This repository will hold a host of analyses examining the statstical properties and structure of US equity returns and how they relate to a portfolio of assets.

1. Univariate Factor Analysis

2. Multivariate Factor Analysis

3. Time-Series Modeling

4. Growth Factor Exploration

5. This repository runs through a host of analyses examining the statstical properties and structure of US equity returns and how they relate to a portfolio of assets, starting with data collected during a machine learning analysis of US equities (Project 2). Unlike the rest of the projects outlined here, this repo will use strictly R code.

We begin by calculating the distribution of monthly returns for large-cap US equities and compare them to the normal and T distributions. Then we delve deeper into univariate factor analysis of returns bucketing data by factors that can be examined on the income statement, balance sheet, and cash flow statement. We then visualize the performance of these factors via returns, volatility, and sharpe ratio. Then we rank the factors that performed the best over the period of time the data was collected before finally looking at the correlation for top-performing factors.