Volatility Clustering of Select Sectoral Indices in the BSE Stock Market
D. Vijayalakshmi1, G. C. Thanya2
1Dr. D. Vijayalakshmi, Department of Commerce, PSGR Krishnammal College for Women, Coimbatore (Tamil Nadu), India.
2Thanya. G.C, Department of Commerce, PSGR Krishnammal College for Women, Coimbatore (Tamil Nadu), India.
Manuscript received on 30 July 2022 | Revised Manuscript received on 03 August 2022 | Manuscript Accepted on 15 August 2022 | Manuscript published on 30 August 2022. | PP: 47-54 | Volume-11 Issue-9, August 2022. | Retrieval Number: 100.1/ijitee.G92470811922 | DOI: 10.35940/ijitee.G9247.0811922
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Abstract: Volatility is a standard measure of financial vulnerability and it plays a vital role in analyzing the risk of the securities market. It is traditionally measured using the standard deviation, which indicates how the price of a stock is clustered around the mean or moving average. The intent of the study is to analyse the volatility clustering of six select sectoral indices such as S&P BSE AUTO (Automobile), S&P BSE BANKEX (Bank) , S&P BSE FMCG (Fast Moving Consumer Goods), S&P BSE IT (Information Technology), S&P BSE METAL ( Metals), and S&P BSE OIL & GAS (Oil & Gas Industries). A sample of 2726 days of observations for 11 years period from 03.01.2011 to 31.12.2021 has been taken for the study. The econometric model namely ARCH and GARCH have been applied to analyse the data. The result of the study reveals the presence of volatility clustering in the select six sectoral indices. Metal Sector has shown the higher phase of volatility.
Keywords: Volatility Clustering, Sectoral Indices, ARCH Model, GARCH Model
Scope of the Article: Clustering