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5 - FNB - Finance and Banking

FNB 138 - Quantitative Trading Analysis with R

Code Start Date Duration Venue
FNB 138 29 July 2024 5 Days Istanbul Registration Form Link
FNB 138 26 August 2024 5 Days Istanbul Registration Form Link
FNB 138 23 September 2024 5 Days Istanbul Registration Form Link
FNB 138 21 October 2024 5 Days Istanbul Registration Form Link
FNB 138 18 November 2024 5 Days Istanbul Registration Form Link
FNB 138 16 December 2024 5 Days Istanbul Registration Form Link
Please contact us for fees


Course Description

Quantitative Trading Analysis with R offers course attendees a glimpse into the daily activities of quants/traders who deal with financial data analysis and the formulation of model-driven trading strategies. This training programme illuminates many of the problems that professionals encounter on a daily basis. Answers to some of the more relevant questions are provided, and the easy-to-follow examples show the participants how to build functional R computer code in the process. Anyone interested in applying programming, mathematical, and financial concepts to the creation and analysis of simple trading strategies will benefit from the content provided in this training. Quantitative Trading Analysis with R focuses on helping participants achieve practical competency in utilizing the popular R language for data exploration and strategy development. Training programme outlines basic trading concepts and walks the reader through the necessary math, data analysis, finance, and programming that quants/traders rely on. 

Course Objectives

  • Evaluate simulated strategy historical risk adjusted performance 
  • Calculate main trading statistics 
  • Measure principal strategy performance metrics 
  • Estimate key risk management metrics 
  • Maximize historical risk adjusted performance by optimizing strategy parameters through an exhaustive grid search of all indicators parameters combinations.
  • Minimize optimization over-fitting or data snooping 

Who Should Attend?

  • Financial Investors and Traders
  • Financial Quantitative Professionals
  • Finance professional or academic researcher who wishes to deepen their knowledge in quantitative finance.

Course Details/Schedule

Day 1

  • Installing Technical Analysis library for R
  • Loading Historical Data (Input)
  • Obtaining Stock Prices Data using Quantmod
  • Graphical Analysis using GGPlot2
  • Adding Technical Indicators on the Original Plot

Day 2

  • Calculating Technical Indicators
  • Moving Averages
  • Simple
  • Exponential
  • Weighted
  • Double-Exponential
  • Bollinger Bands
  • RSI – Relative Strength Indicator
  • MACD

Day 3

  • Trading Strategy Implementation
  • Trend-Following
  • Mean-Reversion
  • Strategy Indicators
  • Strategy Signals
  • Strategy Rules
  • Strategy Application

Day 4

  • Strategy Reporting
  • Trend-Following
  • Mean-Reversion
  • Trading Statistics
  • Performance Metrics
  • Risk Management Metrics
  • Introduction to Strategy Parameters Optimization

Day 5

  • Other Trading Strategies
  • Momentum
  • Directional
  • Distance
  • Correlation
  • Co-Integration Based
  • Introduction to Machine Learning for Algorithmic Trading