Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

Rituparna Sen () and Pulkit Mehrotra
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Rituparna Sen: Indian Statistical Institute, Chennai Centre
Pulkit Mehrotra: HSBC Analytics

Journal of Quantitative Economics, 2016, vol. 14, issue 1, No 7, 137-150

Abstract: Abstract Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models.

Keywords: High frequency financial data; Realized volatility; Jump detection; Asymmetric power ARCH (search for similar items in EconPapers)
JEL-codes: C52 C58 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40953-016-0028-5

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