A Vector Autoregressive Market Model for IT Sector Stocks in India

Mihir Dash, Rita S.


This study proposes a vector autoregressive form for the market model and tests its significance against the market model for information technology (IT) sector stocks in the Indian stock market. The analysis was performed for a sample of nineteen IT sector stocks listed on the National Stock Exchange of India, of which nine stocks were large-cap, six were mid-cap, and four were small-cap. The study period considered was Jan. 1, 2018 – Dec. 31, 2018.


The key contribution of the study was the finding that the vector autoregressive model is a better model of stock returns than the market model for IT sector stocks. Thus, IT sector stocks seem to react more to market movements from the previous day than on the day itself. The implication for asset pricing modelling is that systematic risk may be further decomposed into a component corresponding to sensitivity to market movements on the day and a component corresponding to sensitivity to market movements on the previous day. The asset pricing model would be extended to include market risk premia for both of these components of systemic risk.


Keywords: market model, vector autoregressive model, IT sector, asset pricing modelling, systematic risk.

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DOI: https://doi.org/10.5296/ajfa.v13i1.18589

Copyright (c) 2021 Mihir Dash, Rita S.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Asian Journal of Finance & Accounting ISSN 1946-052X

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