Results 131 to 140 of about 22,447 (299)
Indirect inference for stochastic volatility models via the log-squared observations. [PDF]
Model; Models; Stochastic volatility; Volatility;
Dhaene, Geert
core
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
Power variation & stochastic volatility: a review and some new results [PDF]
In this paper we review some recent work on limit results on realised power variation, that is sums of powers of absolute increments of various semimartingales.
Svend Erik Graversen +2 more
core
Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses
Advanced Electronic Materials, EarlyView.Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol +7 more
wiley +1 more source
MathematicsAmerican options are more complex to price than European options because they grant holders the right to exercise at any time before expiration, especially in realistic market environments that consider both stochastic volatility and asset price jumps ...
Yu Zhang, Shilong Wang, Longsuo Li
doaj +1 more source
On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility [PDF]
In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be neither a difussion, nor ...
Josep Vives, Elisa Alòs, Jorge A. León
core
Advanced Electronic Materials, EarlyView.In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
Model Selection and Testing of Conditional and Stochastic Volatility Models [PDF]
This paper focuses on the selection and comparison of alternative non-nested volatility models. We review the traditional in-sample methods commonly applied in the volatility framework, namely diagnostic checking procedures, information criteria, and ...
Caporin, M., McAleer, M.J.
core +3 more sources
A TWO FACTOR LONG MEMORY STOCHASTIC VOLATILITY MODEL [PDF]
In this paper we fit the main features of financial returns by means of a two factor long memory stochastic volatility model (2FLMSV). Volatility, which is not observable, is explained by both a short-run and a long-run factor. The first factor follows a
Helena Veiga
core
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
Advanced Electronic Materials, EarlyView.ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source