CHAPTER 7Special Topics in Quantitative Trading
The first six chapters of this book covered most of the basic knowledge needed to research, develop, and execute your own quantitative strategy. This chapter explains important themes in quantitative trading in more detail. These themes form the bases of statistical arbitrage trading, and most quantitative traders are conversant in some if not most of these topics. They are also very helpful in informing our intuition about trading.
I will describe the two basic categories of trading strategies: mean-reverting versus momentum strategies. Periods of mean-reverting and trending behaviors are examples of what some traders call regimes, and the different regimes require different strategies, or at least different parameters of the same strategy. Mean-reverting strategies derive their mathematical justification from the concepts of stationarity and cointegration of time series, which I will cover next. Following that, I will discuss a novel application of machine learning to adapt the parameters of a trading strategy to different regimes that we call Conditional Parameter Optimization (CPO). Then I will describe a theory that many hedge funds use to manage large portfolios and one that has caused much turmoil in their performances: namely, factor models. Other categories of strategies that traders frequently discuss are seasonal trading and high-frequency strategies. All trading strategies require a way to exit their positions; I will ...
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