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Course Outline

Introduction

Setting up the Integrated Development Environment (IDE)

  • RStudio

Fundamentals of R Programming

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

Data Access with R

  • Reading and writing CSV files
  • Accessing data in SQL databases

Data Visualization with R

  • Creating plots with R

Data Analysis with R

  • Manipulating data frames
  • 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

  • Capital allocation, asset allocation, and risk assessment
  • Regression analysis

Risk Analysis and Investment Performance

  • Defining and solving portfolio optimization problems
  • VaR and 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 your application
  • R multiprocessing

Troubleshooting

Closing Remarks

Requirements

  • Foundational knowledge of finance concepts (securities, derivatives, etc.)
  • A strong understanding of mathematics
  • Programming experience is beneficial but not mandatory
 28 Hours

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