Results 111 to 120 of about 1,459,377 (344)
Advanced Functional Materials, EarlyView.Interphase chemistry governs the stability of multivalent metal batteries. We summarize state‐of‐the‐art developments in calcium and magnesium metal batteries by focusing on the correlation among electrolytes, interphase layers, and the electrochemical performance of corresponding metal anodes.
Huijun Lin +4 more
wiley +1 more source
The forecasting power of EPU for crude oil return volatility
Energy Reports, 2019 Economic policy uncertainty (EPU) has important implications for crude oil market. To explore the implications, this paper investigates the impact of EPU on the crude oil return volatility and which EPU index has the most forecasting power in crude oil ...
Rufei Ma +3 more
doaj +1 more source
A model-free approach to do long-term volatility forecasting and its variants. [PDF]
Financ Innov, 2023 Wu K, Karmakar S.
europepmc +1 more source
Stock market returns, volatility, and future output [PDF]
In this article, Hui Guo shows that, if stock volatility follows an AR(1) process, stock market returns relate positively to past volatility but relate negatively to contemporaneous volatility in Merton’s (1973) Intertemporal Capital Asset Pricing Model.
Hui Guo
core
Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems
Advanced Functional Materials, EarlyView.MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley +1 more source
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
Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility [PDF]
Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors : the model used to forecast volatility, and the method of computing quantiles from the ...
Clements, Michael P. +2 more
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Atomic Layer Deposition in Transistors and Monolithic 3D Integration
Advanced Functional Materials, EarlyView.Transistors are fundamental building blocks of modern electronics. This review summarizes recent progress in atomic layer deposition (ALD) for the synthesis of two‐dimensional (2D) metal oxides and transition‐metal dichalcogenides (TMDCs), with particular emphasis on their enabling role in monolithic three‐dimensional (M3D) integration for next ...
Yue Liu +5 more
wiley +1 more source
An Empirical Study of Asian Stock Volatility Using Stochastic Volatility Factor Model: Factor Analysis and Forecasting [PDF]
This paper is an empirical study of Asian stock volatility using stochastic volatility factor (SVF) model of Cipollini and Kapetanios (2005). We adopt their approach to carry out factor analysis and to forecast volatility.
Silvia S.W. Lui
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Volatility Forecasting and Volatility Risk Premium
Journal of Applied Mathematics and Physics, 2015 Volatility is an important variable in the financial market. We propose a model-free implied volatility method to measure the volatility and test the volatility risk premium. The model-free implied volatility does not depend on the option pricing model, and extracts information from all the option contracts. We provide empirical evidence from the S & P
openaire +2 more sources