Results 51 to 60 of about 2,339 (211)
Frontiers in Applied Mathematics and StatisticsThis study addresses the limitations of the Kalman Filter (KF) by extending the application of the Unscented Kalman Filter (UKF) and the variational Bayes method (VBM) for estimating long-memory (LM) volatility models.
Kisswell Basira +2 more
doaj +1 more source
Does the Oil Market Volatility have Long Run Memory? [PDF]
Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2011 This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones ...
Seed Rasekhi, Amir Khanalipour
doaj
A new multivariate nonlinear model to handle the volatility transmission
South African Journal of Industrial Engineering, 2014 Price volatility of stocks is an important issue in stock markets. It should also be taken into account that the stochastic nature of volatility affects decision-makers’ minds to a great extent. Therefore, predicting price volatility could help them make
Ebrahimi, Seyed Babak +1 more
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Discrete Dynamics in Nature and Society, Volume 2026, Issue 1, 2026.Today, the astonishing growth of digital currency has attracted many bold investors. This has caused digital currencies to be gradually introduced as a new asset class with its own criteria. However, the relationship between traditional assets and new assets is not yet deeply understood. This study’s objective is to investigate the dynamic relationship
Farzaneh Shams Tarnabi, Fabio Tramontana
wiley +1 more source
Volatility forecasts: a continuous time model versus discrete time models [PDF]
, 2006 This paper compares empirically the forecasting performance of a continuous time stochastic volatility model with two volatility factors (SV2F) to a set of alternative models (GARCH, FIGARCH, HYGARCH, FIEGARCH and Component GARCH).
Veiga, Helena
core +1 more source
Journal of Futures Markets, Volume 45, Issue 8, Page 917-945, August 2025.ABSTRACT This paper investigates the economic consequences for Bitcoin options' prices of a long memory in conditional volatility and conditional non‐normality of Bitcoin returns. The arbitrage‐free prices of Bitcoin options are determined by market consistent valuation and the conditional Esscher transform. Monte Carlo estimates for option prices from
Tak Kuen Siu
wiley +1 more source
Spatial and spatiotemporal volatility models: A review
Journal of Economic Surveys, Volume 39, Issue 3, Page 1037-1091, July 2025.Abstract Spatial and spatiotemporal volatility models are a class of models designed to capture spatial dependence in the volatility of spatial and spatiotemporal data. Spatial dependence in the volatility may arise due to spatial spillovers among locations; that is, in the case of positive spatial dependence, if two locations are in close proximity ...
Philipp Otto +4 more
wiley +1 more source
Discrete Dynamics in Nature and Society, Volume 2018, Issue 1, 2018., 2018 Memory in finance is the foundation of a well‐established forecasting model, and new financial theory research shows that the stochastic memory model depends on different time windows. To accurately identify the multivariate long memory model in the financial market, this paper proposes the concept of a moving V‐statistic on the basis of a modified R/S
Peng Zheng +3 more
wiley +1 more source
Forecasting West Texas Intermediate Crude Oil Price: Stochastic Differential Approach [PDF]
مدلسازی اقتصادسنجی, 2018 Uncertainty in oil markets has led economic researchers to the use of stochastic processes. The purpose of this paper, is the use of stochastic differential models to predict the crude oil price of West Texas Intermediate (WTI) and compare the ...
ramin khochiani, younes nademi
doaj +1 more source
Modelling Volatility Cycles: The MF2‐GARCH Model
Journal of Applied Econometrics, Volume 40, Issue 4, Page 438-454, June/July 2025.ABSTRACT We propose a novel multiplicative factor multi‐frequency GARCH (MF2‐GARCH) model, which exploits the empirical fact that the daily standardized forecast errors of one‐component GARCH models are predictable by a moving average of past standardized forecast errors.
Christian Conrad, Robert F. Engle
wiley +1 more source