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,b,c) to examine the importance of jumps, and in particular large and small jumps, using high frequency price returns on 25 … stocks in the DOW 30 and S&P futures index. In particular, we examine jumps from both the perspective of their contribution … of jumps in around 22.8% of the days during the 1993-2000 period, and in 9.4% of the days during the 2001-2008 period …
Persistent link: https://www.econbiz.de/10010282828
,b,c) to examine the importance of jumps, and in particular “large" and “small" jumps, using high frequency price returns on 25 … stocks in the DOW 30 and S&P futures index. In particular, we examine jumps from both the perspective of their contribution … of jumps in around 22.8% of the days during the 1993-2000 period, and in 9.4% of the days during the 2001-2008 period …
Persistent link: https://www.econbiz.de/10009372741
variables. We then provide empirical evidence on "small" and "large" jumps from the perspective of their contribution to overall …, Bollerslev and Diebold (2007) and Aït-Sahalia and Jacod (2009a,b,c). Evidence of jumps is found in around 22.8% of the days … role of jumps is lessening, the role of large jumps has not decreased, and indeed, the relative role of large jumps, as a …
Persistent link: https://www.econbiz.de/10009372773
asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a … number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in …
Persistent link: https://www.econbiz.de/10009771770
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011730304
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011568279
assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …-data models at 5% and 1% VaR level. Specifically, independently from the data frequency, allowing for jumps in price (or providing …
Persistent link: https://www.econbiz.de/10011674479
We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor's 500...
Persistent link: https://www.econbiz.de/10010478989
The focus of the volatility literature on forecasting and the predominance of the conceptually simpler HAR model over long memory stochastic volatility models has led to the fact that the actual degree of memory estimates has rarely been considered. Estimates in the literature range roughly...
Persistent link: https://www.econbiz.de/10011715842
This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump estimators. This combined effect adversely affects...
Persistent link: https://www.econbiz.de/10012063222