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Model a Quantitative Trading Strategy in R

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10 Hours6 Videos74 Exercises5,268 Learners5400 XP

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Course Description

R is widely used by analysts and traders around the world to develop quantitative trading strategies that can be executed manually or through program trading. This is an introductory course for beginners in R to get familiar with quantitative trading strategies and coding technical indicators in R. You will learn technical terms associated with trading strategies, work with data.tables in R, and manipulate the input data to create trading signals and profit-and-loss columns. You will also learn about optimizing parameters to be able to maximize profits. This course is for everyone interested in getting started with algorithmic trading. No prior knowledge is required!
  1. 1

    Introduction to R for trading

    Free

    This chapter equips you with basic programming skills in R before proceeding to strategy writing. This chapter covers reading a data.table, creating new columns in the table, calculating returns by different methods, loop functions, conditional functions, and plotting of datasets.

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    Read file: read.csv()
    100 xp
    Get a glimpse of your data
    100 xp
    Types, Classes and Dimensions of Objects in R
    100 xp
    Extract data frame cell value
    50 xp
    Extract value of consecutive cells in a column
    50 xp
    Function c()
    100 xp
    Create a column using function c()
    100 xp
    Vector Operations
    50 xp
    Calculate returns: Get started
    100 xp
    Using the diff() function
    50 xp
    Calculate returns: Using c() and diff() together
    50 xp
    Calculate returns: For the second row
    100 xp
    Calculate returns: the general formula
    50 xp
    Calculate returns: vector division
    100 xp
    Calculate returns: for-loop
    100 xp
    Calculate log returns
    100 xp
    Plotting and interpreting charts
    50 xp
    Plot the Returns
    100 xp
    Conditional Statements
    50 xp
  2. 2

    Code a basic trading strategy

    Free

    In this chapter, you’ll learn how to write a simple strategy based on stock price movements, learn how to generate trading signals and how to determine the trading quantity and price to place orders. Finally, learn to assess your strategy based on the accrued profit and loss. Use R as a statistical tool to write your first fully functional programming code that performs these tasks automatically.

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    Introduction
    50 xp
    Using the current position counter
    50 xp
    Generate trading signal (1)
    50 xp
    Generate trading signal (2)
    50 xp
    Generating trading signal in actual table
    50 xp
    Output Variables
    50 xp
    Trading quantity & traded lots
    50 xp
    Calculate trading profit
    50 xp
    Mark to market
    50 xp
    Coding the strategy in R
    50 xp
    Load the data set
    100 xp
    Plot the data
    100 xp
    Initialize output variables
    100 xp
    Rows and iterations
    50 xp
    Define & initialize counters
    100 xp
    The for-loop
    100 xp
    The if condition for signal generation
    100 xp
    The if condition for buy or sell
    100 xp
    Update columns in case of buy
    100 xp
    Update columns in case of sell
    100 xp
    Last scenario: no change in trading position
    100 xp
    Formula for calculating the trading profit
    50 xp
    Formula for calculating the mark to market
    50 xp
    Calculate profit and mark to market
    100 xp
    Calculate traded lots
    100 xp
    Print profit & traded lots
    100 xp
    Run the complete code and report the results
    50 xp
  3. 3

    Create a technical indicator

    Free

    Apply the knowledge you’ve learned to create a more sophisticated trading strategy based on point and figure charting. By the end of this chapter, you will appreciate the complexities involved in creating quantitative trading strategies and will be equipped with the skills to write your own trading strategies in R.

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    Review of previous chapter
    50 xp
    Introduction to a new strategy
    50 xp
    Parameters and indicators in the new strategy
    50 xp
    Calculate box size in prices
    50 xp
    Calculate reversal size in prices
    50 xp
    Load and plot the dataset
    100 xp
    Initialize parameters
    100 xp
    Signal Generation Logic
    50 xp
    Practice benchmark calculation 1
    50 xp
    Practice signal generation 1
    50 xp
    Practice benchmark calculation 2
    50 xp
    Practice signal generation 2
    50 xp
    Logic for generating trading signal of buy
    50 xp
    Conditions for buying
    50 xp
    Conditions for selling
    50 xp
    Coding the strategy in R
    50 xp
    Initialize bench counter
    100 xp
    Initiate the for loop
    100 xp
    For loop: if condition for buy
    100 xp
    For loop: if condition for sell
    100 xp
    For loop: scenario of no change
    100 xp
    Review of the condition for changing benchmark
    50 xp
    Formula for changing benchmark
    50 xp
    For loop: updating the counter 'bench'
    100 xp
    Calculate the trade profit and the mark to market
    100 xp
    Mold your for-loop in a function
    100 xp
    Run the final code
    50 xp
    Optimize the input parameters
    50 xp
Quantinsti Faculty Headshot

Quantinsti Faculty

QuantInsti is one of Asia's pioneer Algorithm Trading Research and Training Institutes focused on preparing financial market professionals for the contemporary field of Algorithmic and High Frequency Trading. QuantInsti institute developed the curriculum for the Asia's first Executive Program in Algorithmic Trading (E-PAT) in 2009. As an initiative by financial markets professionals with stellar academic and professional credentials, the program aims to fulfill the pressing demands for highly specialized skill sets of a potentially lucrative domain. QuantInsti opened the doors to global participants in 2012 by introducing virtual classrooms for its flagship E-PAT course and have seen participation from all inhabited continents since then.
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