The extent of correlation or co-movement among the returns of developed and emerging stock markets remains pivotal for efficiently diversifying global portfolios. This correlation is prone to variation over time as a consequence of escalating economi...
The transient responses of distributed energy resources (DERs) in a microgrid are dynamically correlated in spatial and temporal dimensions. Hence, the transient stability prediction in microgrids would require an effective modeling of time-varying c...
Forecasting correlations between stocks and commodities is important for diversification across asset classes and other risk management decisions. Correlation forecasts are affected by model uncertainty, the sources of which can include uncertainty a...
We construct a parsimonious test of constancy of the correlation matrix in the multivariate conditional correlation GARCH model, where the GARCH equations are time-varying. The alternative to constancy is that the correlations change deterministicall...
The paper analyzes the correlation features between stress strength, multiple failure mechanisms, and multiple components. It investigates the effects of different correlation features on reliability and proposes a method for structural reliability a...
When a target moves at hypersonic speed, the aerodynamic thermal effect will cause air molecules to form a plasma sheath that envelopes the outer surface of the target, which consists of a large number of charged particles. The plasma sheath imposes...
This paper examines the role of non-cash flow factors over correlation jumps in financial markets. Utilizing time-varying risk aversion measure as a proxy for investor sentiment and the cross-quantilogram method applied to intraday data, we show that...
This paper proposes a coordinated capacity configuration method for Virtual Power Plant (VPP) distributed resources that considers time-varying power coupling. The method addresses the inadequate economic efficiency and reliability of existing config...
The study examines the time-varying correlation and return spillover mechanism among developed (U.S.) and emerging (BRIC) stock markets during major crises from 2000 to 2023, namely the global financial crisis, COVID-19, and the Russia–Ukraine...
In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that...
This study contributes to the ongoing debate on the size effect and size-based investment styles by investigating the return and volatility spillovers and time-varying conditional correlations among Saudi large-, mid-, and small-cap indices. To this...
In this study, we proposed a new empirical method by combining generalized autoregressive score functions and a copula model with high-frequency data to model the conditional time-varying joint distribution of the government bond yields between Polan...
Although greenhouse microclimates typically exhibit gradual and near-linear transitions, abrupt fluctuations in external weather conditions and actuator operations introduce nonlinear dynamics that complicate accurate interpretation and prediction. P...
Geopolitical factors are considered a crucial factor that makes a difference in crude oil prices. Over the last three decades, many political events occurred frequently, causing short-term fluctuations in crude oil prices. This paper aims to examine...
In this study, a modified non-stationary geometry-based scattering model for tunnel vehicle-to-vehicle (V2V) multiple-input multiple-output Ricean fading channels is presented. The proposed channel introduces non-line-of-sight three-dimensional multi...
Amid the growing debate over how cryptocurrencies are reshaping global finance, this study explores the nexus between Bitcoin, Brent Crude Oil, Gold and the U.S. Dollar Index. We used a time-varying vector autoregressive (tvVAR) model to examine the...
To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimiza...
This study investigates the daily co-movements in commodity prices over the period 2006–2020 using a novel approach based on a time-varying Gerber correlation. The statistic is computed considering a set of probabilities estimated via non-traditional...
This article undertakes a literature review on the topic of market integration, covering over 380 articles from the 1980s to 2024. The review consists of a qualitative analysis for context and a quantitative analysis for content, identifying key rese...
This paper proposes a methodology for building Multivariate Time-Varying STCC–GARCH models. The novel contributions in this area are the specification tests related to the correlation component, the extension of the general model to allow for a...
Unmanned aerial vehicle (UAV) as an aerial base station or relay device is a promising technology to rapidly provide wireless connectivity to ground device. Given UAV’s agility and mobility, ground user’s mobility, a key question is how t...
This paper explores the potential diversification benefits of socially responsible investments for conventional stock portfolios by examining the risk spillovers and dynamic correlations between conventional and sustainability stock indexes from a nu...
The large-scale utilization of wind and solar energy is crucial for achieving carbon neutrality targets. However, as extensive wind and solar power generation is integrated via power electronic devices, the inertia level of power systems continues to...
Using DCC-GARCH model, this paper finds that, since 1990, the relationship between crude oil prices and the US dollar index is time-varying, demonstrating a process of ‘very weak correlation—negative correlation—enhanced negative co...
The main aim of this paper is to examine the dynamic relationship between the three pillars of the economy: unemployment, inflation, and GDP in Ethiopia using the cross-wavelet transform (XWT) analysis, the multivariate Student-t generalized autoregr...
GNSS time series prediction plays a significant role in monitoring crustal plate motion, landslide detection, and the maintenance of the global coordinate framework. Long short-term memory (LSTM) is a deep learning model that has been widely applied...
In this work, an advanced 2D nonparametric correlogram method is presented to cope with output-only measurements of linear (slow) time-varying systems. The proposed method is a novel generalization of the kernel function-based regularization techniqu...
This study examines the daily top 100 cryptocurrencies on Uniswap V3. It denoises the correlation coefficient matrix of cryptocurrencies by using sliding window techniques and random matrix theory. Further, this study constructs a time-varying correl...
Time-varying wind conditions, on which wind turbines depend, significantly influence power generation performance. Accordingly, this study proposes an approach to improve the accuracy of wind power generation prediction by incorporating time-varying...
Interdependence in trade and financial globalization has increased the vulnerability of developed and developing countries to external shocks alike, whereas emerging markets are more vulnerable to the shocks originating from the world’s leading econo...
Time-varying reliability models of multi-cracked beam structures are established in this paper, which provide a theoretical method for the safety evaluation of multi-cracked beam structures. The reliability models proposed in this paper consider the...
Reliability-based robust design methods have been widely used in the field of product design; however, they are difficult to apply to the fatigue reliability design process of rolling bearings due to the problems of determining fatigue accumulated da...
In field harvesting conditions, the non-stationary random vibration characteristics of the harvester are rarely considered, and the results of vibration frequency calculated by different time–frequency transformation methods are different. In t...
Rolling bearings are critical to the normal operation of mechanical systems, which often undergo time-varying working conditions. When the local defects appear on a rolling bearing, the transient impulses will generate and be covered by the strong ba...
The nonlinear mechanical properties of ballasted tracks along railways result in complex dynamics of the vehicle–track systems. Employing localized characterization of ballast and a simplified model might underestimate the vehicle–track s...
The relationship between foreign exchange rates and crude oil prices holds significant importance in comprehending the dynamics of oil markets and their implications for diverse economies. This study utilizes the time-varying copula to examine the in...
This paper takes a four-point contact ball bearing of a wind turbine as the research object, analyzes the force and deformation relationship under the combined action of axial load and radial load, obtains the load distribution of rolling elements, a...
Traditional correlation analysis is analyzed separately in the time domain or the frequency domain, which cannot reflect the time-varying and frequency-varying characteristics of non-stationary signals. Therefore, a time–frequency (TF) correlat...
Underwater signal processing is primarily based on sound waves because of the unique properties of water. However, the slow speed and limited bandwidth of sound introduce numerous challenges, including pronounced time-varying characteristics and sign...
Accurate short-term load forecasting (STLF) is essential for power grid systems to ensure reliability, security and cost efficiency. Thanks to advanced smart sensor technologies, time-series data related to power load can be captured for STLF. Recent...
Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally deriv...
More accurate traffic prediction can further improve the efficiency of intelligent transportation systems. However, the complex spatiotemporal correlation issues in transportation networks pose great challenges. In the past, people have carried out a...
The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes ove...
In engineering, loose sandy (gravelly) strata are often filled with cement-based grout to form a mixed material with a certain strength and impermeability, so as to improve the mechanical properties of sandy (gravelly) strata. The tortuosity effect o...
The aim of this study is to investigate the herding of beta transmission between return and volatility. We have used the dynamic conditional correlation model with the mixed-data sampling (DCC-MIDAS) model for the analysis. The evidence demonstrates...
For this paper, we dynamically analysed the comovements between three major stock markets—Germany, the UK, and the US—and the countries of the European Union, divided into two groups: Eurozone and non-Eurozone. Correlation coefficients ba...
The conventional average acceleration approach relies on K-band range observation, containing an unknown bias, which leads to possible degradation of the precision of Earth’s gravity field modelling. It also suffers from correlated errors cause...
This paper focuses on the time-varying correlation among China’s seven emissions trading scheme markets. Correlation analysis shows a weak connection among these markets for the whole sample period, which spans from 9 June 2014 to 30 June 2017....
For orthogonal frequency division multiplexing (OFDM) systems in high-mobility scenarios, the estimation of time-varying multipath channels not only has a large error, which affects system performance, but also requires plenty of pilots, resulting in...
This paper shows solicitude for the generalized projective synchronization of Caputo fractional-order uncertain memristive neural networks (FOUMNNs) with multiple delays. By extending the constant scale factor to the time-varying function matrix, we...
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