Superiority of six factor model in Indian stock market

This novel work is the first study in India to incorporate the Human capital (HC) factor as a six-factor asset-pricing model and presents a robust methodology. The aim of this work is to examine the ability of the six-factor model to capture excess returns using a GMM framework with time periods that were missing in previous studies. Therefore, data for this study were collected using the BSE 500 index. Building on this insight, this study attempts to explain the inherent risk factors (firms and markets) that predict returns over a period of time, considering the dynamics of the Indian market. The GRS test also confirms the superiority of the six-factor model for the Indian equity market. The study asserts that the Instrumental variable- Generalized method of moments (IVGMM) is a robust model over OLS in explaining portfolio returns (single and bivariate), which implies that OLS in the asset pricing model is exaggerated in the Indian context. Single portfolios are constructed based on the factors of size, value, ROE, INV and human capital, while bivariate portfolios are constructed based on the intersection of any these two factors. This study confirms the significant role of HC (wealth) in describing the stock returns of an economy. This study contributes to the ongoing discourse on asset pricing models and offers valuable implications for investment decisions, risk management, and portfolio construction in one of the most attractive global financial markets. This novel work is the first study in India to incorporate the Human capital (HC) factor as a six-factor asset-pricing model and presents a robust methodology. The aim of this work is to examine the ability of the six-factor model to capture excess returns using a GMM framework with time periods that were missing in previous studies. The study asserts that the Instrumental variable- Generalized method of moments (IVGMM) is a robust model over OLS in explaining portfolio returns (single and bivariate), which implies that OLS in the asset pricing model is exaggerated in the Indian context. Single portfolios are constructed based on the factors of size, value, ROE, INV and human capital, while bivariate portfolios are constructed based on the intersection of any these two factors. This study confirms the significant role of HC (wealth) in describing the stock returns of an economy. This study contributes to the ongoing discourse on asset pricing models and offers valuable implications for investment decisions, risk management, and portfolio construction in one of the most attractive global financial markets.

Authors

Institutions

Publication Details

Journal
Cogent Economics & Finance
Published
2024-10-08
DOI
https://doi.org/10.1080/23322039.2024.2411567
Citations
4
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
2.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Superiority of six factor model in Indian stock market

Saroj S. Prasad, Shantanu Prasad, Priti Bakhshi, Ashutosh Verma
4 citations
Cogent Economics & Finance
Financial Markets and Investment Strategies
2.16
article

Superiority of six factor model in Indian stock market

Saroj S. Prasad, Shantanu Prasad, Priti Bakhshi, Ashutosh Verma
article en
4 citations

Abstract

This novel work is the first study in India to incorporate the Human capital (HC) factor as a six-factor asset-pricing model and presents a robust methodology. The aim of this work is to examine the ability of the six-factor model to capture excess returns using a GMM framework with time periods that were missing in previous studies. Therefore, data for this study were collected using the BSE 500 index. Building on this insight, this study attempts to explain the inherent risk factors (firms and markets) that predict returns over a period of time, considering the dynamics of the Indian market. The GRS test also confirms the superiority of the six-factor model for the Indian equity market. The study asserts that the Instrumental variable- Generalized method of moments (IVGMM) is a robust model over OLS in explaining portfolio returns (single and bivariate), which implies that OLS in the asset pricing model is exaggerated in the Indian context. Single portfolios are constructed based on the factors of size, value, ROE, INV and human capital, while bivariate portfolios are constructed based on the intersection of any these two factors. This study confirms the significant role of HC (wealth) in describing the stock returns of an economy. This study contributes to the ongoing discourse on asset pricing models and offers valuable implications for investment decisions, risk management, and portfolio construction in one of the most attractive global financial markets. This novel work is the first study in India to incorporate the Human capital (HC) factor as a six-factor asset-pricing model and presents a robust methodology. The aim of this work is to examine the ability of the six-factor model to capture excess returns using a GMM framework with time periods that were missing in previous studies. The study asserts that the Instrumental variable- Generalized method of moments (IVGMM) is a robust model over OLS in explaining portfolio returns (single and bivariate), which implies that OLS in the asset pricing model is exaggerated in the Indian context. Single portfolios are constructed based on the factors of size, value, ROE, INV and human capital, while bivariate portfolios are constructed based on the intersection of any these two factors. This study confirms the significant role of HC (wealth) in describing the stock returns of an economy. This study contributes to the ongoing discourse on asset pricing models and offers valuable implications for investment decisions, risk management, and portfolio construction in one of the most attractive global financial markets.

Cogent Economics & FinanceVol. 12(1)
Indian Institute of Forest Management (IN), Birla Institute of Technology and Science, Pilani - Goa Campus (IN)
Openalex Percentile: Top 12%
Financial Markets and Investment Strategies
2.16
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.