A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction

Sasmita Mishra, Sudarsan Padhy, Satya Narayan Mishra and Satya Narayan Misra

The North American Journal of Economics and Finance, 2021, vol. 55, issue C

Abstract: In this study a LASSO – TLBO – SVR hybrid model is used for portfolio construction. Relevant economic parameters are determined and used for stock selection. Along with stock selection, weights for the stocks are obtained by solving a portfolio optimization problem using three methods: GRG Nonlinear, Evolutionary method based on Genetic Algorithm, and Equal weight method. The portfolio return in the proposed model is compared with the return of the Indian market portfolio (NSE and BSE). It is observed that the proposed model outperforms the market portfolio.

Keywords: Portfolio construction; Least absolute shrinkage and selection operator (LASSO); Teaching learning-based optimization (TLBO); Support vector regression (SVR); Mean absolute percentage error (MAPE); Weight optimization (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:55:y:2021:i:c:s1062940820302333

DOI: 10.1016/j.najef.2020.101350

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