Coding for Finance

Quantitative Finance with R

Quantitative Finance with R

Presented by: Marco Neffelli and Omar Bazara
Learn portfolio optimization, asset pricing, and risk management with R.
AboutTutor(s)BreakdownKey Info

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.

What you’ll 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

Marco Neffelli headshot

Marco Neffelli is a Ph.D. candidate in Economics at the University of Genova, Italy. His main research revolves around Quantitative Finance and Financial Econometrics. He is a lecturer for the course Quantitative Finance with R at the University of Pavia, Italy. His background includes an MSc in Quantitative Finance from Cass Business School, London.

- More about Marco Neffelli

Omar Bazara headshot

Omar Bazara holds a Master’s degree in financial mathematics from Cass Business School, City University of London. Omar is a portfolio valuation analyst at IHS Markit, London. He is specialized in Credit Derivatives and working alongside a variety of different asset classes.

- More about Omar Bazara

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 Quantmod
  • 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 and Return with Modern Portfolio 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)

  • R Warm-Up Introduction to Performance Analytics
  • Idiosyncratic versus Systematic Risk
  • Risk Factors
  • The CAPM
  • Fama-French and Other Factor Models
  • Getting Practical – Empirical Testing of the CAPM

Manage Risk 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

Cost: £59.99

Duration: 4

This course expects viewers to have some basic knowledge of financial markets and a good understanding of R programming. However, they need not have any knowledge of quantitative finance or working with financial data.

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