Probability distribution of returns in the Heston model with stochastic volatility* [PDF]
, 2002 Adrian A. Drǎgulescu +1 more
openalex +3 more sources
Modelling fluctuations of financial time series: from cascade process to stochastic volatility model [PDF]
, 2000 J. F. Muzy, J. Delour, Emmanuel Bacry
openalex +1 more source
AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing
Advanced Intelligent Discovery, EarlyView.AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley +1 more source
Stochastic volatility models: conditional normality versus heavy-tailed distributions [PDF]
, 2000 Roman Liesenfeld, Robert C. Jung
openalex +1 more source
Bayesian Inference in a Stochastic Volatility Nelson-Siegel Model [PDF]
In this paper, we develop and apply Bayesian inference for an extended Nelson- Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the ...
Fuyu Yang, Nikolaus Hautsch
core
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
Advanced Intelligent Systems, EarlyView.This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen +4 more
wiley +1 more source
On the Optimal Choice of Strike Conventions in Exchange Option Pricing
MathematicsAn important but rarely-addressed option pricing question is how to choose appropriate strikes for implied volatility inputs when pricing more exotic multi-asset derivatives.
Elisa Alòs, Michael Coulon
doaj +1 more source
BUGS for a Bayesian analysis of stochastic volatility models [PDF]
, 2000 Renate Meyer, Jun Yu
openalex +1 more source
Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms
Advanced Intelligent Systems, EarlyView.Codesign is used to implement a neuroscience‐inspired machine learning algorithm in all neuromorphic hardware. In this implementation, the hidden memristors cannot be directly accessed, limiting control of the network during training. By leveraging theoretical tools, including memristor circuits dynamics and a closed form expression for the network ...
Frank Barrows +3 more
wiley +1 more source
Frontiers in Applied Mathematics and StatisticsIn this paper, we explore the applications of fractional stochastic volatility (FSV) models within the realm of market microstructure theory and optimal execution strategies. FSV models extend traditional stochastic volatility frameworks by incorporating
Abe Webb
doaj +1 more source