Results 61 to 70 of about 1,307,477 (404)
Multipower Variation and Stochastic Volatility [PDF]
, 2006 In this brief note we review some of our recent results on the use of high frequency financial data to estimate objects like integrated variance in stochastic volatility models. Interesting issues include multipower variation, jumps and market microstructure effects.
Barndorff-Nielsen, Ole Eiler +1 more
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Bootstrapping Non-Stationary Stochastic Volatility [PDF]
SSRN Electronic Journal, 2019 In this paper we investigate how the bootstrap can be applied to time series regressions when the volatility of the innovations is random and non-stationary. The volatility of many economic and financial time series displays persistent changes and possible non-stationarity.
Iliyan Georgiev +5 more
openaire +9 more sources
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
doaj +1 more source
Local volatility under rough volatility [PDF]
arXiv, 2022 Several asymptotic results for the implied volatility generated by a rough volatility model have been obtained in recent years (notably in the small-maturity regime), providing a better understanding of the shapes of the volatility surface induced by rough volatility models, and supporting their calibration power to S&P500 option data. Rough volatility
arxiv
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
semanticscholar +1 more source
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
semanticscholar +1 more source
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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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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Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models [PDF]
, 2016 We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies to substantially accelerate convergence and mixing of ...
G. Kastner +2 more
semanticscholar +1 more source