Stock pair trading is a popular strategy among algorithmic traders. It involves identifying two stocks that have a historical relationship and trading the pair long/short based on the deviation from this historical relationship. The idea is to buy long the underperformer in the pair and sell short the overperformer once their relative performances have diverged. The trader profits if this relative performance re-converges. In this blog post, we will discuss two statistical approaches used in stock pair trading: the copula method and the cointegration method.
The Copula MethodThe copula method involves modeling the marginal distributions of the two stocks separately and then using a copula function to model the dependence structure between them.
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