Statistics and Financial Data Analysis

Introduction

This document represents group project work for course in Statistics and Financial Data Analysis for advanced degree Masters in Computational Finance, Union University.

Professor: Prof. Milan Nedeljkovic, PhD

Students:

• Nikola Krivacevic
• Aleksandar Milinkovic
• Milos Milunovic

MSFT stock returns forecasting

The goal of the project is to perform all steps/elements of the empirical analysis with financial/economic data, with the goal to produce useful forecasts. The project is organized in several phases and multiple steps within each phase.

The whole data analysis, visualization, statistical tests, forecasting and valuation done in R programming language. Project code is organized across multiple directories, in R Notebooks. One convenient thing with R notebooks is that you can generate various output formats, html including, which can be deployed to the RPubs from RStudio.

All the notebooks, used in the project, are organized according to the several phases for forecasting and are deployed to the RPubs.

Project phases:

Each of the project phases has detailed description of all the steps, implementation details, intuition for modeling, interpretation of data analysis, modeling, evaluation and statistical test that were performed.

• Data collection
• Data analysis
• Building univariate time series model for forecast
• Building multivariate model for forecast
• Building volatility model