ANALYSIS OF STOCK PORTFOLIO OPTIMIZATION ON JAKARTA ISLAMIC INDEX USING SIMULATED ANNEALING AND GENETIC ALGORITHM METHOD

• Main Author: Bintang Ramadhanti, Nadya
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/49456
• Institution: Institut Teknologi Bandung

There are more cases that are occurring from various fields that still need solutions to solve these problems. Physicists have discovered a new system in the world of physics to answer these problems called a complex system. Complex systems are a system that studies how to solve complex cases using theories that have been studied in physics. Complex systems are divided into three: econophysics, sociophysics, and urban physics. Problems in the real world can occur in various fields, one of which is economics, so econophysics is used. Econophysics is a science that is based on physical theories to solve cases in the economic world. In the economic world, stock price is categorized as a complex system. This is because the stock price cannot be predicted because its value can go up and down immediately so it needs to be analyzed using a new approach. Stock prices needs to be predicted in order to be able to invest. Investment is an activity of investing capital in a particular asset that aims to generate large profits with minimum risk. To achieve these objectives in investing, it is necessary to create a stock portfolio. The stock portfolio contains a collection of assets to be invested with their respective weights. The proportion of each share that will be invested requires a solution using the approach of the econophysical method, the simulated annealing (SA) method and the genetic algorithm (GA). Both of these methods are methods that can calculate the optimization of a function to be compared which one is better. The index that will be analyzed is the Jakarta islamic index (JII). The data taken is the stock price for 6 years, which is from 1st January 2014 to 31st December 2019. The results that are obtained are the simulated annealing method which has a faster performance and produces greater fitness compared to the GA method of 0,875.