APPLICATION OF COMBINED GENETIC ALGORITHM AND SIMULATED ANNEALING METHODS FOR VALUE AT RISK MINIMIZATION IN SHARIA STOCK PORTFOLIO - Rais Adiwidya, Hatta
Physics is the most basic science that studies the structure of matter, behavior and motion, types of energy, time and space in the universe so that people can understand and model how the universe works. Stocks are certificates that show proof of ownership of a company, and stockholders have the right to claim the profits and assets of the company. In building a portfolio, an investor would want the maximum profit with the lowest possible risk, but this condition is difficult to realize because in reality there are many factors that affect stock price movements. The solution is the proper distribution of investment burdens and calculate the Value at Risk or VaR, which is the maximum probability of loss of an investment based on the level of confidence. A safe stock portfolio is a portfolio that has a low VaR. In this study, an optimization of asset burden sharing will be carried out to obtain a portfolio that has the smallest VaR. The stock portfolio formed is from companies that are constituents of the JII70 index. The optimization method used in this research is a hybrid method of Genetic Algorithm which is an optimization method by adopting the principle of Mendelian inheritance and Simulated Annealing which is an optimization method adopted from the annealing process in metallurgy. The two methods will be combined expecting that the combined method of Genetic Algorithm and Simulated Annealing or GA-SA can provide optimal results. The result shows, a VaR value of 3.766% which is lower compared to the VaR results using the equalization method and Genetic Algorithm. The distribution of investment burden also shows good results where stable companies tend to get large allocations and vice versa. The combined GA-SA method has succeeded in producing a safe investment burden sharing pattern.