Cursos de R Programming for Finance

Nossos Clientes

Código do Curso

rforfinance

Duration

28 hours (usually 4 days including breaks)

Requisitos

  • An understanding of finance (securities, derivatives, etc.)
  • A solid grasp of mathematics
  • Programming experience in any language is helpful but not required

Overview

R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems.

In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems.

By the end of this training, participants will be able to:

  • Understand the fundamentals of the R programming language
  • Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
  • Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
  • Troubleshoot, integrate deploy and optimize an R application

Audience

  • Developers
  • Analysts
  • Quants

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Note

  • This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.

Programa do Curso

Introduction

Setting up the IDE (Integrated Development Environment)

  • RStudio

R Programming Fundamentals

  • R objects: vectors, matrices, arrays, data frames and lists
  • Flow control: branching, looping and truth testing

Accessing Data with R

  • Reading and writing CSV data
  • Accessing data in an SQL database

Visualizing Data with R

  • Plotting with R

Analyzing Data 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

  • Performing 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

  • Performing fixed-income analysis and option pricing

Taking Your R Application into Production

  • Integrating your application with Excel and other web applications

Application Performance

  • Optimizing your application
  • R multiprocessing

Troubleshooting

Closing Remarks

Declaração de Clientes

★★★★★
★★★★★

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