Results 61 to 70 of about 15,562 (261)
Markov Kernels Local Aggregation for Noise Vanishing Distribution Sampling
SIAM Journal on Mathematics of Data Science, 2022 A novel strategy that combines a given collection of $π$-reversible Markov kernels is proposed. At each Markov transition, one of the available kernels is selected via a state-dependent probability distribution. In contrast to random-scan type approaches that assume a constant (i.e.
Maire, Florian, Vandekerkhove, Pierre
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A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting
Journal of Forecasting, EarlyView.ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
wiley +1 more source
Entropy, 2004 We define heat kernel measure on punctured spheres. The random field which is got by this procedure is not Gaussian. We define a stochastic line bundle on the loop space, such that the punctured sphere corresponds to a generalized parallel transport on ...
Rémi Léandre
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International Journal of Finance &Economics, EarlyView.ABSTRACT This study aims to classify pivotal fintech innovations and explore the prospects and pitfalls associated with emerging fintech services extensively discussed in the literature. We conducted a multistage systematic review of research published on fintech over the past decade from a technological perspective. Using the Preferred Reporting Items
Muhammad Imran Qureshi, Nohman Khan
wiley +1 more source
A System of Multivariable Krawtchouk Polynomials and a Probabilistic Application
Symmetry, Integrability and Geometry: Methods and Applications, 2011 The one variable Krawtchouk polynomials, a special case of the 2F1 function did appear in the spectral representation of the transition kernel for a Markov chain studied a long time ago by M. Hoare and M. Rahman.
F. Alberto Grünbaum, Mizan Rahman
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An Iterative Reduced KPCA Hidden Markov Model for Gas Turbine Performance Fault Diagnosis
Energies, 2018 To improve gas-path performance fault pattern recognition for aircraft engines, a new data-driven diagnostic method based on hidden Markov model (HMM) is proposed.
Feng Lu +3 more
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Heavy Tailed Approximate Identities and σ-stable Markov Kernels [PDF]
Potential Analysis, 2017 The aim of this paper is to present some results relating the properties of stability, concentration and approximation to the identity of convolution through not necessarily mollification type families of heavy tailed Markov kernels. A particular case is provided by the kernels $K_t$ obtained as the $t$ mollification of $L^{σ(t)}$ selected from the ...
Aimar, Hugo Alejandro +2 more
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Industry Portfolio Volatility Connections and Industry Portfolio Returns
International Journal of Finance &Economics, EarlyView.ABSTRACT This paper tracks dynamic connections that form among daily US industry portfolio return volatilities using a Bayesian time‐varying parameter VAR model. Market participants often focus on sectors to filter vast amounts of information, and this focus results in cross‐industry return predictability. We characterise connections that form over the
Michael Ellington +2 more
wiley +1 more source
Identifiable regional and neural network abnormalities in early childhood anxiety
JCPP Advances, EarlyView.Abstract Background Although the neural underpinnings of anxiety have been investigated, most research has been confined to adolescence and adulthood, with less of a focus on the early childhood period. Little is known about the role of anticipatory fear processing early childhood, which is a sensitive period for anxiety development.
Khalil I. Thompson +7 more
wiley +1 more source
IEEE Access, 2018 Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang +3 more
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