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Application of a Multi-factor Linear Regression Model for Stock Portfolio Optimization
- Source :
- 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Multi-factor models of asset pricing indicate a linear relationship between the expected return of assets while exposing to one or more risks. In this study, the sensitivity of portfolio returns to 4 selected macroeconomic factors (Market Performance, Real GDP, Inflation, Unemployment) were examined by means of multiple linear regression analyses with regard to multi-factors. Experiments show that the generalized approach of moment estimators of risk premiums lead to better results on individual assets over historical averages. Especially when the factors are weakly correlated with assets which indicates that the factors selected should be less correlated with each other.
- Subjects :
- Inflation
050208 finance
Computer science
media_common.quotation_subject
Risk premium
05 social sciences
Moment (mathematics)
Real gross domestic product
0502 economics and business
Linear regression
Econometrics
Portfolio
Expected return
Capital asset pricing model
050207 economics
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)
- Accession number :
- edsair.doi...........daaf2e3d6b641bbd7b1f2606dcdcb8f6