Fit Stock Price Distributions

The 'StockDistFit' package provides functions for fitting probability distributions to stock price data. The package uses maximum likelihood estimation to find the best-fitting distribution for a given stock. It also offers a function to fit several distributions to one or more assets and compare the distribution with the Akaike Information Criterion (AIC) and then pick the best distribution. References are as follows: Siew et al. (2008) < https://www.jstage.jst.go.jp/article/jappstat/37/1/37_1_1/_pdf/-char/ja> and Benth et al. (2008) < https://books.google.co.ke/books?hl=en&lr=&id=MHNpDQAAQBAJ&oi=fnd&pg=PR7&dq=Stochastic+modeling+of+commodity+prices+using+the+Variance+Gamma+(VG)+model.+&ots=YNIL2QmEYg&sig=XZtGU0lp4oqXHVyPZ-O8x5i7N3w&redir_esc=y#v=onepage&q&f=false>.

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)