Realized Measures to Explain Volatility Changes over Time

Christos Floros, Konstantinos Gkillas, Christoforos Konstantatos and Athanasios Tsagkanos
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Konstantinos Gkillas: Department of Business Administration, University of Patras, University Campus–Rio, 26504 Patras, Greece
Christoforos Konstantatos: Department of Business Administration, University of Patras, University Campus–Rio, 26504 Patras, Greece
Athanasios Tsagkanos: Department of Business Administration, University of Patras, University Campus–Rio, 26504 Patras, Greece

JRFM, 2020, vol. 13, issue 6, 1-19

Abstract: We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S&P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S&P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling.

Keywords: volatility; realized measures; high frequency data; statistical properties; FTSE100; S& P500 (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (8)

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