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Open AccessArticle

Realized Measures to Explain Volatility Changes over Time

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Department of Accounting and Finance, Hellenic Mediterranean University, 71410 Heraklion, Greece
2
Department of Business Administration, University of Patras, University Campus–Rio, 26504 Patras, Greece
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Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2020, 13(6), 125; https://doi.org/10.3390/jrfm13060125
Received: 13 April 2020 / Revised: 2 June 2020 / Accepted: 6 June 2020 / Published: 13 June 2020
(This article belongs to the Special Issue Modern Portfolio Theory)
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. View Full-Text
Keywords: volatility; realized measures; high frequency data; statistical properties; FTSE100; S& P500 volatility; realized measures; high frequency data; statistical properties; FTSE100; S& P500
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Floros, C.; Gkillas, K.; Konstantatos, C.; Tsagkanos, A. Realized Measures to Explain Volatility Changes over Time. J. Risk Financial Manag. 2020, 13, 125.

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