Paper Info
Title
Fitness function evaluation for MA trading strategies based on genetic algorithms
Abstract
This paper presents a new approach to optimize an investment strategy based on moving averages (MA). The proposed approach optimizes the entry and exit points, for both long and short positions, using a genetic algorithm (GA) kernel. This approach outperforms B&H strategy and explores alternative functions to the classical absolute return fitness function. The approach is demonstrated for major market indexes, such as, S&P 500, FTSE100, DAX30, NIKKEI225.
Year
DOI
Venue
2011
10.1145/2001858.2002105
GECCO (Companion)
Keywords
Field
DocType
h strategy,fitness function evaluation,ma trading strategy,short position,genetic algorithm,alternative function,investment strategy,classical absolute return fitness,exit point,new approach,major market index,fitness function,technical analysis,moving average,evolutionary algorithm,indexation,stocks,evolutionary algorithms,investment strategies,optimization,trading strategy,financial analysis
Trading strategy,Mathematical optimization,Evolutionary algorithm,Computer science,Investment strategy,Absolute return,Fitness function,Fitness approximation,Moving average,Genetic algorithm
Conference
Citations 
PageRank 
References 
4
0.50
4
Authors
3
Name
Order
Citations
PageRank
José Pinto1236.89
Rui Ferreira Neves2688.16
Nuno Cavaco Horta331049.65