خرید و دانلود نسخه کامل کتاب A Machine Learning based Pairs Trading Investment Strategy – Original PDF

Pairs Trading is a well-known investment strategy developed in the 1980s. It has been employed as one important long/short equity investment tool by hedge funds and institutional investors Cavalcante et al. [2], and is a fundamental topic in this work. This strategy comprises two steps. First, it requires the identification of two securities, for example two stocks, for which the corresponding prices series display a similar behaviour, or simply seem to be linked to each other. Ultimately, this indicates that both securities are exposed to related risk factors and tend to react in an identical way. Figure 1.1 illustrates how this behaviour can be found in some popular stocks. In Figure 1.1a, we may observe how the price series from two car manufacturers seem to be tied to each other. The same behaviour is also illustrated in Figure 1.1b, this time illustrating the price series of two of the biggest retail stores in the United States. Two securities that verify an equilibrium relation between their price series can compose a pair. 1 Once the pairs have been identified, the investor may proceed with the strategy’s second step. The underlying premise is that if two securities’ price series have been moving close in the past, then this should persist in the future. Therefore, if an irreg- ularity occurs, it should provide an interesting trade opportunity to profit from its correction. To find such opportunities, the spread 2 between the two constituents of the pairs must be continuously monitored. When a statistical anomaly is detected, a market position is entered. The position is exited upon an eventual spread correc- tion. It is interesting to observe that this strategy relies on the relative value of two securities, regardless of their absolute value.