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Trading Society: Pairs Trading with Hudson & Thames Quantitative Research Event Logo

Trading Society: Pairs Trading with Hudson & Thames Quantitative Research

by Trading Society


Mon, Jan 18, 2021

5:00 PM – 7:30 PM (GMT+0)

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Meeting ID: 852 9203 7535
Passcode: Pairstrad

Hudson and Thames Quantitative Research is a company with a focus on implementing the most cutting-edge algorithms in quantitative finance. Known for their MlFinLab package, with professionals such as Dr. Marcos Lopez de Prado - Co-founder and CIO at True Positive Technologies; Professor of Practice at Cornell University, Dr. Ernest Chan - Hedge Fund Manager at QTS & Author, and Dr. Thomas Raffinot - Lead Data Scientist at AXA Investment Managers providing praise on their work, this session will not be one to miss.

In this workshop they will be covering four topics:
  1. Distance Approach in Pairs Trading
    • From at least four distinct branches of research in the pairs trading filed, the distance approach papers are one of the most cited. The popularity of the approach is mainly contributed to its simplicity. The downside is, however, that the dependencies found by this approach may be spurious. We will cover the upsides of this approach and possible improvements to its caveats.
  2. Simulating Cointegrated Pairs and Minimum Profit Optimisation
    • Cointegration is one of the most important statistical arbitrage strategies for pairs and multi-asset trading. In this talk, I will cover the basic concepts of cointegration, the simulation of cointegrated pairs using stationary AR(1) process, the application of mean first-passage time of an AR(1) process to optimize cointegrated pairs trading boundaries and frequency, and the numerical algorithm to generate the trading signal.
  3. Introduction to Copula-Based Pairs Trading Strategy
    • The concept of copula has been widely used in risk management and CDO pricing from the 90s. However, applications for capturing pairs trading arbitrage is relatively novel. For this talk, we will go through the basic concepts of copula for pairs trading application, underlying assumptions, trading signal generation, and some common fallacies. We will cover two commonly adopted approaches: using prices series and returns series.
  4. Applying Machine Learning to Statistical Arbitrage
    • ​​​​​​​Classical statistical arbitrage research has grown quite generously in the past few years. Yet attempts to solutions using ML have been far and few between; this presentation will cover some of the latest approaches, key takeaways, and tips to avoid common pitfalls.​​​​​​​​​​​​​​

As well as giving Cass Business School students 2 months access to their ArbitrageLab.

Any queries please contact

Kind Regards, 
The Trading Society

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