This paper presents two methods for increasing comprehensibility in technical trading rules produced by Genetic Programming. For this application domain adding a complexity penalizing factor to the objective fitness function also avoids overfitting the training data. Using pre-computed derived technical indicators, although it biases the search, can express complexity while retaining comprehens...

In this paper, the authors maintain that the prevalence of technical analysis in professional investment argues that such techniques should perhaps be taken more seriously by academics. They use the new technique of genetic programming to investigate a long time series of price data for a quoted property investment company, to discern whether there are any patterns in the data which could be us...

T his paper ascertains the extent of mispricing in equity portfolios, mispricing-divestment relation, and the role of African equities as risk diversification strategies during commodity market turbulence. Following Baur and Lucey (2010), one identifies an arbitrary commodity market crisis to be 1%, 5%, and 10% declining moments in returns. However, their approach is extended by usin...

Major events often trigger abrupt changes in stock prices and volatility.We study the implications of jumps in prices and volatility on investment strategies. Using the event-risk framework of Du⁄e, Pan, and Singleton (2000), we provide analytical solutions to the optimal portfolio problem. Event risk dramatically a¡ects the optimal strategy. An investor facing event risk is less willing to tak...

We study the problem of nding the minimal price needed to dominate European-type contingent claims under proportional transaction costs in a continuous-time diiu-sion model. The result we prove has already been known in special cases-the minimal super-replicating strategy is the least expensive buy-and-hold strategy. Our contribution consists in showing that this result remains valid for genera...

In this paper a portfolio optimization algorithm based on Evolution Strategies is presented. This method makes use of artificial trading experts discovered earlier by a genetic algorithm. These experts, consisting of technical analysis rules, are trained to process financial time series and to generate trading advice. Evolution Strategies lead to the optimization of portfolio structures where i...

Evidence suggests that predictabilities in asset class returns exist but transactions costs prevent exploiting them using individual securities. Extant research also shows that these relationships may by exploitable through the trading of mutual funds but fails to examine whether this relationship exists within an individual fund family. This paper finds that TIAA/CREF retirement annuities exhi...

We propose a prediction model based on the minority game in which traders continuously evaluate a complete set of trading strategies with different memory lengths using the strategies’ past performance. Based on the chosen trading strategy they determine their prediction of the movement for the following time period of a single asset. We find empirically using stocks from the S&P500 that our pr...