Introduction to FinTech Using R

Description

R is a high-level statistical language and is widely used among statisticians and data miners to develop statistical applications. This complete hands-on course will help you code some finance and ML projects. In the first section of the course, you will learn some basic things to look at in money management, something very simple, something everybody knows and yet not many people start with. In the second section, you will look at stock market timing and focus on the coding aspect of how the algorithm is designed, then will land on the video on how to use the algorithm. We will also discuss soft thresholds and extend the market timing concept to a generalized framework. In the last section of the course, you will understand Asset Pricing. We will try to answer questions such as What is market beta? What is Capital Asset Pricing Model? Why do we pay attention to the market coefficient? How to construct an efficient portfolio? We will also look at the growth strategy. We will be looking at our data and every period we are going to pick a few TOP performing stocks by looking at the returns of these stocks within the period. In the next period, we are simply going to hold these stocks. By the end of the course, we are going to talk about how to build a web-based application so that we can come up with a software platform for clients to use. All resources and code files are placed here: https://github.com/PacktPublishing/Introduction-to-FinTech-Using-R

What You Will Learn

Learn how to time the stock market using probability theory
Explore the qualitative nature of stock market timing
Know the quantitative nature of stock market timing
Learn the basics of asset pricing theory
Learn the intermediate and advanced asset pricing practices
Build trade-able factor-based algorithms

Audience

This course is for financial and technology enthusiasts, beginners in programming, and people interested in statistics and data analysis. No programming experience is needed as you will learn everything from this course.

Approach

Each lecture is a live coding round in R directly and will help you get through the code block by block to explain each of the functionality.

Key Features

Understand the fundamentals of stock market timing * Fundamentals of asset pricing and building a tradeable factor-based algorithm from scratch * Get to know the most basic rules of thumb and intuition that every successful trader should know

Github Repo

https://github.com/PacktPublishing/Introduction-to-FinTech-Using-R

About the Author

Yiqiao Yin

Yiqiao Yin was a PhD student in statistics at Columbia University. He has a BA in mathematics and an MS in finance from the University of Rochester. He also has a wide range of research interests in representation learning: feature learning, deep learning, computer vision, and NLP. Yiqiao Yin is a senior data scientist at an S&P 500 company LabCorp, developing AI-driven solutions for drug diagnostics and development. He has held professional positions as an enterprise-level data scientist at EURO STOXX 50 company Bayer, a quantitative researcher at AQR working on alternative quantitative strategies to portfolio management and factor-based trading, and equity trader at T3 Trading on Wall Street.

Course Outline

1. Introduction

2. Stock Market Timing

3. Asset Pricing