A Study Of Stock Volatility In The Context Of Factor Volatility Models For Large Datasets: Factor Analysis And Forecasting [PDF]
, 2007 PhDThis thesis is a study of stock volatility adopting two factor volatility models for large datasets: the orthogonal GARCH model and the stochastic volatility factor model.
Lui, Sze Wai Silvia
core +2 more sources
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
The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures
Energies, 2019 This paper investigates the impact of jumps in forecasting co-volatility in the presence of leverage effects for daily crude oil and gold futures. We use a modified version of the jump-robust covariance estimator of Koike (2016), such that the estimated ...
Manabu Asai +2 more
doaj +1 more source
“Smelltronics”—From Gas to Smell Sensing
Advanced Materials, EarlyView.The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono +7 more
wiley +1 more source
Estimating and Forecasting Asset Volatility and Its Volatility: A Markov-Switching Range Model [PDF]
This paper proposes a new model for modeling and forecasting the volatility of asset markets. We suggest to use the log range defined as the natural logarithm of the difference of the maximum and the minimum price observed for an asset within a certain ...
Jan Piplack
core
Hybrid fuzzy inference rules of descent method and wavelet function for volatility forecasting. [PDF]
PLoS One, 2022 Alenezy AH +4 more
europepmc +1 more source
Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
Advanced Materials, EarlyView.This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen +7 more
wiley +1 more source
Can Elastomers Combine Stiffness, Toughness and Fatigue Resistance?
Advanced Materials, EarlyView.This review studies how the molecular and macroscopic architecture of elastomers influence their mechanical properties including: stiffness, stretchability, toughness, fatigue resistance, and damping behavior. By linking the structure to performance, it proposes design principles for advanced elastomeric systems that combine mechanical properties ...
Eva Baur, Esther Amstad
wiley +1 more source
Sultan Qaboos University Journal for ScienceThis study examines key characteristics of stock market time series, such as regime shifts and non-linearity, which necessitate specialized methods for capturing market volatility. To improve volatility forecasting for the Muscat Securities Market Index (
Brahim Benaid +2 more
doaj +1 more source
Artificial Neural Network Based Non-linear Transformation of High-Frequency Returns for Volatility Forecasting. [PDF]
Front Artif Intell, 2021 Mücher C.
europepmc +1 more source