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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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In recent years, there has been an explosion of research on the volatility of stock returns. As high frequency stock price data became more readily available, there have been many proposed estimators of integrated variance which attempt to take advantage of the informational gains of high-frequency data while minimizing any potential biases that arise from sampling at such a fine scale. These estimators rely on various assumptions about the price process which can make them difficult to compare theoretically. Relying on the methods of Patton (2011a), this paper analyzes the performance of five different classes of integrated variance estimators when applied to various stocks of differing market capitalization in an attempt to discover the circumstances under which one estimator should be chosen over another.
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참고문헌 (27)
참고문헌 신청
Ait-Sahalia, Y. / 2011 / Testing Whether Jumps Have Finite or Infinite Activity / The Annals of Statistics 39 : 1689 ~ 1719
Ait-Sahalia, Y. / 2012 / Analyzing the Spectrum of Asset Returns: Jumps and Volatility Components in High Frequency Data / Journal of Economic Literature 50 : 1007 ~ 1050
Andersen, T. / 2008 / Duration-Based Volatility Estimation
Andersen, T. / 2012 / Jump-Robust Volatility Estimation using Nearest Neighbor Truncation / Journal of Econometrics 169 : 75 ~ 93
Andersen, T. G. / 2000 / Great Realizations / Risk 13 : 105 ~ 108
Ait-Sahalia, Y. / 2012 / Analyzing the Spectrum of Asset Returns: Jumps and Volatility Components in High Frequency Data / Journal of Economic Literature 50 : 1007 ~ 1050
Andersen, T. / 2008 / Duration-Based Volatility Estimation
Andersen, T. / 2012 / Jump-Robust Volatility Estimation using Nearest Neighbor Truncation / Journal of Econometrics 169 : 75 ~ 93
Andersen, T. G. / 2000 / Great Realizations / Risk 13 : 105 ~ 108
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