Results 51 to 60 of about 291,653 (252)
Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity [PDF]
, 2018 In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the homoskedastic case, become over-identifying and can be tested.
arxiv +1 more source
Chaoticity Properties of Fractionally Integrated Generalized Autoregressive Conditional Heteroskedastic Processes [PDF]
Bulletin of Mathematical Sciences and Applications, 2016 Fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) arises in modeling of financial time series. FIGARCH is essentially governed by a system of nonlinear stochastic difference equations.In this work, we have studied the chaoticity properties of FIGARCH (p,d,q) processes by computing mutual information ...
Adil Yilmaz, Gazanfer Ünal
openalex +2 more sources
The Volatility Spillover of Global Oil Price Uncertainty
International Journal of Energy Economics and PolicyThis manuscript, for the first time, analyses the volatility spillover of oil price uncertainty in the world using data from oil price uncertainty recently developed by Abdul and Qureshi (2023), spanning the time 1996-2019 on a monthly frequency.
Kamil Pícha +5 more
doaj +1 more source
Exploring the Dynamic Links between GCC Sukuk and Commodity Market Volatility
International Journal of Financial Studies, 2018 This study investigates the impact of commodity price volatility (including soft commodities, precious metals, industrial metals, and energy) on the dynamics of corporate sukuk returns.
Nader Naifar
doaj +1 more source
Discussing energy volatility and policy in the aftermath of the Russia–Ukraine conflict
Frontiers in Environmental Science, 2023 The ongoing Russo–Ukrainian War has highly affected energy markets in the EU and worldwide, with different EU- and country-level emergency policy measures being advanced to tackle high energy prices.
Adrian-Gabriel Enescu +1 more
doaj +1 more source
ARCHModels.jl: Estimating ARCH Models in Julia
Journal of Statistical Software, 2023 This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models.
Simon A. Broda, Marc S. Paolella
doaj +1 more source
Agribusiness, EarlyView.Abstract The vegetable market experiences significant price fluctuations due to the complex interplay of trend, cyclical, seasonal, and irregular factors. This study takes Korean green onions as an example and employs the Christiano–Fitzgerald filter and the CensusX‐13 seasonal adjustment methods to decompose its price into four components: trend ...
Yiyang Qiao, Byeong‐il Ahn
wiley +1 more source
Probabilistic Graph Models (PGMs) for Feature Selection in Time Series Analysis and Forecasting
JISR on Computing, 2021 Time series or longitudinal analysis has a very important aspect in the field of research. Day by day new and better analyses are getting developed in this field.
Syed Ali Raza Naqvi
doaj +1 more source
Examining the Financial Impact of Biodiversity‐Related Reputational Disasters
Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT This research investigates the reaction of financial markets to biodiversity‐related corporate events, utilising an EGARCH model to assess the implications on stock returns and volatility. Results reveal that markets significantly respond to these events, demonstrating heightened sensitivity and volatility that underscore the financial ...
Erdinc Akyildirim, Shaen Corbet
wiley +1 more source
Spatial Correlation in Weather Forecast Accuracy: A Functional Time Series Approach [PDF]
arXiv, 2021 A functional time series approach is proposed for investigating spatial correlation in daily maximum temperature forecast errors for 111 cities spread across the U.S. The modelling of spatial correlation is most fruitful for longer forecast horizons, and becomes less relevant as the forecast horizon shrinks towards zero.
arxiv