课程

Introduction to R for Finance

基础技能水平

更新时间 2024年5月

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

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RApplied Finance

4小时

14 视频

61 道练习

5,200 XP

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课程描述

In this finance-oriented introduction to R, you will learn essential data structures such as lists and data frames and have the chance to apply that knowledge to real-world financial examples. By the end of the course, you will be comfortable with the basics of manipulating your data to perform financial analysis in R.

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1

The Basics

Get comfortable with the very basics of R and learn how to use it as a calculator. Also, create your first variables in R and explore some of the base data types such as numerics and characters.

Welcome to Introduction to R for Finance!

Your first R script

Arithmetic in R (1)

Arithmetic in R (2)

Assignment and variables (1)

Assignment and variables (2)

Financial returns

Financial returns (1)

Financial returns (2)

Basic data types

Data type exploration

What's that data type?

2

Vectors and Matrices

In this chapter, you will learn all about vectors and matrices using historical stock prices for companies like Apple and IBM. You will then be able to feel confident creating, naming, manipulating, and selecting from vectors and matrices.

What is a vector?

Vector names()

Visualize your vector

Vector manipulation

Weighted average (1)

Weighted average (2)

Weighted average (3)

Vector subsetting

Matrix - a 2D vector

Create a matrix!

Matrix <- bind vectors

Visualize your matrix

cor()relation

Matrix subsetting

3

Data Frames

Arguably the most important data structure in R, the data frame is what most of your data will take the form of. It combines the structure of a matrix with the flexibility of having different types of data in each column.

What is a data frame?

Create your first data.frame()

What goes in a data frame?

Making head()s and tail()s of your data with some str()ucture

Naming your columns / rows

Data frame manipulation

Accessing and subsetting data frames (1)

Accessing and subsetting data frames (2)

Accessing and subsetting data frames (3)

Adding new columns

Present value

Present value of projected cash flows (1)

Present value of projected cash flows (2)

4

Factors

Questions with answers that fall into a limited number of categories can be classified as factors. In this chapter, you will use bond credit ratings to learn all about creating, ordering, and subsetting factors.

What is a factor?

Create a factor

Factor levels

Factor summary

Visualize your factor

Bucketing a numeric variable into a factor

Ordering and subsetting factors

Create an ordered factor

Subsetting a factor

5

Lists

Wouldn't it be nice if there was a way to hold related vectors, matrices, or data frames together in R? In this final chapter, you will explore lists and many of their interesting features by building a small portfolio of stocks.

What is a list?

Create a list

Named lists

Access elements in a list

Adding to a list

Removing from a list

A few list creating functions

Split-Apply-Combine

Congratulations!

Introduction to R for Finance

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