TY  - JOUR
TI  - A Brief Introduction to Portfolio Optimization Using Genetic Algorithm

AU  - Abisekh Kumar
AU  -  Minakshi Ghosh
AU  -  Chiranjit Mandal
AU  -  Runa Mallick
AU  -  Arnab Chatterjee
AU  -  Susobhan Das
AU  -  Sourav Samanta
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2018/04/25
PY  - 2018
DO  - https://doi.org/10.32628/IJSRCSEIT
UR  - https://ijsrcseit.com/CSEIT411856
VL  - 4
IS  - 1
SP  - 335	
EP  - 340
AB  - A portfolio can be said as a group of financial assets such as stocks bonds and even cash and funds. Portfolio optimization refers to the allocation of the investment in such a way among assets so as to maximize the overall profit and minimize the risk. The problem is obtaining the risk and expected return for each of the individual assets, further computations involving how to divide the basic wholesome amount of investment into different assets so as the entire weight of the assets remain one is ensured. Portfolio Optimization problem is an important and hard optimization problem that, with the addition of necessary realistic constraints,becomes computationally intractable, in the area of economics and finance. Genetic Algorithm (GA) is an optimization technique which mimics the natural evolution that has the optimization features. GA has been increasingly used during the last decades to support complex decision-making in a number of fields, such as image processing, logistics and transportation, telecommunication networks, bioinformatics, finance, and many more. In recent years, much work has been done in finding optimum solution in solving portfolio problem with the use of GA. This paper gives a brief introduction about how to use Genetic Algorithm for solving portfoliooptimization problem. This study focuses on optimization of Markowitz model using GA.