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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)
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))
Comparing to previous statistical measures, skewness can be applied to only one set at the time. However, this functional limitation is possible to overcome without any libraries using apply()
. Otherwise, try timeSeries library with colSkewness()
.
- Default R script:
skewness()
- fBasics library:
colSkewness()
- Advanced R script:
apply(x,2, function(col) skewness(col))
Same story as with Skewness.
- Default R script:
kurtosis()
- fBasics library:
colKurtosis()
- Advanced R script:
apply(x,2, function(col) kurtosis(col))
R code: cor()
R code: summary(lm(formula = y ~ x)
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.
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