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Quantitative financial modeling made easy with R
With the ever-changing financial environment in the global market, investment banks, hedge funds, and private equity firms are always on the lookout for professionals able to identify profitable investment opportunities and manage risk. If you are interested in Quantitative Finance, especially in modern portfolio theory and risk management, then this is the perfect course for you.
Solving complex quantitative finance tasks becomes much easier with hands-on coding implementations. This course mixes important theoretical steps in a practical way to enhance your financial IQ in your day-to-day activities.
By the end of the course, you’ll be comfortable using R and its associated libraries to solve any problem associated with Quantitative Finance without getting stressed; in short, you’ll be solving the complex challenges that portfolio and risk managers face every day.
This course mixes key theoretical aspects of quantitative finance with practical explanations and implementations in R. Each section is made up of these two elements, which are deeply interrelated and ultimately inseparable. A series of exercises helps the user succeed and overcome obstacles in the learning process.
What You Will Learn
- A solid understanding of how to analyze—with a quantitative mindset—the most important financial products such as equities, derivatives, and bonds
- Use statistical analysis to find hidden insights into financial data used in financial models and strategies
- Diversify your portfolio with hedging and eliminate unwanted risk during times of market volatility
- Price any financial instrument
- Go safe with fixed income securities by exploring the bond market
- Analyze financial assets to find their Return On Investment (ROI)
- Gain an in-depth understanding of Markowitz’s modern portfolio theory and the ability of applying it using real data with R
- Build your own profit-making strategy with advanced financial techniques to measure, predict and manage risk
Table of Contents
FIRST THINGS FIRST!
The Course Overview
Fundamentals of Quantitative Finance
R Functions and Packages
DATA ANALYSIS WITH R
R Warm-Up – Introduction to Quantmod
Equity – Definitions and Price Download
Modeling Prices and Returns
Asset Returns Simulation
Getting Practical – Financial Modeling with R: S&P500 Statistical Analysis
STAYING SECURED WITH FIXED-INCOME SECURITIES
R Warm-Up – Introduction to jrvFinance
Introduction to Fixed-Income Securities
The Importance of Interest Rate
Pricing of Fixed-Income Securities
Duration, Modified Duration, and Convexity
Getting Practical – The Yield Curve and the Bootstrapping Approach
DERIVATIVES FOR RISK MANAGEMENT
R Warm-Up – Introduction to fOptions
Working with Futures
European and American Options
Pricing European Options – The Binomial Model
Getting Practical – Pricing European Options with the Black-Scholes Model
ANALYSING RISK/RETURN WITH MODERN PORTFOLIO THEORY TECHNIQUES
R Warm-Up – Introduction to PortfolioAnalytics
The Benefits of Diversification
Risk/Return Paradigm
Capital Allocation Line and Capital Market Line
Getting Practical – Optimal Asset Allocation with Markowitz Framework
THE CAPITAL ASSET PRICING MODEL – CAPM MODEL
R Warm-Up –Introduction to PerformanceAnalytics
Idiosyncratic versus Systematic Risk
Risk Factors
The CAPM
Fama-French and Other Factor Models
Getting Practical – Empirical Testing of the CAPM
MANAGE RISKS AND SAFEGUARD PROFITS WITH PORTFOLIO RISK MANAGEMENT
R Warm-Up– PerformanceAnalytics for Risk Management
The Value-at-Risk (VaR) Model
The Expected Shortfall (ES)
Benefits and Pitfalls of VaR Approach
Getting Practical – Hedging Financial Exposure
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