A universal approach to estimate the conditional variance in semimartingale limit theorems [PDF]
The typical central limit theorems in high-frequency asymptotics for semimartingales are results on stable convergence to a mixed normal limit with an unknown conditional variance. Estimating this conditional variance usually is a hard task, in particular when the underlying process contains jumps.
Mathias Vetter
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Comparing GARCH Models by Introducing Fuzzy Asymmetric Realized GARCH [PDF]
Estimation of conditional variance has lots of application reflecting economic, especially financial economics, social economics and political economics’ risk and volatility research.
Esmaiel Abounoori, Mohammad Amin Zabol
doaj +1 more source
Modeling and Recognition of Driving Fatigue State Based on R-R Intervals of ECG Data
Driving fatigue is an important contributing factor to traffic crashes. Developing a system that monitors the driver's fatigue level in real time and produces alarm signals when necessary, is important for the prevention of accidents. In the past decades,
Linhong Wang, Jingwei Li, Yunhao Wang
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Unobserved component models with asymmetric conditional variances [PDF]
In this paper, unobserved component models with GARCH disturbances are extended to allow for asymmetric responses of conditional variances to positive and negative shocks. The asymmetric conditional variance is represented by a member of the QARCH class of models.
Ruiz, Esther, Broto, Carmen
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Count data models with variance of unknown form: an application to a hedonic model of worker absenteeism [PDF]
We examine an econometric model of counts of worker absences due to illness in a sluggishly adjusting hedonic labor market. We compare three estimators that parameterize the conditional variance?least squares, Poisson, and negative binomial pseudo ...
Delgado, Miguel A., Kniefner, Thomas J.
core +3 more sources
Conditioning Information and Variance Bounds on Pricing Kernels [PDF]
Gallant, Hansen, and Tauchen (1990) show how to use conditioning information optimally to construct a sharper unconditional variance bound (the GHT bound) on pricing kernels. The literature predominantly resorts to a simple but suboptimal procedure that scales returns with predictive instruments and computes standard bounds using the original and ...
Geert Bekaert, Jun Liu
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Suitability of variance shift keying for real conditions [PDF]
This paper investigates the possibility of real-life using the brand new type of digital modulation, which implies the transmission of white Gaussian noise whose variance changes in time. That modulation has been entitled as variance shift keying. The signals obtained on its basis have a high level of transmission security, and they even cannot be ...
Sokolov, R. I., Abdullin, R. R.
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A characterization theorem for matrix variances [PDF]
Some recent papers formulated sufficient conditions for the decomposition of matrix variances. A statement was that if we have one or two observables, then the decomposition is possible. In this paper we consider an arbitrary finite set of observables and we present a necessary and sufficient condition for the decomposition of the matrix variances.
arxiv +1 more source
Conditional sampling for barrier option pricing under the LT method [PDF]
We develop a conditional sampling scheme for pricing knock-out barrier options under the Linear Transformations (LT) algorithm from Imai and Tan (2006).
Derman E.+6 more
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Risk Reduction of Portfolio based on Generalized Autoregressive Conditional Heteroscedasticity Model in Tehran Stock Exchange [PDF]
Return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. The structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. It’s
Gholamreza Eslami Bidgoli+1 more
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