如何解读对数价格配对交易中的协整系数
文章 Quant Q&A · 作者: mathjacks
总结
本文探讨对数价格协整关系中的系数对于配对交易意味着什么,并比较将其解读为股数比与市值比这两种方式,说明两者为何会导致不同的头寸规模和收益计算。
一种回答认为,将股票价格乘以常数不会改变其百分比变动,因此拟合系数不变,但截距会改变。由于代表给定市值所需的股数会变化,这支持将该系数解读为市值权重。另一种回答指出,对数价格变化代表增长率,并提醒当两条腿投入的资金不同时,不能直接将各自收益相加;总利润应与投入的总资金相比。讨论较简略,呈现了相互冲突的观点,既没有完整推导,也没有给出普遍适用的交易建议。实际解读还取决于价差和投资组合的具体定义。
核心观点
- 对数价格之间的协整关系,其系数不会因某个价格序列乘以常数而改变。
- 这种尺度不变性支持将系数解读为相对市值敞口,而非原始股数。
- 对数价格变化描述价格的比例变动,因此合并各腿收益时应考虑各自投入的资金。
- 讨论未能充分调和不同解读,也未规定普遍适用的头寸规模规则。
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# 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.
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