[blackcat] L3 Financial Minesweeper: Altman Z ScoreLevel: 3
Background
The Altman Z-score is the output of a credit-strength test that gauges a publicly traded manufacturing company's likelihood of bankruptcy. The Altman Z-score is a formula for determining whether a company, notably in the manufacturing space, is headed for bankruptcy.
Function
The possibility of financial failure or bankruptcy of the enterprise is analyzed and predicted through the comprehensive score. The lower the Z value, the more likely the enterprise will go bankrupt. By calculating the Z value of an enterprise for several consecutive years, we can find out whether the enterprise has signs of financial crisis. Generally speaking, when the Z value is greater than 2.675, it indicates that the financial situation of the enterprise is good, and the possibility of bankruptcy is small; When the value is less than 1.81, it indicates that the enterprise is in a potential bankruptcy crisis; when the Z value is between 1.81 and 2.675, it is called a "gray area, indicating that the financial situation of the enterprise is extremely unstable.
Remarks
STOCKs ONLY which require financial data.
X1~X5 coefficients can be customized for different stock markets.
Compared to TradingView official Altman Z-Score Indicator.
Feedbacks are appreciated.
Analysis
Volatility Calculator for Daily Top and Bottom RangeWith the usage of ATR, applied on the close of the daily candle, I am calculated the volatility channels for the TOP and BOTTOM
Based on this logic, we can estimate, with a huge confidence factor, where the prices are going to be compressed for the trading day.
Having said that, lets take a look at the data gathered among the most important financial markets:
SPX
TOP CROSSES : 2116
BOT CROSSES : 1954
Total Daily Candles : 18908
Occurance ratio = 0.215
NDX
TOP CROSSES : 1212
BOT CROSSES : 1183
Total Daily Candles : 9386
Occurance ratio = 0.255
DIA
TOP CROSSES : 759
BOT CROSSES : 769
Total Daily Candles : 6109
Occurance ratio = 0.25
DXY
TOP CROSSES : 1597
BOT CROSSES : 1598
Total Daily Candles : 13156
Occurance ratio = 0.243
DAX
TOP CROSSES : 1878
BOT CROSSES : 1848
Total Daily Candles : 13155
Occurance ratio = 0.283
BTC USD
TOP CROSSES : 416
BOT CROSSES : 417
Total Daily Candles : 4290
Occurance ratio = 0.194
ETH USD
TOP CROSSES : 247
BOT CROSSES : 268
Total Daily Candles : 2452
Occurance ratio = 0.21
EUR USD
TOP CROSSES : 820
BOT CROSSES : 805
Total Daily Candles : 7489
Occurance ratio = 0.217
GOLD
TOP CROSSES : 1722
BOT CROSSES : 1569
Total Daily Candles : 13747
Occurance ratio = 0.239
USOIL
TOP CROSSES : 1077
BOT CROSSES : 1089
Total Daily Candles : 10231
Occurance ratio = 0.212
US 10Y
TOP CROSSES : 1302
BOT CROSSES : 1365
Total Daily Candles : 9075
Occurance ratio = 0.294
Based on this, we can assume with a very high confidence ( 70-80%) that the market is going to stay, within the range created from the BOT and TOP ATR points.
Heikin Multi Time Frame// How it Works \\
This script calculates the open and close prices of Heikin Ashi candles across multiple timeframes,
If the candle formed on that timeframe is green it will display in the table a green square, If the candle is red, the square will display red.
// Settings \\
You can change the colours of the plots
You can also Change any of the timeframes which the Heikin Ashi candles are being calculated on
// Use Case \\
Heikin Ashi candles are often used to give a smoother trend direction and help cancel out some of the noice/consolidation.
It can also be use as trend detection for multiple timeframes at once
/ / Suggestions \\
Happy for anyone to make any suggestions on changes which could improve the script,
// Terms \\
Feel free to use the script, If you do use the scrip please just tag me as I am interested to see how people are using it. Good Luck!
IsPullbackPivotRetested experimentThe indicator counts how often a pullback that starts outside the Keltner Channel resolves or fails.
Resolves: the pullback high or low is retested.
Fails: price goes outside the oppositie side of the Keltner Channel.
FunctionPolynomialFitLibrary "FunctionPolynomialFit"
Performs Polynomial Regression fit to data.
In statistics, polynomial regression is a form of regression analysis in which
the relationship between the independent variable x and the dependent variable
y is modelled as an nth degree polynomial in x.
reference:
en.wikipedia.org
www.bragitoff.com
gauss_elimination(A, m, n) Perform Gauss-Elimination and returns the Upper triangular matrix and solution of equations.
Parameters:
A : float matrix, data samples.
m : int, defval=na, number of rows.
n : int, defval=na, number of columns.
Returns: float array with coefficients.
polyfit(X, Y, degree) Fits a polynomial of a degree to (x, y) points.
Parameters:
X : float array, data sample x point.
Y : float array, data sample y point.
degree : int, defval=2, degree of the polynomial.
Returns: float array with coefficients.
note:
p(x) = p * x**deg + ... + p
interpolate(coeffs, x) interpolate the y position at the provided x.
Parameters:
coeffs : float array, coefficients of the polynomial.
x : float, position x to estimate y.
Returns: float.
Key Financials A simple table with up to 9 key financials on your chart.
Simple, easy and configurable.
S&P 500 Earnings Yield SpreadThis indicator compares the attractiveness of equities relative to the risk-free rate of return, by comparing the earnings yields of S&P 500 companies to the 10Y treasury yields. "Earnings yield" refers to the net income attributable to shareholders divided by the stock's price - effectively the inverse of the PE ratio. The tangible meaning of this metric is "the annual income received by (attributable to) shareholders as a percent of the price paid to receive said income." Therefore, earnings yield is comparable to bond yields, which are "the annual income received by bond holders as a percent of the price paid to receive said income."
This indicator subtracts the earnings yield of S&P 500 companies from the current 10-year treasury bond yield, creating a "spread" between the yields that determines whether equities are currently an attractive investment relative to bonds. That is, if the S&P 500 earnings yield exceeds the 10Y treasury yield, then equity investors are receiving more attributable income per dollar paid than bondholders, which could be an indication that equities are an attractive purchase relative to the risk-free rate. The same applies vice-versa; if the 10Y treasury yield exceeds that of the S&P 500 earnings yield, then equities may not be an attractive investment relative to the risk-free rate.
Since data on S&P 500 companies' earnings yields are pulled on a monthly basis, this indicator should be used on a monthly timeframe or longer. Historical data has shown that the critical zones for the indicator are at -4% and +3%, i.e. when equities are trading with a 4% greater yield than 10Y T-bonds and when equities are trading with a 3% lower yield than 10Y T-bonds, respectively. In the "Oversold" case (-4%), equities are trading at a steep discount to the risk-free rate and has often represented a strong buying opportunity. In the "Overbought" case (+3%), equities are trading at a premium to the risk-free rate, which may be an indication that caution should be exercised within the stock market. When the indicator first crosses into "Oversold" territory, this has historically been near a the bottom of a crash on the S&P 500. When the indicator first crosses into the "Overbought" territory, this has often precipitated a correction of 15% on the S&P 500.
Some notable "misses," crashes that this indicator missed, include the 1973 stock market crash and the 2008 global recession. However, both of these cases were largely precipitated by unprecedented economic events, as opposed to stocks simply being "Overbought" relative to treasury yields. Nonetheless, this indicator should form only a small portion of your fundamental analysis, as there are many macroeconomic factors that could lead to major corrections besides the impact of treasury yields. Furthermore, it should also be noted that since markets are "forward looking," future earnings growth or interest rate hikes may become "priced into" both the stock and bond markets, affecting the outputs of this indicator. However, since both the stock and bond markets should account for these factors simultaneously, the impact has historically been minimized.
I hope you find this indicator to be beneficial to your strategies. Stay safe, and happy trading.
Accumulation/Distribution Bands & Signals (BTC, 1D, BITSTAMP) This is an accumulation/distribution indicator for BTC/USD (D) based on variations of 1400D and 120D moving averages and logarithmic regression. Yellow plot signals Long Term Accumulation, which is based on 1400D (200W) ALMA, orange plot signals Mid Term Accumulation and is based on 120D ALMA, and finally the red plot signals Long Term Distribution that's based on log regression. It should be noted that for red plot to work BTC 1D BITSTAMP graph must be used, because the function of the logarithmic regression was modified according to the x axis of the BITSTAMP data.
Signal bands have different coefficients; long term accumulation (yellow) and and the log regression (red) plots have the highest coefficients and mid term accumulation (orange) has the lowest coefficients. Coefficients are 6x, 3x and 1.5x for the red (sell) and yellow (buy) plots and 1x, 2x and 3x for the orange (buy) plot. Selling coefficient for the yellow and the orange plots are respectively 2x and 1x. Buy and sell signals are summed up accordingly and plotted at the top of the highest band.
Acknowledgement: Credits for the logarithmic regression function are due @memotyka9009 and Benjamin Cowen
Bitcoin Movement vs. Coin's Movement MTFThis script tracks the percent change of Bitcoin vs. the percent change of the coin on the chart. Crypto markets are usually affected greatly by Bitcoin swings so being able to see if the given coin is trending above or below Bitcoin is useful market data. All choices made with this script are your own! Thanks.
FunctionPeakDetectionLibrary "FunctionPeakDetection"
Method used for peak detection, similar to MATLAB peakdet method
function(sample_x, sample_y, delta) Method for detecting peaks.
Parameters:
sample_x : float array, sample with indices.
sample_y : float array, sample with data.
delta : float, positive threshold value for detecting a peak.
Returns: tuple with found max/min peak indices.
TradingGroundhog - Fundamental Analysis - Multiple RSI Ema(Script Available Version of my previous Fundamental Analysis - Multiple RSI Ema )
As the number of crypto currencies is expanding, we need to find the one which will boom in the next months, weeks or even days.
Therefore, I present to you a Fundamental Analysis tool based on RSI built in order to compare the RSI between the diverse cryptocurrencies.
When cryptocurrencies start to trend, become active, minable and especially "buyable", people are investing their money into them.
As a result,the Daily RSI rises and the price of the crypto in question increases steadily.
With "Fundamental Analysis - Multiple RSI EMA" you can :
Follow up to 20 RSI from different exchanges at the same time.
Find easily Increasing/Decreasing RSI as the lines get transparent if their RSI decrease.
You can also select market with high potential of booming as :
Booming Market : 60 < Daily RSI <= 100 (Strong green background)
Potent Market : 55 < Daily RSI <= 60 (Light green background)
Sleepy Market : 50 < Daily RSI <= 55 (Light red background)
Dying Market : 0 < Daily RSI <= 50 (Strong red background)
Futur booming crypto will go from the Potent Market to the Booming Market
Can be used with the following time frames depending on the necessity:
4H
Daily (Preferred)
Weekly
Monthly
Good trades !
Disclaimer (As it should always be one to any script)
***
This script is intended for and only to be used for personal purposes only. No such information provided by it constitutes advice or a recommendation for any investment or trading strategy for any specific person. There is no guarantee presented or implied as to the accuracy of specific forecasts, projections, or predictive statements offered by the script. Users of the script agree that its original developer does not take responsibility for any of your investment decisions. Please seek professional advice before trading.
***
Fibonacci Moving AverageThe Fibonacci Moving Average is a powerful indicator that takes into account many underlying moving averages to give out an approximate short-term/long-term view of the markets. Its strength lies with dynamic support and resistance levels. I have created this indicator in order to improve trend-following entry positions.
© AlpHay : SECURITY FUNDAMENTAL TABLE// Equity Fundamental Data Report Table:
// Data Provider: Tradingview
// I am not a financial advisor or expert.
// This is my interpretation of this data. Consider this data doesn't represent the whole picture of what is going on!
// If you find some fundamentally wrong thinking about this approach, please inform me.
// I am open to suggestions. I am also looking for answers.
// Use it with a daily timeframe for data consistency.
// You can change or customize the threshold values whatever you want.
// www.tradingview.com
Pivot TrackerThis script finds swing lows and swing highs based on input criteria for lookback and lookforward periods, and plots letters accordingly.
Helps identify trend or lacktherof
HH = higher high
LH = lower high
HL = higher low
LL = lower low
Multi timeframe Stochastic RSI Screener by noop42Here is a custom x4 timeframes Stochastic RSI screener to add on your charts.
Options
Repaint mode : if enabled: values are updated in live, if disabled: values are updated once the concerned candle is closed
Default parameters
Timeframes: 1, 5, 15, 60
Repaint mode: enabled
Notes
Use the lowest timeframe configured on the screener to get real values
A classic x3 multi-timeframe Stochastic RSI indicator is also available
Volume Pressure AnalysisVolume Pressure Analysis is a new concept I have been working on designed to show the effort required to move price. An ideal tool for confirming trends or locating reversals early. This indicator can highlight whale action and market manipulation. It calculates volume vs volatility and displays the results as a meter:
Above 0 shows how easy price action is traveling, the bigger these bars the less volume and effort is required to push price. These are indicated with a teal or red arrows and can confirm the beginning or continuation of a trend. This is the natural direction the chart wants to travel at that time.
Below 0 shows how hard price is to move. The bigger these bars the more volume and effort is required to push price. When whales and market makers push price against its will these bars will get bigger.
Yellow arrows signal pressure in that direction and excessive amounts of volume is required to move price. These signals can lead to reversal/ pivot points as price action struggles to continue its trend. These signals can be turned on in settings or use the overlay version of this script to display signals on chart. This is a very powerful tool when used with relative volume.
Volume Pressure Analysis - OverlayVolume Pressure Analysis is designed to show effort required to move price. This script is the overlay version that displays signals on the candles as well as changes the bar colors. Yellow arrows signal pressure in that direction and excessive amounts of volume is required to move price. These signals can lead to reversal/pivot points as price action struggles to continue its trend. Red and teal arrows indicate free flowing price action where very little effort or volume is needed to push price. These signals can confirm the beginning or continuation of a trend and is the natural direction the chart wants to travel at that time. For more information please check out the main Volume Pressure Analysis indicator.
Percentile - Price vs FundamentalsThis is done in the same lines of below scripts
Drawdown-Price-vs-Fundamentals
Drawdown-Range
Instead of using drawdown, here we are only plotting percentile of drawdown. Also added few more fundamental stats to the indicator. Also using part of the code from Random-Color-Generator/ to automatically generate colors. This in turn uses code from @RicardoSantos for convering color based on HSL to RGB
This is how the study can be used:
Study plots percentile of price and each of the listed fundamentals based on history. History can be chose All time or particular window. If any fundamental or price is near 100 - which means it is nearer to its peak. And if something is near its bottom, it is nearer to its 0th percentile.
Price of the stock is considered undervalued based on historical levels when it is below most of the fundamentals. Price is considered overvalued based on historical levels when it is above all the fundamentals. Please note, being undervalued does not guarantee immediate mean reversion. Stocks can stay undervalued for prolonged time and can go further down. Similarly overvalued stock can stay overvalued for prolonged time before correcting itself or justifying the position. Hence, further discretion needs to be used while using this study.
Few examples:
AMZN seems to be trading in range and so are the fundamentals:
MSFT at peak along with half of the fundamentals. But, debt levels are going up along with margins reducing.
LPX is trading at 15% discount whereas most of the fundamentals are at the peak.
FLGT price seems to have gone down further whereas fundamentals look pretty healthy.
Drawdown RangeHello death eaters, presenting a unique script which can be used for fundamental analysis or mean reversion based trades.
Process of deriving this table is as below:
Find out ATH for given day
Calculate the drawdown from ATH for the day and drawdown percentage
Based on the drawdown percentage, increment the count of basket which is based on input iNumber of ranges . For example, if number of ranges is 5, then there will be 5 baskets. First basket will fit drawdown percentage 0-20% and each subsequent ones will accommodate next 20% range.
Repeat the process from start to last bar. Once done, table will plot how much percentage of days belong to which basket.
For example, from the below chart of NASDAQ:AAPL
We can deduce following,
Historically stock has traded within 1% drawdown from ATH for 6.59% of time. This is the max amount of time stock has stayed in specific range of drawdown from ATH.
Stock has traded at the drawdown range of 82-83% from ATH for 0.17% of time. This is the least amount of time the stock has stayed in specific range of drawdown from ATH.
At present, stock is trading 2-3% below ATH and this has happened for about 2.46% of total days in trade
Maximum drawdown the stock has suffered is 83%
Lets take another example of NASDAQ:TSLA
Stock is trading at 21-22% below ATH. But, historically the max drawdown range where stock has traded is within 0-1%. Now, if we make this range to show 20 divisions instead of 100, it will look something like this:
Table suggests that stock is trading about 20-25% below ATH - which is right. But, table also suggests that stock has spent most number of days within this drawdown range when we divide it by 20 baskets instad of 100. I would probably wait for price to break out of this range before going long or short. At present, it seems a stage ranging stage. I might think about selling PUTs or covered CALLs outside this range.
Similarly, if you look at AMEX:SPY , 36% of the time, price has stayed within 5% from ATH - makes it a compelling bull case!!
NYSE:BABA is trading at 50-55% below ATH - which is the most it has retraced so far. In general, it is used to be within 15-20% from ATH
NOW, Bit of explanation on input options.
Number of Ranges : Says how many baskets the drawdown map needs to be divided into.
Reference : You can take ATH as reference or chose a time window between which the highest need to be considered for drawdown. This can be useful for megacaps which has gone beyond initial phase of uncertainity. There is no point looking at 80% drawdown AAPL had during 1990s. More approriate to look at it post 2000s where it started making higher impact and growth.
Cumulative Percentage : When this is unchecked, percentage division shows 0-nth percentage instad of percentage ranges. For example this is how it looks on SPY:
We can see that SPY has remained within 6% from ATH for more than 50% of the time.
Hope this is helpful. Happy trading :)
PS: this can be used in conjunction with Drawdown-Price-vs-Fundamentals to pick value stocks at discounted price while also keeping an eye on range tendencies of it.
Thanks to @mattX5 for the ideas and discussion today :)
Drawdown - Price vs FundamentalsIn this study, we are trying to compare drawdown from ATH of price and fundamentals to understand if price drawdown is really justifyable or if this is the buying opportunity.
For example, NYSE:BABA in the chart below shows that price has come down by more than 50%. But, the fundamentals has not changed upto this extent.
This may be viewed as buying opportunity from the eyes of fundamental based trader.
Similarly NYSE:LPX is trading at 15% below ATH whereas fundamentals are at peak. This again can be considered as buying opportunity.
NASDAQ:AAPL on the other hand is trading almost near ATH whereas fundamentals are having higher drawdown.
Well, this is just one factor to consider. I am about to release another script which can demonstrate amount of time (in terms of percentage) instrument trades at certain drawdown range. This looks something like this:
These two scripts can be used in conjunction to define your fundamental based trade.
I can add more funcamentals to the list. But, the higher value of fundamental should correlate to better position. Hence we cannot use things such as PE (which inversely correlates to value). Also need to keep the factor which includes total number of shares in it so that it is not affected by share dilution. Hence, have considered Total Revenue per Share instead of Total Revenue in this script.
Thanks to @mattX5 for suggesting fundamental based ideas in this line :)
Fundamnetals + Strength + RiskManagementCreated indicator to help investors by providing fundamental, technical and Risk Management information on screen for better decision making
you can see
Fundamentals
- Solvency,
- Liquidity
- Growth,
- Profitability
- Patrioski Score
- Altman Z-Score
Technicals
- MAs
- Oscillators
Risk Management
- Position Size
- Stop Loss
- Total Investment
Trading Rule #19This script is based on Trading Rule #19 from Chester Keltner's book How To Make Money On Commodities. It is best applied to candlestick charts with longer time frames and plans with minimal losses (i.e. swing trades). The rule is based on "Key" trend days (this is applied to daily charts in the book).
An initial Key-Up day is established on the third day of 3 consecutive new highs. Subsequent key-up days are determined as follows:
1. The first day following an initial key-up day trades 0.375% above the previous key-up day
2. The second day or any following day trades 0.125% above the previous key-up day
An initial Key-Down day is established on the third day of 3 consecutive new lows. Subsequent key-down days are determined as follows:
1. The first day following an initial key-up day trades 0.375% below the previous key-down day
2. The second day or any following day trades 0.125% below the previous key-down day
Green candles are considered up-trend, red candles are down-trend. Gray candles are undecided - when there is a new high and low in the same time frame, when there is no new high or low in that time frame, or the order price was cleared.
Order prices are represented as a blue line, with some days being "na" when order prices remain unchanged. On key-up days, orders are placed 0.375% below the low of the previous key-up day or the day previous (whichever is lower). Order prices on key-down days are placed 0.375% above the high of the previous key-down day or the day previous (whichever is higher).
The tolerance setting mainly effects the plot point of order price, at a certain point key-trend rules will take priority over order price (meaning if tolerance is high enough, order price will have no effect on determining key-trends).
Supertrend LSMA long StrategyThis is a long strategy which combines Super trend indicator with LSMA moving average.
In general it tends to works better with long trending markets such as stocks and cryptos using a big timeframe.
The rules are simple
Long entry:
Supertrend is telling us to go long and close of a candle is above moving average
Long exit:
Supertrend is telling us to go short
IF you have any questions, let me know !