Download The Book: The Definitive Guide to Pairs Trading
First, we need to start with a definition of statistical arbitrage and pairs trading. Often people will use these two terms interchangeably, however, pairs trading is a subset of statistical arbitrage and so we can say that all pairs trading is statistical arbitrage but not all statistical arbitrage is pairs trading.
Statistical arbitrage is typically broken down into factor investing and the mean-reverting portfolios of pairs trading. We should add that in its simplest form pairs trading refers to trading only 2 assets but it can be extended to an n-dimensional mean reverting portfolio.
There is no single agreed-upon definition in the literature with each author bringing their own take, so we took it upon ourselves to formalize it as follows:
“Pairs trading is an approach that takes advantage of the mispricing between two (or more) co-moving assets, by taking a long position in one(many) and shorting the other(s), betting that the relationship will hold and that prices will converge back to an equilibrium level”
The intuition behind pairs trading goes back to the fundamental principle of investing: “buy undervalued – and sell overvalued”. However, to determine if the asset is truly over or undervalued, we need to know the intrinsic value, which is at best an approximation and largely what value investing sets out to do.
Statistical arbitrage and pairs trading tries to solve this problem using price relativity. If two assets share the same characteristics and risk exposures, then we can assume that their behavior would be similar as well. This has the benefit of not having to estimate the intrinsic value of an asset but rather just if it is under or overvalued relative to a peer(s). We only have to focus on the relationship between the two, and if the spread happens to widen, it could be that one of the securities is overpriced, the other is underpriced, or the mispricing is a combination of both.
In this case, we are able to take advantage by selling the higher-priced security and buying the lower-priced one, expecting the mispricing to naturally correct itself in the future as prices converge to the equilibrium level.
The example below shows the relationship between AME and DOV, notice how the spread is stationary enough for entry and exit positions to be taken and profits to be made.
The mutual mispricing between the two assets is represented by the value of the spread. The greater the price difference from 0 and hence the spread, the greater the profit potential. One of the best qualities of pairs trading is market-neutrality, as by adjusting the hedge ratio of the spread it can be constructed to have a beta that is negligible, and therefore minimise the exposure to the market.
Pairs trading strategies usually vary in two ways: the way of detecting the “co-moving” pairs and the logic behind the trading rules. We dive into this topic in “A Taxonomy of Pairs Trading Strategies“.
PAIRS TRADING LECTURES SERIES
PAIRS TRADING LECTURES SERIES
Previously we’ve discussed the “what’s” and “why’s” of pairs trading. Now it’s time to move on to the question of “where?”. Where do we apply pairs trading strategies? Building a strategy starts with pair selection, so our desire to choose the best market for it is only natural.
Since pairs trading bears its roots in equity markets, it usually serves as the first pick by most traders, this is largely due to the high number of possible combination pairs. However, asset classes such as commodities, forex, or even crypto have numerous supporting studies on the profitability of statistical arbitrage. Some have been around since 1990, as is the case for commodities futures; some are more recent, like crypto markets, however, they all support the universality of statistical arbitrage.
The requirement of “price co-movement” and “short-term price inefficiency” can be applied to every conceivable type of asset. Whether it’s ETFs or options, if the market exhibits the violation of the “Law of One Price”, statistical arbitrage will thrive.
With every market and every asset at our disposal, we need to be aware of the nuances that come with given asset types and how they influence our approach to strategy creation.
Let’s take a deeper look into the taxonomy of pairs trading strategies.