Book Image

Learning Quantitative Finance with R

By : Dr. Param Jeet, PRASHANT VATS
Book Image

Learning Quantitative Finance with R

By: Dr. Param Jeet, PRASHANT VATS

Overview of this book

The role of a quantitative analyst is very challenging, yet lucrative, so there is a lot of competition for the role in top-tier organizations and investment banks. This book is your go-to resource if you want to equip yourself with the skills required to tackle any real-world problem in quantitative finance using the popular R programming language. You'll start by getting an understanding of the basics of R and its relevance in the field of quantitative finance. Once you've built this foundation, we'll dive into the practicalities of building financial models in R. This will help you have a fair understanding of the topics as well as their implementation, as the authors have presented some use cases along with examples that are easy to understand and correlate. We'll also look at risk management and optimization techniques for algorithmic trading. Finally, the book will explain some advanced concepts, such as trading using machine learning, optimizations, exotic options, and hedging. By the end of this book, you will have a firm grasp of the techniques required to implement basic quantitative finance models in R.
Table of Contents (16 chapters)
Learning Quantitative Finance with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Market risk


The risk for an investor to encounter losses due to changes in overall performance of the market in which he has invested, is known as market risk. Market risk is a kind of systematic risk which cannot be tackled with diversification. It may be hedged. The risks happening due to recessions, political instability, interest rate changes, natural disasters, and terrorist attacks are examples of market risks. Market risks are measured differently for banks, individual stocks, portfolios, and so on.

Let us consider how market risks are measured for individual securities. The market risk of a stock which is a part of a portfolio is measured as the contribution of a security in the overall risk of the portfolio. The individual stock risk is measured by the beta coefficient, which is the volatility of stock with respect to the market.

Let us run regression analysis on stock IBM as dependent variable and GPSC index as the independent variable and try to estimate the beta. It can be done...