Quantitative Analysis of Stock Portfolio: Taking Six Technology Companies as Example

Heng Li, Xiaoxi Zhu, Xiao Wang

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

This article introduces a quantitative analysis method of selected stocks with Python. Firstly, the portfolio weight of the six selected technology stocks with maximum Sharpe Ratio was determined. Secondly, the performance of the portfolio according to the historical data was back-tested. Also, Fama-French three-factor model was used to analyze the factors that might affect the stock price and a regression analysis was done on these factors. Through quantitative analysis, the portfolio weights with maximum Sharpe Ratio and minimum volatility of target stocks could be given out respectively.

Original languageEnglish
Title of host publicationProceedings - 2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021
Place of PublicationU. S. A.
PublisherIEEE
Pages468-473
Number of pages6
ISBN (Electronic)9781665412278
ISBN (Print)9781665429641
DOIs
Publication statusPublished - 20 Apr 2022
Externally publishedYes
Event2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021 - Nanjing, China
Duration: 23 Apr 202125 Apr 2021

Publication series

NameProceedings - 2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021

Conference

Conference2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021
Country/TerritoryChina
CityNanjing
Period23/04/2125/04/21

Keywords

  • Component
  • Fama-French three-factor model
  • Markowitz Portfolio Theory
  • Regression analysis
  • Sharpe Ratio

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Finance
  • Development

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