Results 141 to 150 of about 22,553 (296)
Advanced Electronic Materials, EarlyView.Through the introduction of a niobium oxide layer into a hafnia ferroelectric capacitor stack, we build a memory device with a strong imprint effect. This imprint leads to a millisecond retention loss that can be tuned by the programming conditions that can be utilized as a scalable, analog hardware time constant for bio‐inspired temporal computing ...
Luca Fehlings +3 more
wiley +1 more source
Block Structure Multivariate Stochastic Volatility Models
Most multivariate variance models suffer from a common problem, the “curse of dimensionalityâ€. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature
Asai, M., Caporin, M.
core +1 more source
Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models. [PDF]
Continuous-time stochastic volatility models are becoming increasingly popular in finance because of their flexibility in accommodating most stylized facts of financial time series.
Emanuele Taufer +2 more
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Existence of solutions of some boundary value problems with stochastic volatility. [PDF]
Heliyon, 2020 Osu BO, Eze EO, Obasi UE, Ukomah HI.
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Quasi-Maximum Likelihood estimation of Stochastic Volatility models. [PDF]
Changes in variance or volatility over time can be modelled using stochastic volatility (SV) models. This approach is based on treating the volatility as an unobserved vatiable, the logarithm of which is modelled as a linear stochastic process, usually ...
Ruiz, Esther
core
Behavioral portfolio decisions in a GARCH world
Financial InnovationThis paper pioneers behavioral portfolio decisions as per prospect theory under a stochastic volatility setting that is exemplified by the use of an affine GARCH model.
Nando Ehler +3 more
doaj +1 more source
Skew selection for factor stochastic volatility models. [PDF]
J Appl Stat, 2020 Nakajima J.
europepmc +1 more source
Advanced Electronic Materials, EarlyView.Resistive memory devices are explored for operation at extremely low temperatures relevant to quantum computing. The study reveals how transistor behavior strongly influences memory performance under cryogenic conditions and introduces an optimized programming strategy.
Emilio Pérez‐Bosch Quesada +11 more
wiley +1 more source
Asymptotic Results for GMM Estimators of Stochastic Volatility Models [PDF]
We derive closed-form expressions for the optimal weighting matrix for GMM estimation of the stochastic volatility model with AR(1) log-volatility, and for the asymptotic covariance matrix of the resulting estimator.
Geert Dhaene, Olivier Vergote
core