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Trading Alphas: Mining, Optimisation, and System Design

1904 Learners
15 Hours
Why should you choose micro alpha models over other trading strategies such as traditional factor models, risk-parity, or trend following? In short, these models, if built well, can provide better performance, stability, and risk management than other trading systems. In this course, you will learn where micro-alphas reside and how to write the most efficient codes to quickly analyse, backtest, optimise and go live with your trading strategy in the least amount of time possible.
Level
Advanced
Author
Dr. Thomas Starke
Price Lifetime Access Limited Time Offer

₹14300/-₹57199/-

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  • Live Trading
  • Learning Track
  • Prerequisites
  • Syllabus
  • About author
  • Testimonials
  • Faqs

Live Trading

  • Backtesting, adding stop-loss and profit-take using vectorised approach
  • Mining micro-alphas using trends, mean-reversion, correlation across assets, and cointegration
  • Metrics for analysing strategy which include total profit, sharpe ratio, sortino ratio, profit factor, drawdown, and profit per trade
  • Parameter optimisation using machine learning techniques such as clustering
  • Building a trading system from scratch
  • Explain software architecture, logging, storage, hardware, testing and version control
  • Brief study on execution models, implement parallel computing and describe different levels of logging
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Skills Covered

learning track 8

This course is a part of the Learning Track: Advanced Algorithmic Trading Strategies

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Need help? Write to us at quantra@quantinsti.com or call us at +91 8450963428.

Course Features

  • Community
    Community

    Faculty Support on Community

  • Interactive Coding Exercises
    Interactive Coding Exercises

    Interactive Coding Practice

  • Capstone Project
    Capstone Project

    Capstone Project Using Real Market Data

  • Trade & Learn Together
    Trade & Learn Together

    Trade and Learn Together

  • Get Certified
    Get Certified

    Get Certified

Prerequisites

Fluency with Python including python libraries like pandas, numpy, matplotlib and concepts of machine learning such as clustering, prediction, in-sample, out of sample and features. Working knowledge to place orders to buy and sell exchange traded assets.

Syllabus

about author

Dr. Thomas Starke
Dr. Thomas Starke
Dr Thomas Starke is the CEO of the financial consultancy firm AAAQuants. With a remarkable career spanning working with Boronia Capital, Vivienne Court Trading and Rolls-Royce, he has worked on the development of high-frequency stat-arb strategies for index futures and AI-based sentiment strategy. As an academic, he was a senior research fellow and lecturer at Oxford University. A tech aficionado, he takes a keen interest in new technologies such as AI, quantum computing and blockchain. He holds a PhD in Physics from Nottingham University (UK).
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    More in Less Time

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  • Expert Faculty
    Expert Faculty

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  • Self-paced
    Self-paced

    Learn at your own pace

  • Data & Strategy Models
    Data & Strategy Models

    Get data & strategy models to practice on your own

Faqs

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