Results 71 to 80 of about 1,307,477 (404)
An Investment and Consumption Problem with CIR Interest Rate and Stochastic Volatility
We are concerned with an investment and consumption problem with stochastic interest rate and stochastic volatility, in which interest rate dynamic is described by the Cox-Ingersoll-Ross (CIR) model and the volatility of the stock is driven by Heston’s ...
Hao Chang, Xi-min Rong
doaj +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani+4 more
wiley +1 more source
A materials and device design concept that comprises a self‐assembled ultra‐thin epitaxial ion‐transporting layer, an amorphous oxide overcoat oxygen‐blocking layer, and a partial filament formed during an electroforming step is proposed for low‐current multilevel resistive switching devices.
Ming Xiao+17 more
wiley +1 more source
This paper prepared for the Handbook of Statistics (Vol.14: Statistical Methods in Finance), surveys the subject of stochastic volatility. the following subjects are covered: volatility in financial markets (instantaneous volatility of asset returns, implied volatilities in option prices and related stylized facts), statistical modelling in discrete ...
Ghysels, E., Harvey, A., Renault, E.
openaire +1 more source
Geometric multi‐bit patterning based on dynamic wetting and dewetting phenomena creates roulette‐like Physical Unclonable Function (PUF) labels with stochastic yet deterministic properties. This method leverages the solutal‐Marangoni effect for high randomness while achieving deterministic multinary patterns through polygonal confinement of binary ...
Yeongin Cho+8 more
wiley +1 more source
ESTIMASI VALUE AT RISK MENGGUNAKAN VOLATILITAS DISPLACED DIFFUSION
Value at Risk (VaR) is a measure of risk that is able to calculate the worst possible loss that can occurs to stock prices with a certain level of confidence and within a certain period of time. The purpose of this study was to determine the VaR estimate
MIRANDA NOVI MARA DEWI+2 more
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Computational Modeling of Reticular Materials: The Past, the Present, and the Future
Reticular materials are advanced materials with applications in emerging technologies. A thorough understanding of material properties at operating conditions is critical to accelerate the deployment at an industrial scale. Herein, the status of computational modeling of reticular materials is reviewed, supplemented with topical examples highlighting ...
Wim Temmerman+3 more
wiley +1 more source
Pricing Arithmetic Asian Options under Hybrid Stochastic and Local Volatility
Recently, hybrid stochastic and local volatility models have become an industry standard for the pricing of derivatives and other problems in finance. In this study, we use a multiscale stochastic volatility model incorporated by the constant elasticity ...
Min-Ku Lee+2 more
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PERHITUNGAN VALUE AT RISK DENGAN PENDUGA VOLATILITAS STOKASTIK HESTON
Value at risk is a method that measures financial risk of an security or portfolio. The aims of the research is to find out the value at risk of an exchange rate using the Heston stochastic volatility model. Heston model is a strochastic volatility model
DESAK PUTU DEVI DAMIYANTI+2 more
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Multiple time scales and the exponential Ornstein-Uhlenbeck stochastic volatility model [PDF]
We study the exponential Ornstein-Uhlenbeck stochastic volatility model and observe that the model shows a multiscale behavior in the volatility autocorrelation. It also exhibits a leverage correlation and a probability profile for the stationary volatility which are consistent with market observations. All these features make the model quite appealing
arxiv +1 more source