Portfolio Optimization by Using Big Bang-Big Crunch Algorithm
الموضوعات :
علیرضا علی نژاد
1
(
استادیار دانشکده مهندسی صنایع و مکانیک، دانشگاه آزاد اسلامی واحد قزوین، قزوین، ایران
)
الکلمات المفتاحية: Mean-variance Markowitz Model, Portfolio Optimization Problem, Big Bang- Big Crunch Algorithm, Cardinality Constraints, Efficient frontier,
ملخص المقالة :
Investment plays a vital role on economic growth. One of the main objectives of all countries is to achieve sustainable economic growth and development. Nowadays, a considerable amount of activities performed by the managers and investors in general is to make a portfolio of assets effectively meeting demand goals. In this study, mean-variance Markowitz model by cardinality constraints and also a new innovative approach called Big Bang-Big Crunch algorithm are used to create a portfolio of assets. The algorithm proposed in this study compares with other algorithms such as simulated annealing, genetic, etc. by using datasets taken from the stock exchange indices in Hong Kong, Iran and Japan, the results indicate that the algorithm is competitive to solve the portfolio optimization problem efficiently.
