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Welcome to the stockanalytics wiki!
- Default R script:
mean(x) - Advanced R script:
apply(x,2, function(col) mean(col))
- Default R script:
median(x)orquantile(x, 0.5) - Advanced R script:
apply(x,2, function(col) mean(col))orapply(x, 2, function(col) quantile(col, 0.5))
Rarely used in Finance, but can be referred as the 'height' of distribution, representing the most frequent observation value.
- Default R script:
mode(x)
- Default R script:
sd() - Advanced R script:
apply(x,2, function(col) sd(col))
Shows how distribution is skewed. It depends on the value that further located from the mode: further minimum value states that distribution is negatively skewed whereas further maximum values demonstrates positively skewed distribution.
- Default R script:
skewness() - fBasics library:
colSkewness() - Advanced R script:
apply(x,2, function(col) skewness(col))
Measures peakedness of the distribution.
- Default R script:
kurtosis() - fBasics library:
colKurtosis() - Advanced R script:
apply(x,2, function(col) kurtosis(col))
Default R script enables to calculate statistical measures only for one array or matrix column. To overcome limitation is possible thanks to two options: either downloading package or using apply()
R code: cor()
Regression is a great tool to find which factors indeed have an impact on dependent variable and forecast possible change. For example, how will change Oil Company price if WTI or Brent goes up. Default script enables to change variables manually when experienced econometrician would prefer packages like MuMIn, which facilitates selection of valid variables.
• Default R script: summary(lm(formula = y ~ x)
• R script for MuMIn package: full.model <- lm(Portfolio ~ GC.F + BZ.F + HG.F + SI.F, reg_df) dredge(full.model)
Mostly used by economists.
- R script:
jarqueberaTest()orjbTest()
- R script:
shapiroTest() - My R script: https://github.com/vladislavpyatnitskiy/stockanalytics/blob/main/Normality%20Tests/Shapiro-Wilk%20Test.R
Often used in Life Sciences.
- R script:
ksnormTest()
Here are represented scripts to calculate ratios that enable to assess performance of the financial instruments.
The most popular ratio to assess asset and portfolio performance. It is a ratio of market premium (Rp - Rf, difference between asset/portfolio return and risk free rate) and standard deviation of the asset/portfolio. The higher Sharpe, the better the performance has been for the selected period.
Alternative to Sharpe ratio, where denominator is beta of the asset/portfolio.
The drawback of the ratio is the unsuitability for assets with negative beta coefficient to market as it makes their values ambiguous to interpret. Meanwhile, values of the Sharpe's standard deviation can never be negative.
The least popular ratio due to its complexity to calculate.
Würtz, D. et al. (2014) Basic R for Finance. publication. Zurich: Finance Online GmbH, pp. 186.
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