Results 51 to 60 of about 1,263,567 (386)
Option Pricing under the Jump Diffusion and Multifactor Stochastic Processes
Journal of Function Spaces, 2019 In financial markets, there exists long-observed feature of the implied volatility surface such as volatility smile and skew. Stochastic volatility models are commonly used to model this financial phenomenon more accurately compared with the conventional
Shican Liu +3 more
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Numerical Simulation of the Heston Model under Stochastic Correlation
International Journal of Financial Studies, 2017 Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing ...
Long Teng +2 more
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Medidas alternativas de volatilidad en el mercado de valores peruano
Revista de Análisis Económico y Financiero, 2019 This document seeks to compare the main volatility calculation methodologies for the Peruvian stock market. Three volatility calculation methods are presented, the EWMA model, the GARCH model and the Stochastic Volatility (SV) model.
Rafael Nivin Valdiviezo
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Asymptotics for Rough Stochastic Volatility Models [PDF]
SIAM Journal on Financial Mathematics, 2016 Using the large deviation principle (LDP) for a rescaled fractional Brownian motion $B^H_t$, where the rate function is defined via the reproducing kernel Hilbert space, we compute small-time asymptotics for a correlated fractional stochastic volatility ...
M. Forde, Hongzhong Zhang
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The Alpha‐Heston stochastic volatility model [PDF]
Mathematical Finance, 2018 We introduce an affine extension of the Heston model, called the α ‐Heston model, where the instantaneous variance process contains a jump part driven by α ‐stable processes with α∈(1,2] .
Y. Jiao +3 more
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AIMS Mathematics, 2023 In general, derivation of closed-form analytic formulas for the prices of path-dependent exotic options is a challenging task when the underlying asset price model is chosen to be a stochastic volatility model.
Min-Ku Lee, Jeong-Hoon Kim
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A Neural Stochastic Volatility Model [PDF]
AAAI Conference on Artificial Intelligence, 2017 In this paper, we show that the recent integration of statistical models with deep recurrent neural networks provides a new way of formulating volatility (the degree of variation of time series) models that have been widely used in time series ...
Rui Luo +3 more
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Model of Continuous Random Cascade Processes in Financial Markets
Frontiers in Physics, 2020 This article presents a continuous cascade model of volatility formulated as a stochastic differential equation. Two independent Brownian motions are introduced as random sources triggering the volatility cascade: one multiplicatively combines with ...
Jun-ichi Maskawa, Koji Kuroda
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Forecasting the Crude Oil Prices Volatility With Stochastic Volatility Models
SAGE Open, 2021 In this article, the stochastic volatility model is introduced to forecast crude oil volatility by using data from the West Texas Intermediate (WTI) and Brent markets.
Dondukova Oyuna, Liu Yaobin
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Population Ecology, EarlyView.Population size and dynamics fundamentally shape speciation by influencing genetic drift, founder events, and adaptive potential. Small populations may speciate rapidly due to stronger drift, whereas large populations harbor more genetic diversity, which can alter divergence trajectories. We highlight theoretical models that incorporate population size
Ryo Yamaguchi +3 more
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