(Click Category to List Courses)
5 - FNB - Finance and Banking
FNB 138 - Quantitative Trading Analysis with R
| Code | Start Date | Duration | Venue | |
|---|---|---|---|---|
| FNB 138 | 22 April 2024 | 5 Days | Istanbul | Registration Form Link |
| FNB 138 | 06 May 2024 | 5 Days | Istanbul | Registration Form Link |
| FNB 138 | 03 June 2024 | 5 Days | Istanbul | Registration Form Link |
| 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 |
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
