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Interpreting the Cointegration Coefficient in Log-Price Pairs Trading

Article Quant Q&A · Author: mathjacks

Summary

The document examines what the coefficient in a log-price cointegrating relation means for a pairs trade. It contrasts interpreting the coefficient as a share ratio with interpreting it as a ratio of market values, and explains why those interpretations lead to different position sizing and return calculations.

One answer argues that scaling a stock’s price by a constant leaves its percentage movements unchanged and therefore leaves the fitted coefficient unchanged, while changing the intercept. Since the number of shares needed to represent a given market value does change, this supports reading the coefficient as a market-value weight. Another answer points to log-price changes as growth rates and cautions that returns on each leg cannot simply be added when the capital invested differs; total profit should be compared with total capital deployed. The discussion is brief and presents conflicting claims without a full derivation or a general trading prescription. Practical interpretation also depends on how the spread and portfolio are explicitly defined.

Key ideas

  • A cointegrating relation between log prices uses a coefficient that is invariant to multiplying one price series by a constant.
  • That scale invariance supports interpreting the coefficient as a relative market-value exposure rather than a raw share count.
  • Log-price changes describe proportional price movements, so leg returns should be combined using their invested capital.
  • The discussion does not fully reconcile the differing interpretations or specify a universal sizing rule.

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Full text
# What does the cointegration coefficient represent in pairs trading when cointegrating log stock prices?


# What does the cointegration coefficient represent in pairs trading when cointegrating log stock prices?












In Pairs Trading by Vidyamurthy, on page 83 (and throughout the book), the author describes an elementary example of trading with log prices. The long run equilibrium of the basic portfolio is given by

$$ \log(p_t^A) - \gamma \log(p_t^B) = \mu $$

where $p_t^A$ and $p_t^B$ represent the prices of stocks $A$ and $B$ at time $t$, respectively, and $\gamma$ is the cointegration coefficient. When using these log prices, Vidyamurthy uses the cointegration coefficient ($\gamma$) to indicate the ratio of shares to hold rather than market values of positions (as stated should be the case here, for example).

My questions are:

> What is the correct practical interpretation of $\gamma$ when cointegrating log prices, should it represent the ratio of shares or the ratio of market values? If the latter, why does Vidyamurthy use the former interpretation throughout his book? Could both be valid?

Here is the example from the book:

## Answer by Artem Korol (score 1)

https://quant.stackexchange.com/a/21284

Firstly i think if you use log prices then γ shows by how much B stock growth rate outpaces A stock growth rate, but I don't understand why Ernie says that you need to hold market values fixed, if you do this then how are you going to profit from the spread?

Secondly there are typos in the return calculation: log(20.1)-log(19.5) = 0.03 not 0.3. Which refers to the 3% return on the A leg trade. B leg return is indeed 5.6% (assuming cc returns), however it is incorrect to sum these return to get 9% return on the total trade, since they were obtained from different amounts of capital. The return from A leg is 0.6USD and return from B leg is 0.29USD*1.5 = 0.435USD thus the total return is 1.035USD which we divide by the total capital deployed in the trade at time t, 19.5+1.5*7.46 = 30.69$, so 1.035/30.69 = 0.0337 and this is the real return on this trade, not 9%.

## Answer by Jason Huang (score 1)

https://quant.stackexchange.com/a/39613

It should mean market values (instead of shares). You can see this more obviously by creating an "artificial stock" (stock C) which price equals the price of stock B divided by 10,000 (same fluctuation rate, but just much smaller absolute price). Now the co integration coefficient would not change because C and B have the same variation rate (it would only affect the intercept, mu). If the cointegration coefficient means the shares ratio, then it would not make sense because now C occupy too little of your portfolio. It would only make sense as market values.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.