Our first white papers deal with the subject of systematic trading. The papers discuss different approaches to the topic, present specific trading strategies and introduce associated risk management techniques:
An Introduction to Algorithmic Trading – course taught at IE Business School in Madrid:
Session 1: Introduction
This lecture introduces basic concepts of trading.
Session 2: Success and Risk Factors of Quantitative Trading Strategies
This lecture analyzes which factors drive the performance of quantitative trading strategies and introduces important risk factors to judge downside risk.
Sessions 3 – 6: Trade Signal Generation
These lecturess introduce techniques to decide when and how to trade.
- Algo Trading Intro – Session 3
- Algo Trading Intro – Session 4
- Algo Trading Intro – Session 5
- Algo Trading Intro – Session 6
Sessions 7 – 9: Trade Implementation
These lectures explain how to size and execute entry and exit orders.
Session 10: Performance Measurement
This lecture covers basic performance measurement ratios.
Session 11 & 12: Performance Analysis
These lectures cover various concepts to judge quantitative trading strategies. Metrics covered
include return, risk, efficiency, trade frequency and leverage.
EVOLUTIQ’s Pred-X model is built upon doctoral research on the applicability of ensemble methods to enhance option pricing models based on Lévy processes conducted by Oliver Steinki and was further enhanced by Peter Miko’s research in artificial intelligence. Their doctoral research can be found here:
- Oliver’s doctoral thesis: “An Investigation of Ensemble Methods to Improve the Bias and/or Variance of Option Pricing Models based on Lévy Processes“
- Peter’s doctoral thesis: “The closed form solution of the inverse kinematic problem of 3R positioning manipulators“