Results 81 to 90 of about 20,255,155 (246)

Fractional Integration and Cointegration in US Financial Time Series Data [PDF]

open access: yes
This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets ...
Luis A. Gil-Alana   +1 more
core  

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

open access: yesAdvanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič   +7 more
wiley   +1 more source

Practical volatility and correlation modeling for financial market risk management [PDF]

open access: yes, 2005
What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics.
Tim Bollerslevb   +7 more
core  

On the linkages between stock prices and exchange rates: evidence from the banking crisis of 2007-2010 [PDF]

open access: yes, 2013
This study examines the nature of the linkages between stock market prices and exchange rates in six advanced economies, namely the US, the UK, Canada, Japan, the euro area, and Switzerland, using data on the banking crisis between 2007 and 2010 ...
Ali, Faek Menla   +9 more
core   +1 more source

A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting

open access: yesData, 2019
Neuro-fuzzy models have a proven record of successful application in finance. Forecasting future values is a crucial element of successful decision making in trading.
Alexander Vlasenko   +4 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

Supervised autoencoder MLP for financial time series forecasting

open access: yesJournal of Big Data
This paper investigates the enhancement of financial time series forecasting with the use of neural networks through supervised autoencoders, aiming to improve investment strategy performance. It specifically examines the impact of noise augmentation and
Bartosz Bieganowski, Robert Ślepaczuk
doaj   +1 more source

Model‐Guided Design of Paper Membrane Architectures for Controlled Flow and Enhanced Diagnostic Sensitivity

open access: yesAdvanced Engineering Materials, EarlyView.
Geometrical modifications on nitrocellulose membranes can result in observable differences in signal intensity relative to a reference membrane (top and bottom left). Using two reference experiments, we have developed a theoretical model that can reproduce the experimentally observed flow changes and provide information on membrane parameters, e.g ...
Maria Dimaki   +2 more
wiley   +1 more source

Testing for Changes in the Unconditional Variance of Financial Time Series [PDF]

open access: yes
Inclan and Tiao (1994) proposed a test for the detection of changes of the unconditional variance which has been used in financial time series analysis.
Andreu Sansó   +2 more
core  

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

open access: yesAdvanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang   +6 more
wiley   +1 more source

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