Intermediate R for Finance培训

课程编码

intermediaterforfinance

课程时长

21 小时 通常来说是3天,包括中间休息。

要求

  • Experience in basics of R programming
  • A basic understanding of finance concepts

课程概览

R是金融行业中流行的编程语言。它用于从核心交易程序到风险管理系统的金融应用程序。

在这个以讲师为主导的现场培训中,参与者将学习R中的高级编程概念,因为他们使用财务示例在R中进行编码。

在培训结束时,参与者将能够:

  • 实现高级R编程技术
  • 使用R操纵其数据以执行更高级的财务操作

听众

  • 程序员
  • Finance专业人士
  • IT专业人士

课程形式

  • 部分讲座,部分讨论,练习和繁重的实践练习

Machine Translated

课程大纲

Introduction

Refresher on R Programming Basics

Creating Dates and Times in R

  • Overview of Data Classes for Dates and Times
  • Exploring Your First Date and Time Objects
  • Creating Dates from Character Strings
  • Using Vectors to Create Multiple Dates from Character Strings
  • Specifying Date Formats
  • Converting Between Date Formats
  • Getting Time Intervals Between Dates
  • Extracting Date Components Using Functions

Using If Statements and Operators in R

  • Overview of the Exercise: Creating a Program for Buying or Selling Stocks
  • Using Relational Operators
  • Comparing Vectors Using Relational Operators
  • Using Logical Operators
    • Implementing And/Or
    • Implementing Not
    • Using Subsets with Data Frames and Logical Operators
  • Hands On: Creating Your Stocks Program by Combining Relational and Logical Operators
  • Using If Statements
    • Exploring the Basic If Structure
    • Implementing If-Else Statements
    • Implementing Nested If Statements
    • Using the ifelse() Function

Implementing Loops in R

  • Implementing Repeat Loops Using Stock Prices Example
  • Implementing Break Points
  • Implementing While Loops Using Debt Example
    • Using While Loops with Printing Function
    • Creating Plots Using While Loops
    • Using Break and If Statements in While Loops
  • Implementing For Loops Using Stocks Example
    • Looping Over Vectors
    • Looping Over Data Frame Rows
    • Looping Over Matrix Elements
    • Using Break and Next

Implementing Functions in R

  • Overview of Functions
  • Getting Help with Functions and Reading Documentations
  • Using Arguments and Optional Arguments
  • Implementing Nested Functions
  • Creating Your First Function: Turning Percentage into a Decimal
  • Implementing Multiple Arguments in Your Custom Function
  • Creating a Function to Calculate Present Value
  • Understanding Function Scoping
  • Introduction to Packages Using tidyquant

Using Apply Functions in R

  • Using Apply Functions to Perform Complicated Calculations
  • Implementing lapply() on a List
  • Implementing lapply() on a Data Frame Using Sharpe Ratio Example
  • Using FUN Arguments in lapply() to Improve the Sharpe Ratio Function
  • Using sapply() to Simplify Apply
  • Exercise: Examining a Sample Program on the Stock Market Crash List
  • Using vapply() and FUN.VALUE
  • Using Anonymous Functions

Troubleshooting

Summary & Conclusion

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