Making Profit in Stock Investment Before XD Dates by Using Genetic Algorithm - Innovative Management in Information and Production - page 338

The rates of return of the investment strategies are impressive when calculated
in the equivalence of the annual rate. More than half of the eight stocks yield more
than 50 % of the return per year.
The performance of the genetic algorithm is quite good. The model with zero
mutation rate that is applied to the data in the first half of the year can extract
62 % of the highest potential profit. Increasing the rate to be positive reduces the
performance probably by half. However, even though the yield of the second half
of the year is lower than in the first half, the performances of genetic algorithm
with zero mutation rate are quite similar in both periods. The algorithm extracts
around 62 % of the highest potential profit without the influence of how much profit
is available in each period.

Acknowledgements The authors would like to thank Professor Berlin Wu, Prof. Hung T. Nguyen,
and Prof. Songsak Sriboonchitta for the inspiration, stimulation, valuable comments, and technical
supports to this study.

References

A. Jann, Multiple change-point detection with a genetic algorithm. Soft Comput. 4 , 68-75 (2000)
S. Li, R. Lund, Multiple changepoint detection via genetic algorithms. J. Climate 25 , 674-686

(2012)
T. Sudtasan, Detection of regime switching in stock prices before window dressing at the year end
using genetic algorithm. Int. J. Intell. Techn. Appl. Stat. 5 , 143-155 (2012)
T. Sudtasan, K. Suriya, Detection of regime switching in stock prices before window dressing at
the year end using genetic algorithm. Paper presented in the 5th international conference of the
Thailand econometric society, Chiang Mai, January 2012