the prevailing 10 year note's rate.
In the inputs you have to set 2 variables:
1. How many years back you have the first data for book value per share available?
2. What was the per share book value that year?
(Bookvalue is ploted in olive colour and you can get the oldest one if you move your cursor over the latest data on the left)
CAUTION! You have to reenter it for every stock you analyse as this is stock-specific data!
After setting the input data, you will see the "Intrinsic Value"'s pink curve ploted over the price chart.
If the price is well below the pink line, the company is undervalued and can be a possible applicant for long therm investment.
Margin of safety: when the current price is 50% below the intrinsic value that means a 10% yearly growth potential (100% growth in 10 years) or a 100% margin of safety.
I am a beginer in Pine so please excuse my coding...
If anybody knows hot to extract historical data from 15 years ago, please share it with me, so I can automate the whole calculation without inputs necessary.
Metcalfes Law - Bitcoin Fair PriceMetcalfe's Law has been successfully used to value a variety of network effect technologies and businesses, including Facebook and Tencent.
Applying Metcalfe's Law to Bitcoin, using "Daily Active Addresses" (DAA) as the "n" value, yields interesting results.
Historically, Bitcoin has tracked the Metcalfe Law Fair Price reasonably well. A number of studies have been performed over recent years which validate this and have used various derivations of Metcalfe’s Law. Note: this indicator sticks to the original Metcalf’s Law.
Prior to 2018, every time Bitcoin was above the Metcalfe’s Law fair price (calculated using a default “A” of 0.5 here), a bubble had formed, and price quickly reverted back down to the mean.
Nonetheless, since February 2018, Metcalfe's Law Fair Price has remained below the actual Bitcoin price, suggesting Bitcoin is currently overvalued.
There may be a few reasons for this:
1. Possibility A: Bitcoin may still be extremely overvalued. Since the December 2017 peak, Bitcoin has only reverted to the Metcalfe’s Law Fair Price briefly during the December 2018 bottom. If this case is true, there could be further to fall unless DAA numbers pick up to fill the gap.
2. Possibility B: The introduction of side-chains, private transactions and the Lightning Network may have fundamentally altered the effectiveness of using DAA to value Bitcoin. As more daily transactions are completed off-chain, or on large platforms/exchanges which use fewer addresses, the relative number and growth of DAA may be misrepresented and artificially low. In this case, DAA as it is reported today is no longer useful in assessing the fair value of Bitcoin with Metcalfe’s Law and this Indicator is effectively useless.
3. Possibility C: Neither of the above are true. We are just in an anomalous period in which price and Metcalfe’s Law Fair Price have deviated from the mean for an extended period (and will meet again in the future, potentially at a higher price).
4. Possibility D: Metcalfe’s Law doesn’t really work for Bitcoin.
I am inclined to believe Possibilities “C” and “D” are unlikely. Given the way Bitcoin infrastructure is being developed and used in 2019, Possibility “B” seems the most likely, as this case is supported by the fact that a number of other metrics indicate that Bitcoin is currently on the lower side of “fair value” (including Dynamic Range NVT Signal).
Regardless, Possibility “A” remains a strong candidate. Only time will tell. It will be interesting to check back on this indicator in 12-24 months time. Hopefully this indicator has been proven redundant by then.
Volume ValueInstead of the Volume this plots the closure price times volume, hence the Value.
Useful in study of long term phenomenons.
Current Price Label by Westy_A simple Indicator to display the current price of the asset above the current bar. It shows a green label if the close is equal or greater than the open, red otherwise.
NVT Signal with RMA and thresholds [alertable]NVT Signal, or NVTS, is an indicator that compares the market cap of Bitcoin to the aggregate USD value of daily transactions on the Bitcoin blockchain. It is a value indicator that shows a multiple of Bitcoin price against the actual usage of its blockchain. When the NVTS is low, it suggests Bitcoin price is low relative to the amount of utility the network provides, and vice versa.
For more information on NVTS, visit medium.com
This indicator aims to provide the following:
1. An open-source implementation of NVTS on Tradingview, as the most popular one currently is closed-source.
2. To provide two simple ways to define and visualize "overbought" or "oversold" conditions using the NVTS. Here, we have absolute value of NVTS & deviation from a long-term moving average.
3. Crude integration into Tradingview's alert system.
What this indicator CANNOT do:
1. Timeframes below 1d.
2. Signals based on statistical analyses, such as seen in Bollinger Bands et al. (However, with the appropriate type of account, you can add BBands on top of this indicator.)
I would like to express my gratitude to Willy Woo, Chris Burniske and Dimitry Kalichkin for their work on NVT Ratio and NVT Signal, without which my indicator would not have been created.
Feel free to fork & improve, or experiment with settings. I hope this indicator will be useful to someone.
BitMEX ETHUSD contract value (USD)The ETHUSD Quanto Swap contract on BitMEX allows you to trade ETHUSD with Bitcoin put forward as collateral. However this means that 1 contract is not equal to 1 USD or 1 ETH, but instead varies according to the price of ETHUSD.
You can see the contract specs here www.bitmex.com and find more information here blog.bitmex.com
My advice is always to make sure you fully understand a derivative product before you trade it, however many of us may not have the acumen to actually understand how a quanto swap works. Nevertheless, we have to be aware that the value in USD of each contract depends on the price of Ethereum and also the price of Bitcoin at each point in time.
This tool will show you the value of a single ETHUSD contract in USD, but it solely for indicative purposes only. Your trade, your risk. I do not ask for any donations from your gains and I am not liable for any of your losses.
Source code is provided.
Note in the example image that the price of ETHUSD is plotted on a logarithmic scale but the indicative contract value is linear.
Chiki-Poki BFXLS Longs Shorts Abs Normalized Volume Pro by RRBChiki-Poki BFXLS Longs vs Shorts Absolute Normalized Volume Value Pro by RagingRocketBull 2018
Version 1.0
This indicator displays Longs vs Shorts in a side by side graph, shows volume's absolute price value and normalized volume of Longs/Shorts for the current asset. This allows for more accurate L/S comparisons (like a log scale for volume) since volume on spot exchanges (Bitstamp, Bitfinex, Coinbase etc) is measured in coins traded, not USD traded. Similarly, L/S is usually the amount of coins in open L/S positions, not their total USD value. On Bitmex and other futures exchanges volume is measured in USD traded, so you don't need to apply the Volume Absolute Price Value checkbox to compare L/S. You should always check first whether your source is measured in coins or USD.
Chiki-Poki BFXLS primarily uses *SHORTS/LONGS feeds from Bitfinex for the current crypto asset, but you can specify custom L/S source tickers instead.
This 2-in-1 works both in the Main Chart and in the indicator pane below. You can switch between Main/Sub Window panes using RMB on the indicator's name and selecting Move To/Pane Above/Below.
This indicator doesn't use volume of the current asset. It uses L/S ticker's OHLC as a source for SHORTS/LONGS volumes instead. Essentially L/S => L/S Volume == L/S
Features:
- Display Longs vs Shorts side by side graph for the current crypto asset, i.e. for BTCUSD - BTCUSDLONGS/BTCUSDSHORTS, for ETHUSD - ETHUSDLONGS/ETHUSDSHORTS etc.
- Use custom OHLC ticker sources for Longs/Shorts from different exchanges/crypto assets with/without exchange prefix.
- Plot Longs/Shorts as lines or candles
- Show/Hide L/S, Diff, MAs, ATH/ATL
- Use Longs/Shorts Volume Absolute Price Value (Price * L/S Volume) instead of Coins Traded in open L/S positions to compare total L/S value/capitalization
- Normalize L/S Volume using Price / Price MA / L/S Volume MA
- Supports any existing type of MA: SMA, EMA, WMA, HMA etc
- Volume Absolute Price Value / Normalize also works on candles
- Oscillator mode with negative axis (works in both Main Chart/Subwindow panes).
- Highlight L/S Volume spikes above L/S MAs in both lines/oscillator.
- Change L/S MA color based on a number of last rising/falling L/S bars, colorize candles
- Display L/S volume as 1000s, mlns, or blns using alpha multiplier
1. based on BFXLS Longs vs Shorts and Compare Style, uses plot*, security and custom hma functions
2. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
Notes:
- Make sure that Left Price Scale shows up with Auto Fit Data enabled. You can reattach indicator to a different scale in Style.
- It is not recommended to switch modes multiple times due to TradingView's scale reattachment bugs. You should switch between Main Chart and Sub Window only once.
- When the USD price of an asset is lower you can trade more coins but capitalization value won't be as significant as when there are less coins for a higher price. Same goes for Shorts/Longs.
Current ATH in shorts doesn't trigger a squeeze because its total value is now far less than before and we are in a bear market where it's normal to have a higher number of shorts.
- You should always subtract Hedged L/S from L/S because hedged positions are temporary - used to preserve the value of the main position in the opposite direction and should be disregarded as such.
- Low margin rates increase the probability of a move in an underlying direction because it is cheaper. High margin rates => the market is anticipating a move in this direction, thus a more expensive rate. Sudden 5-10x rate raises imply a possible reversal soon. high - 0.1%, avg - 0.01-0.02%, low - 0.001-0.005%
You can also check out:
- BFXLS Longs/Shorts on BFXData
- Bitfinex L/S margin rates and Hedged L/S on datamish
- Bitmex L/S on Coinfarm.online
Session min/max pointsMinimum and maximum points in a day trading session. It may help you spot the range which min and max occur in a session.
In day trading, for example, at securities like GBPNZD, minimum happens between 02:00-05:00 ET and maximum between 08:00-14:00 ET. This indicator can help you test this hypothesis.
Happy trading!
