Department of Economics and Business Economics

How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?

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How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps? / Veraart, Almut.

In: A St A - Advances in Statistical Analysis, Vol. 95, No. 3, 2011, p. 253-291.

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@article{3580a9d02f8311df9806000ea68e967b,
title = "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?",
abstract = "This paper studies the impact of jumps on volatility estimation and inference based on various realised variation measures such as realised variance, realised multipower variation and truncated realised multipower variation.We review the asymptotic theory of those realised variation measures and present a new estimator for the asymptotic {"}variance{"} of the centered realised variance in the presence of jumps.Next, we compare the finite sample performance of the various estimators by means of detailed Monte Carlo studies. Here we study the impact of the jump activity, of the jump size of the jumps in the price and of the presence of additional independent or dependent jumps in the volatility.We find that the finite sample performance of realised variance and, in particular, of log--transformed realised variance is generally good, whereas the jump--robust statistics tend to struggle in the presence of a highly active jump process.Finally, we investigate the impact of jumps on inference on volatility empirically, where we study high frequency data from the Standard & Poor’s Depository Receipt (SPY).",
keywords = "Realised variance, inference, stochastic volatility, jumps",
author = "Almut Veraart",
year = "2011",
doi = "10.1007/s10182-011-0158-1",
language = "English",
volume = "95",
pages = "253--291",
journal = "A St A - Advances in Statistical Analysis",
issn = "1863-8171",
publisher = "Springer",
number = "3",

}

RIS

TY - JOUR

T1 - How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?

AU - Veraart, Almut

PY - 2011

Y1 - 2011

N2 - This paper studies the impact of jumps on volatility estimation and inference based on various realised variation measures such as realised variance, realised multipower variation and truncated realised multipower variation.We review the asymptotic theory of those realised variation measures and present a new estimator for the asymptotic "variance" of the centered realised variance in the presence of jumps.Next, we compare the finite sample performance of the various estimators by means of detailed Monte Carlo studies. Here we study the impact of the jump activity, of the jump size of the jumps in the price and of the presence of additional independent or dependent jumps in the volatility.We find that the finite sample performance of realised variance and, in particular, of log--transformed realised variance is generally good, whereas the jump--robust statistics tend to struggle in the presence of a highly active jump process.Finally, we investigate the impact of jumps on inference on volatility empirically, where we study high frequency data from the Standard & Poor’s Depository Receipt (SPY).

AB - This paper studies the impact of jumps on volatility estimation and inference based on various realised variation measures such as realised variance, realised multipower variation and truncated realised multipower variation.We review the asymptotic theory of those realised variation measures and present a new estimator for the asymptotic "variance" of the centered realised variance in the presence of jumps.Next, we compare the finite sample performance of the various estimators by means of detailed Monte Carlo studies. Here we study the impact of the jump activity, of the jump size of the jumps in the price and of the presence of additional independent or dependent jumps in the volatility.We find that the finite sample performance of realised variance and, in particular, of log--transformed realised variance is generally good, whereas the jump--robust statistics tend to struggle in the presence of a highly active jump process.Finally, we investigate the impact of jumps on inference on volatility empirically, where we study high frequency data from the Standard & Poor’s Depository Receipt (SPY).

KW - Realised variance

KW - inference

KW - stochastic volatility

KW - jumps

U2 - 10.1007/s10182-011-0158-1

DO - 10.1007/s10182-011-0158-1

M3 - Journal article

VL - 95

SP - 253

EP - 291

JO - A St A - Advances in Statistical Analysis

JF - A St A - Advances in Statistical Analysis

SN - 1863-8171

IS - 3

ER -