Asset Allocation and the Optimization Portfolio Choice for the Retired Firefighter
Anbo Wang ()
Additional contact information
Anbo Wang: Huazhong University of Science and Technology, Institute of Economics
A chapter in Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022), 2022, pp 1513-1520 from Springer
Abstract:
Abstract Asset allocation and portfolio management have become quite important as the fast development of the global finance and the tremendous improvement of people’s life. This paper aims at helping the retired firefighter employ his pension to allocate the assets and find the optimization of the portfolio. He has 2 different choices and the paper also need to make a comparison of them based on the quantitative analysis. In this paper, the Fama-French 3 Factor model is used to run the regression of the historical data between different assets and the influential factors to illustrate the features of each asset. Under the construction of the mean-variance analysis, it helps form the optimization of the portfolio, meanwhile, with the help of solver, the maximized Sharpe ratio is calculated. Then, the biggest Sharpe ratio of the 2 different choices and the corresponding weights of the assets are shown. The final results show that taking the pension benefit and investing his nest-egg to supplement the pension benefit is a better choice than gaining all the money at one time and investing it to the market because of the lower standard deviation. The results can be applied to the portfolio management of the retirees which are of great practical significance.
Keywords: portfolio management; asset allocation; Fama-French Three Factor model; personal tailor (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-052-7_167
Ordering information: This item can be ordered from
http://www.springer.com/9789464630527
DOI: 10.2991/978-94-6463-052-7_167
Access Statistics for this chapter
More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().