VOLATILITY ESTIMATORS WITH HIGH-FREQUENCY DATA FROM BUCHAREST STOCK EXCHANGE

Virgil Damian () and Cosmin – Octavian Cepoi ()
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Virgil Damian: The Bucharest University of Economic Studies
Cosmin – Octavian Cepoi: The Bucharest University of Economic Studies

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2016, vol. 50, issue 3, 247-264

Abstract: In this paper, we have focused on accurately volatility estimation due to its crucial importance in investment and risk management activities. Based on tick by tick data, provided by Thomson Reuters, we have realized a comparative study among different high-frequency volatility estimators for some of the most important three companies listed on Bucharest Stock Exchange. Our findings emphasize that the presence of jumps or microstructure noises affect the efficiency of realized volatility estimator. So, based on data architecture, we have used adequate estimators jump and noise robust. We concluded that for less liquid markets, the presence of more visible jumps leads to higher intra-day volatilities comparing with more liquid markets.

Keywords: stochastic volatility; realized variance; realized kernel; two time scales estimator; jump; stochastic integral representation. (search for similar items in EconPapers)
JEL-codes: C13 C58 G10 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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