经典股市交易思维系列：1、Pairs Trading（配对交易）

1、思维简介：

实践经常表明，有利可图的交易策略并不一定复杂；一个很好的例子是众所周知的股票对交易。Pairs Trading是华尔街历史悠久的热门短期投机策略。然而，正如前面提到的，配对交易的概念很简单。一个潜在的投资者必须找到两个股票，它们的价格在历史上是一致的，当它们之间的价差扩大时，做空赢家，买入输家。利润在于假设历史会重演。如果历史重演，价格将趋同，套利者将获利。总之，这种策略完全基于简单的逆势原则和过去的股价：也就是说，当股票之间的价差扩大时，这种策略押注于趋同。

此外，在欧洲市场也发现了同样的模式。Lucey和Walshe在“欧洲股票对交易：数据频率对风险和回报的影响”一文中，使用1998-2007年期间每日、每周和每月的欧洲股票价格数据，研究了一种股票对交易策略，基于这些价格之间波动性的简单交易规则，每周数据频率的年化原始回报率高达15%。

在不太乐观的情况下，最近的研究表明，这种策略的积极回报正在慢慢减少。例如，Chen，和Li在“股权对交易策略的实证研究”“，在使用过去的数据时也表明，股票对交易策略会产生巨大而显著的异常回报。然而，最后，他们表示，与适应性市场效率理论一致，这种简单的对交易策略的回报随着时间的推移而减少。侵蚀利润导致学者们改进了他们的策略。作为一个例子，我们想提到Do和Faff撰写的论文“简单的配对交易仍然有效吗？”

The practice often shows that profitable trading strategies do not have to be complicated; a good example is a well known Pairs Trading with Stocks. The Pairs Trading is a popular short-term speculation strategy with a long history on Wall Street. However, as was previously mentioned, the concept of pairs trading is straightforward. A potential investor has to find two stocks whose prices have moved together historically, and when the spread between them widens, short the winner and buy the loser. The profits lie in the assumption that history would repeat. If history repeats itself, prices will converge, and the arbitrageur will profit. To sum it up, this strategy is based solely on simple contrarian principles and past stock prices: Said, the strategy bets on convergence when the spread between stocks widens.

Additionally, the same pattern was found in the European markets. Lucey and Walshe in the “European Equity Pairs Trading: The Effect of Data Frequency on Risk and Return” examined an equity pairs trading strategy using daily, weekly and monthly European share price data over the period 1998-2007. The authors show that when stocks are matched into pairs with minimum distance between normalized historical prices, a simple trading rule based on volatility between these prices yields annualized raw returns of up to 15% for the weekly data frequency.

On a less positive note, more recent research states that the positive returns of this strategy are slowly diminishing. For example, Chen, Chen, and Li in the “Empirical Investigation of an Equity Pairs Trading Strategy“, have also shown while using past data that an equity pairs trading strategy generates large and significant abnormal returns. However, in the end, they said that consistent with the adaptive market efficiency theory, the return to this simple pairs trading strategy has diminished over time. Eroding profits have led academics to improve their strategy. As an example, we would like to mention the paper “Does simple pairs trading still work?” written by Do and Faff (the paper can be found in the “Other Papers” section).

2、原理

配对交易策略的先驱，Nunzio Tartaglia表示，对交易的解释是心理上的。他声称，“人类不喜欢违背人性进行交易，因为人性想在股票上涨而不是下跌后买入。”这意味着，配对交易者是有纪律的投资者，他们利用了个人投资者表现出的无纪律的过度反应。

利润也可以通过一些逻辑假设来解释，这些假设导致Pairs Trading投资组合未来回报的预期概率很高。如果过去某些股票对的价格是紧密协整的，那么这两种证券很可能共享基本收益相关性的共同来源。然而，暂时的震荡可能会将一只股票移出共同价格区间，这提供了一个统计套利机会。此外，对的宇宙不断更新，这确保不再同步移动的对从交易中移除。因此，投资组合只包括价格很可能趋同的对。此外，作者排除了对交易利润的几种解释，包括之前文献中记载的均值回归、未实现的破产风险，以及由于卖空限制，套利者无法利用利润。

Chen、Chen和Li在“股权对交易策略的实证研究”中研究了该策略的经济驱动因素。首先，他们发现，这种回报并非纯粹由短期回报逆转驱动。其次，他们将成对的股票收益相关性分解为可以用共同因素（如规模、账面市值和应计利润）解释的相关性和不能解释的相关性。引用作者的话：“我们发现，可由共同因素解释的对相关性驱动了大多数对交易回报。第三，在信息环境更丰富的公司中，对交易的价值加权利润更高，而我们的交易策略在最近的流动性危机中表现不佳，这表明对交易利润主要不是由信息扩散延迟和流动性准备金。最后，与适应性市场效率理论一致，这种简单的配对交易策略的回报随着时间的推移而减少。”

Pioneer of this strategy, Nunzio Tartaglia states that the explanation of the pairs trading is psychological. He claims, that “Human beings don’t like to trade against human nature, which wants to buy stocks after they go up not down.” This means that pairs traders are the disciplined investors taking advantage of the undisciplined over-reaction displayed by individual investors.

The profits could also be explained by some logical assumptions that result in the high expected probability of future returns of the Pairs Trading portfolio. If prices of some stock pair in the past were closely cointegrated, there is a high probability that those two securities share common sources of fundamental return correlations. However, a temporary shock could move one stock out of the common price band, which presents a statistical arbitrage opportunity. Additionally, the universe of pairs is continuously updated, and this ensures that pairs which no longer move in synchronicity are removed from trading. Therefore, the portfolio includes only pairs with a high probability that their prices would be convergent. Moreover, the authors ruled out several explanations for the pairs trading profits, including mean-reversion as previously documented in the literature, unrealized bankruptcy risk, and the inability of arbitrageurs to take advantage of the profits due to short-sale constraints.

Chen, Chen, and Li in the “Empirical Investigation of an Equity Pairs Trading Strategy” have examined the economic drivers of this strategy. First, they have found that this return is not driven purely by theshort-term reversalof returns. Secondly, they have decomposed the pair-wise stock return correlations into those that can be explained by common factors (such assize,book-to-market, andaccruals) and those that cannot. Quoting the authors: “We find that the pairs correlations explainable by common factors drive most of the pairs trading returns. Third, the value-weighted profits of pairs trading are higher in firms in a richer information environment, and our trading strategy performs poorly in the recent liquidity crisis, suggesting that the pairs trading profits are not primarily driven by the delay in information diffusion and liquidity provision. Finally, consistent with the adaptive market efficiency theory, the return to this simple pairs trading strategy has diminished over time.” The last only underlines the need for the enhanced Pair Trading strategy – for example, the work of Do and Faff.