Mixed integer linear programming approach for seasonal anomalies in stock markets: A case study for BIST

This paper proposes a mixed integer programming approach for seasonal anomalies in stock markets and presents a case study for the XU030 index in the stock market of Istanbul Stock Exchange (BIST). Stock markets are significant for economies of countries all over the world. Investors get economical wealth or lose some of their investment by selling and buying stocks. Therefore, buying and selling times of stocks are so important. This paper investigates a well-known effect called as ‘Sell in May and Go Away’ by proposing a MIP approach that searches best times for buying and selling of stocks in a year. Furthermore, this paper includes a numerical example of XU030 stock prices for the past 5 years and shows that most of the XU030 stocks have seasonal anomalies.