Results 81 to 90 of about 681,470 (291)
Advanced Materials, EarlyView.Mg─Te chalcogenides address the leakage scaling trade‐off in ultrathin selector‐only memory. Structural partitioning in multiphase Mg─Te, combined with highly ionic Mg─Te bonding and Hf interfacial engineering, supports reliable 5 nm thickness operation at low write voltage with suppressed leakage current, narrow threshold voltage distributions, 10 ns ...
Yoori Seo +5 more
wiley +1 more source
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
Continuous Time Random Walk with Correlated Waiting Times. The Crucial Role of Inter-Trade Times in Volatility Clustering. [PDF]
Entropy (Basel), 2021 Klamut J, Gubiec T.
europepmc +1 more source
Evidence on the Economics of Equity Return Volatility Clustering [PDF]
The underlying economic sources of volatility clustering in asset returns remain a puzzle in financial economics. Using daily equity returns, we study variation in the volatility relation between the conditional variance of individual firm returns and ...
Robert A. Connolly +1 more
core
Volatile Memristive Devices With Tunable Temporal Dynamics For Event‐Based Sensing
Advanced Materials, EarlyView.Tunable volatile memristive devices can serve various neural‐inspired tasks that require different time windows of information retention. The ionic‐based volatility of the presented Pt/a‐STO/TaOx/Ta device stack can be reproducibly and controllably tuned in multiple ways.
Dimitrios Spithouris +7 more
wiley +1 more source
CQEformer: A Causal and Query-Enhanced Transformer Variant for Time-Series Forecasting
MathematicsStructural breaks and volatility clustering are fundamental challenges in time series analysis. We propose CQEformer, an encoder-only Transformer variant for time-series modeling that addresses these challenges via two complementary innovations.
Yuze Tao, Lu Li
doaj +1 more source
Belief merging and revision under social influence: An explanation for the volatility clustering puzzle [PDF]
A share price in a stock market can be thought of as arising out of an aggregation procedure. The price of a stock aggregates many individual beliefs into a collective one, the collective will of the market, so to speak.
Siddiqi, Hammad
core
Advanced Materials, EarlyView.Water harvesting, radiative cooling, and interfacial solar evaporation are fundamentally governed by coupled heat, mass, and light transport processes. These processes are mediated by pore architecture, including pore size, connectivity, and hierarchical organization.
Dejan J. Trajkovski +5 more
wiley +1 more source
Measuring Volatility Clustering in Stock Markets [PDF]
, 2007 We propose a novel method to quantify the clustering behavior in a complex time series and apply it to a high-frequency data of the financial markets. We find that regardless of used data sets, all data exhibits the volatility clustering properties, whereas those which filtered the volatility clustering effect by using the GARCH model reduce volatility
Gabjin Oh +3 more
openaire +2 more sources
Achieving Portfolio Diversification through Cryptocurrencies in European Markets
Business Systems Research, 2019 Background: Cryptocurrencies represent a specific technological innovation in financial markets that keeps getting more and more popular among investors around the world. Given the specific characteristics of the cryptocurrencies, this paper examines the
Pavković Ana +2 more
doaj +1 more source