摘要：Pairs trading is a comparative-value form of statistical arbitrage designed
to exploit temporary random departures from equilibrium pricing between two shares.
However, the strategy is not riskless. Market events as well as poor statistical modeling
and parameter estimation may all erode potential profits. Since conventional loss
limiting trading strategies are costly, a preferable situation is to integrate loss limitation
within the statistical modeling itself. This paper uses cointegration principles to develop
a procedure that embeds a minimum profit condition within a pairs trading strategy.
We derive the necessary conditions for such a procedure and then use them to define and
implement a five-step procedure for identifying eligible trades. The statistical validity of
the procedure is verified through simulation data. Practicality is tested through actual
data. The results show that, at reasonable minimum profit levels, the protocol does
not greatly reduce trade numbers or absolute profits relative to an unprotected trading
strategy.
