Linear State Models for Volatility Estimation and Prediction [PDF]
, 2006 This report covers the important topic of stochastic volatility modelling with an emphasis on linear state models. The approach taken focuses on comparing models based on their ability to fit the data and their forecasting performance.
Date, P, Hawkes, R
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Robust and Compatible Ferroelectric Memories with Polycrystalline TiO2 Channel for 3D Integration
Advanced Electronic Materials, EarlyView.Robust and monolithic 3D compatible ferroelectric memories are realized using the polycrystalline TiO2 channel‐based FeFET. The review covers physical mechanisms of the TiO2 channel FeFET, quantitative benchmarking, and advanced planar/vertical architectures for monolithic 3D integration based on HfO2‐TiO2 gate stack, offering a roadmap for reliable ...
Xujin Song +10 more
wiley +1 more source
Markov Regime Switching of Stochastic Volatility Lévy Model on Approximation Mode
Journal of Applied Mathematics, 2013 This paper deals with financial modeling to describe the behavior of asset returns, through consideration of economic cycles together with the stylized empirical features of asset returns such as fat tails.
Arthit Intarasit
doaj +1 more source
A Locally Both Leptokurtic and Fat-Tailed Distribution with Application in a Bayesian Stochastic Volatility Model. [PDF]
Entropy (Basel), 2021 Lenart Ł, Pajor A, Kwiatkowski Ł.
europepmc +1 more source
Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays
Advanced Electronic Materials, EarlyView.A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter +7 more
wiley +1 more source
Discrete Dynamics in Nature and Society, 2014 Dynamic portfolio choice is an important problem in finance, but the optimal strategy analysis is difficult when considering multiple stochastic volatility variables such as the stock price, interest rate, and income.
Wenjie Bi +3 more
doaj +1 more source
Pricing American Options under Stochastic Volatility: A New Method Using Chebyshev Polynomials to Approximate the Early Exercise Boundary [PDF]
This paper presents a new numerical method for pricing American call options when the volatility of the price of the underlying stock is stochastic.
Elias Tzavalis, Shijun Wang
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Filtering and identification of stochastic volatility for parabolic type factor models [PDF]
, 2006 We consider the dynamics of forward rate process which is modeled by a parabolic type infinite-dimensional factor model with stochastic volatility. The parameters included in the stochastic volatility dynamics are estimated from the factor process as the
Aihara, ShinIchi, Bagchi, Arunabha
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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
Complexity, 2019 This paper presents an extension of double Heston stochastic volatility model by incorporating stochastic interest rates and derives explicit solutions for the prices of the continuously monitored fixed and floating strike geometric Asian options.
Yanhong Zhong, Guohe Deng
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