Why Pairs Trading?

Trying to pick which way the market is heading is a fools game. Unless you have superior knowledge of future events, policies, economic data, scandals, or whatever might move the market in the future, then you are simply guessing which way the market will move. If you do have such knowledge, then you mnake get indicted for insider trading.

Basing your trading on indicators that evaluate historical price action is equally idiotic. It’s a flawed premise that you can predict the future based on things that happened in the past. The past has nothing to do with the future. Sure, you can ride an ethereal  momentum wave or draw imaginary lines on a chart and pretend the market will obey them, but this has been proven to be a losers game, as 90% of all traders who practice such bunk lose money.

A better way would be to develop a model that has a sound basis in a mathematical proof, something that is independent of market direction, and relies on the fundamental relationships of the assets you want to trade. This is where pairs trading can help.

Pairs trading is simply a strategy where you go long one security and simultaneously go short another. Of course there needs to be a good reason for choosing the pair, and which one you’ll go long or short. You should choose a pair of assets that have some close binding relationship, and look for a break in that relationship that you can take advantage of. Generally, you short the overperforming asset, and go long the under performing after they have diverged from their normal state by some significant degree, and you make money as they move back to their current preferred or mean state.

If you use statistical measures to determine when this divergence is significant enought to enter a trade, and again to determine when a regression back to the mean signals taking profit, then you are employing a type of pairs trading called statistical arbitrage.

So why is this a sound way to trade?

The premise is that like assets, things that share many things such as similar or identical markets, have deep ties that cannot be easily broken. These ties could be the sharing of resources, markets, materials, processes, people…all kinds of things. And ocassionally the companies behind the assets may experience temporary disruptions for any number of reasons, causing their valuation to fluctuate. But the fundamental relatioships don’t change, so any rift that might occur causing the relative price between the assts to diverge will likely settle down and move back closer to where it was before the disruption.

This is not just a feeling, there are ways to measure how highly correlated two assets are, and there are mathematical proofs that show when two like assets are highly correlated, there is a deterministic probablity that any divergence will result in a regression, that number is 75%. This statistical proof is an edge, but not the whole edge. There are methods you can employ that can drastically improve upon this situation. And that will be the primary topic of this blog.

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