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StockDistFit

The goal of StockDistFit is to provide functions that help in fitting probability distributions to financial data, specifically stock returns and prices. These functions can be used to compare the goodness of fit of different distributions and choose the most appropriate one, which can aid in making investment decisions or modeling financial phenomena. The package also includes function for cumulative wealth generated over time, given the initial wealth. Overall, StockDistFit aims to simplify the process of fitting and analyzing probability distributions for financial data.

Installation

You can install the development version of StockDistFit from GitHub with:

# install.packages("devtools")
devtools::install_github("njuguna-brian/StockDistFit")

Example

An example is the following

library(StockDistFit)
df <- asset_loader("path/to/data/folder", "AAPL", "Close")
df_returns <- weekly_return(df)

# Fit a normal Distribution to the Closing Price
norm_fit(df_returns)

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Version

Install

install.packages('StockDistFit')

Monthly Downloads

175

Version

1.0.0

License

GPL (>= 3)

Maintainer

Brian Njuguna

Last Published

May 9th, 2023

Functions in StockDistFit (1.0.0)

skew.normal_fit

Fit Skew Normal Distribution to a vector of returns/stock prices.

Fit a Symmetric Hyperbolic Distribution to a vector of return/stock prices.

Compute Weekly Returns of a Vector.

Fit Variance Gamma Distribution to a vector of return/stock prices.

Fit Student's t Distribution to a vector of returns/stock prices.

Compute Monthly Returns of a Vector.

Fit Symmetric Variance Gamma Distribution to a vector of returns/stock prices.

Compute Cumulative Returns of a Vector.

Load Asset Data.

Amazon.com Inc. Stock Prices Dataset

Fit Cauchy Distribution to a vector of returns/stock prices.

fit_multiple_dist

Fits Multiple Probability Distributions to several assets/stock prices.

Find the best distribution based on AIC values

Compute Annual Returns of a Vector.

Fit Normal Distribution to a Vector/stock prices.

Fit Normal Inverse Gaussian (NIG) Distribution to a vector of returns/stock prices.

Fit Skewed Generalized Error Distribution to a vector of returns/stock prices.

Fit Generalized Error Distribution to a vector of returns/stock prices.

Fit Generalized Hyperbolic Distribution to a vector of returns/stock prices.

Apple Inc. stock prices dataset

Tesla Inc. Stock Prices Dataset

Alphabet Inc Inc. Stock Prices Dataset

Fit Hyperbolic distribution to return/stock prices.

Fit Skewed Student-t Distribution to a vector of returns/stock prices.

Fit Symmetric Generalized Hyperbolic Distribution to returns/stock prices.