Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
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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 -