Genetic programming and the efficient market hypothesis

Abstract

While search plays an important role in the efficient market hypothesis (EMH), the traditional formalization of the EMH, based on probabilistic independence, fails to capture it. Due to this failure, recent findings of nonlinear tests misled us into concluding that the EMH is rejected. Even though most economists are reluctant to make this conclusion, the traditional formalization leaves us no other choice. This paper reformalizes the EMH with a biologically-based search program, i.e., genetic programming (GP). The GP-based search enables us to model search in the EMH explicitly. Through this, serach cost as well as search intensity can be measured objectively, and the notion of predictability and profitability can then be formalized. The GP-based notion of the EMH will be exemplified by testing the EMH with a small, medium and large sample of the S&P 500 stock index.