Dates and Locations

25 & 26 Nov '10	London, UK	Apex City of London Hotel >>
e-learning		Further details

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Course Outline: Pair Trading & Related Strategies

This two day workshop introduces delegates to pairs trading and related strategies, with particular reference to research, testing and implementation. Relevant software (MATLAB) will be used throughout the workshop to illustrate examples and to help students practice the essential steps in developing a pairs trading strategy. No prior knowledge of MATLAB is required. (Note: Students will be able to apply the principles learnt during the workshop, regardless of which software they choose to use thereafter).

Overview
- Stationarity, cointegration, and mean reversion
- Pair trading in stocks, ETF's, futures, and currencies
- Beyond trading pairs: trading stock baskets against index and other statistical arbitrage strategies

Brief Tutorial to MATLAB: The Essentials
- Why MATLAB and what are the alternatives?
- Exercises: building some utilities for trading and plotting simple graphs
- Using toolboxes
- Freeware: Spatial-econometrics.com

Basic Concepts in Pairs Trading
Stationarity of a time series:
a) Concept of stationarity, and why is it useful
b) Statistical test for stationarity
c) Exercise: Using MATLAB and spatial-econometrics toolbox to find out if CADAUD is stationary
d) Exercise: if CADAUD is stationary, backtest a possible trading strategy
e) Exercise: Find out if EURGBP is stationary

Cointegration of 2 time series:
a) Concept of cointegration, and why is it useful
b) Statistical test for cointegration
c) Exercise: Find out if GLD-GDX is cointegrating
d) Exercise: Find out if IGE-EWC is cointegrating
e) Exercise: Building and backtesting a simple Bollinger-band pair trading strategy on IGE-EWC

Calculating the half-life for mean-reversion:
a) How long is the expected holding period for a mean-reversion trade?
b) Why is computing half-life better than computing average holding period?
c) Using Ornstein-Uhlenbeck formula to determine half-life
d) Exercise: Compute the half-life of mean-reversion for IGE-EWC

Practical Aspects of Pairs Trading
The pitfalls of cointegration analysis

Is cointegration necessary for pairs trading?:
a) There are cases where 2 instruments are not cointegrated over long time-scale, but nevertheless mean-revert under certain situations;
b) Mean reversion may depend on time of day, or day of week, or day of month -- seasonal effects;
c) Mean-reversion may depend on trading horizon

"Parameterless" pairs trading strategies:
a) A way to "pyramid" or "layer" your pairs positions

What about stop losses?

Pairs trading stocks, ETFs, and futures:
a) Which is the best market?;
b) The pitfalls of each market and some ways to avoid them

High-frequency pairs trading:
a) Divergence between backtest and reality;
b) Exercise: backtesting a high frequency calendar spread strategy;
c) Exercise: building a automated trading program for calendar spread strategy;

Beyond Trading Pairs
- Trading an ETF against a subset of its component stocks
- Exercise: Construct a trading model of XLE against its components
- Statistical arbitrage: picking two subsets of stocks from an index & trading them against each other
- Exercise: Constructing a market neutral statistical arbitrage strategy

Conclusion
- Mean-reversion vs. momentum strategies: why focus on the former?
- Cointegration and mean-reversion: related, but neither necessary nor sufficient
- Different ways to construct mean-reverting portfolios
- Software for download, books and articles for references