15340

13763

كارشناسي ارشد

مخابرات

اصفهان : دانشگاه صنعتي اصفهان

1398

يازده، 80ص.: مصور، جدول، نمودار

محمدمهدي نقش

محمد دخيل عليان، نغمه السادات مويديان

1398/09/16

كتابنامه

مهندسي برق

مهندسي برق و كامپيوتر

1398/09/17

2582022

Selection of Sparse and Diverse Index Tracking Portfolio Using Optimization Techniques Samira Gharibi Farashbandi samira gharibi@ec iut ac ir June 22 2019 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Dr Mohammad Mahdi Naghsh mm naghsh@cc iut ac ir AbstractInvestment affairs is one of the most important factors affecting the economics of countries Investors have always been looking for optimal investment choices Investors use one oftwo active or passive management methods to manage their portfolios In an active way theinvestor tries to find stocks that have higher returns in future moments than other stocks Inorder to find such stocks the investor must well predict stock performance in the comingmoments But passive investment does not require market prediction The great benefits ofthe passive investment strategy including less risk less managment costs and the lack ofmarket forecasting have led to special attention in this way in the world s capital markets inrecent years In this thesis in addition to introducing the basic financial concepts and being familiarwith the active investment method we focus mainly on index tracking as one of the mostimportant passive investment methods The purpose of index tracking is creating a portfolio which has a similar performance to that of the benchmark index Sparse tracking is one of thetracking methods The aim of sparse index tracking is creating a portfolio with small numberof stocks to track a benchmark index The smaller the number of portfolio components theless money the investor will need to pay We also consider diversity in sparse index trackingfor the first time for error reduction In this thesis two different problems are consideredfor index tracking In the first problem the goal is to minimize a multi objective function in terms of the total weight of the tracking error the degree of sparsity and diversity ofthe portfolio taking into account the long only and the capital budget constraints Then we deal with the first problem via MaMi technique In the second problem in addition tothe constraints considered for the first problem the holding constraint is also considered This problem has also been dealt with MaMi technique The simulation results show thatwith considering the diversity property for portfolio a portfolio can be designed that track abenchmark index with less error Key Words Portfolio Passive Investment Index Tracking MaMi Algorithm

محمدمهدي نقش

محمد دخيل عليان، نغمه السادات مويديان