Empirical analysis and forecasting of volatility dynamics in high-frequency returns with time-varying components

2009 ◽  
pp. n/a-n/a
Author(s):  
Kasing Man ◽  
Chunchi Wu
Keyword(s):  
Empirical Analysis ◽  
High Frequency ◽  
Time Varying

scholarly journals Frequency variations of gravity waves interacting with a time-varying tide

2013 ◽  
Vol 31 (10) ◽  
pp. 1731-1743 ◽  
Author(s):  
C. M. Huang ◽  
S. D. Zhang ◽  
F. Yi ◽  
K. M. Huang ◽  
Y. H. Zhang ◽  
...  
Keyword(s):  
Gravity Waves ◽  
High Frequency ◽  
Lower Atmosphere ◽  
Horizontal Wind ◽  
Frequency Variation ◽  
Time Varying ◽  
Transient Nature ◽  
Critical Layers ◽  
Favorable Conditions ◽  
Frequency Variations

Abstract. Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs) in a time-varying tide. Our simulations show that when a GW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative) accelerations induce frequency increases (decreases) with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal–GW interactions are more complicated than usually taken into account by GW parameterizations in global models.

scholarly journals COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing

2021 ◽  
Vol 2021 (407) ◽  
Author(s):  
Alexander Chudik ◽  
◽  
M. Hashem Pesaran ◽  
Alessandro Rebucci ◽  
◽  
...  
Keyword(s):  
Empirical Analysis ◽  
Time Varying ◽  
Social Distancing ◽  
Reproduction Numbers

scholarly journals Estimating dynamic copula dependence using intraday data

2015 ◽  
Vol 19 (4) ◽  
Author(s):  
Lidan Grossmass ◽  
Ser-Huang Poon
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
High Frequency ◽  
Time Varying ◽  
Credit Crisis ◽  
Dynamic Copula ◽  
Tick Data ◽  
Out Of Sample ◽  
Intraday Data ◽  
Better Than

AbstractWe estimate the dynamic daily dependence between assets by applying the Semiparametric Copula-Based Multivariate Dynamic (SCOMDY) model on intraday data. Using tick data of three stock returns of the period before and during the credit crisis, we find that our dependence estimator better captures the steep increase in dependence during the onset of the crisis as compared to other commonly used time-varying copula methods. Like other high-frequency estimators, we find that the dependence estimator exhibits long memory and forecast it using a HAR model. We show that for out-of-sample forecasts, our dependence estimator performs better than the constant estimator and other commonly used time-varying copula dependence estimators.

Robust Tracking Time-Varying High-Frequency CW Telegraph Signal

2012 ◽  
Vol 155-156 ◽  
pp. 435-439
Author(s):  
Guo Jun Li ◽  
Xiao Na Zhou ◽  
Nai Qian Liu ◽  
Shao Hua Li
Keyword(s):  
High Frequency ◽  
Continuous Wave ◽  
Impulsive Noise ◽  
Model Simulation ◽  
Time Varying ◽  
Simulation Studies ◽  
Robust Tracking ◽  
Robust Kalman Filter ◽  
Tracking Time ◽  
Nonlinear Statistical Model

Continuous wave (CW) telegraph is a crucial communication means for high-frequency tactical communication. But there is serious frequency deviation and impulsive noise in High-frequency channel, thus the conventional tracking method based on Gaussian noise assumption may lose the track of time-varying CW signal. A new robust kalman filter-based tracker is proposed in this paper to extract the time-varying CW signal in presence of impulsive interference, which uses a nonlinear statistical model. Simulation studies show this method can dynamically track nonstationary CW signal and effectively suppress burst impulse noise.

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