[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 PulseWire official Altman Z-Score Indicator.
Feedbacks are appreciated. Indicator
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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. Library
Indicator
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. Indicator
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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 :) Indicator
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