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Course Outline

Introduction

Setting Up the IDE (Integrated Development Environment)

  • RStudio

R Programming Fundamentals

  • R objects: vectors, matrices, arrays, data frames, and lists
  • Control flow: branching, looping, and logical testing

Accessing Data with R

  • Reading and writing CSV data
  • Connecting to SQL databases

Visualizing Data with R

  • Creating plots with R

Analyzing Data with R

  • Data frame manipulation
  • Descriptive statistics

Inference and Time Series Analysis

  • Analyzing time series data in financial markets
  • Volatility modeling for high-frequency financial data

Simulating Asset Price Trajectories

  • Monte Carlo simulation

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset allocation, and risk assessment
  • Regression analysis

Risk Analysis and Investment Performance

  • Defining and solving portfolio optimization problems
  • Value at Risk (VaR) and Expected Shortfall (ES)

Fixed-Income Analysis and Option Pricing

  • Conducting fixed-income analysis and option pricing

Deploying Your R Application to Production

  • Integrating your application with Excel and other web-based tools

Application Performance

  • Optimizing application efficiency
  • Parallel processing with R

Troubleshooting

Closing Remarks

Requirements

  • A foundational understanding of finance (e.g., securities, derivatives)
  • A strong command of mathematics
  • Programming experience in any language is beneficial but not mandatory
 28 Hours

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