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Estimating the Value-at-Risk from High-frequency Data
Data augmentation Gibbs sampler Quadratic variation Time changed Brownian motion
2016/1/27
We present two alternative approaches for estimating VaR. Both approaches are based on the observation that each trading day is very diverse and we can observe K different phases of the trading day. W...
Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data
Analyzing the Spectrum Asset Returns Jump Volatility Components High Frequency Data
2014/3/13
This paper reports some of the recent developments in the econometric analysis of semimartingales estimated using high frequency financial returns. It describes a simple yet powerful methodology to de...
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection
Minimum variance portfolio portfolio allocation risk assessment
2010/10/20
Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of selected portfolios among a vast pool of assets, as demonstrated in Fan et al (20...
IS BROWNIAN MOTION NECESSARY TO MODEL HIGH-FREQUENCY DATA?
Semimartingale Brownian motion jumps finite activity infinite activity discrete sampling high frequency
2014/3/13
This paper considers the problem of testing for the presence of a continuous part in a semimartingale sampled at high frequency. We provide two tests, one where the null hypothesis is that a continuou...
Correction to "Leverage and volatility feedback effects in high-frequency data" [J. Financial Econometrics 4 (2006) 353--384]
Leverage volatility feedback effects
2010/10/29
Bollerslev et al. (2006) study the cross-covariances for squared returns under the Heston
(1993) stochastic volatility model. In order to obtain these cross-covariances the authors
use an incorrect ...
A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data
Bias-correction Market microstructure Martingale Measurement error Realized volatility Subsampling
2014/3/13
It is a common practice in finance to estimate volatility from the sum of frequently sampled squared returns. However, market microstructure poses challenges to this estimation approach, as evidenced ...