Search Results (224)

This study investigates the dynamic relationship between bearing gearbox condition indicators (BGCIs) and the lubrication oil temperature within the framework of health and usage monitoring system (HUMS) applications. Using the dynamic autoregressive distributed lag (DARDL) simulation model, we quantified both the short- and long-term responses of condition indicators to shocks in oil temperature, offering a robust framework for a counterfactual analysis. To complement the time-domain perspective, we applied a wavelet coherence analysis (WCA) to explore time–frequency co-movements and phase relationships between the condition indicators under varying operational regimes. The DARDL results revealed that the ball energy, cage energy, and inner and outer race indicators significantly increased in response to the oil temperature in the long run. The WCA results further confirmed the positive association between oil temperature and the condition indicators under examination, aligning with the DARDL estimations. The DARDL model revealed that the ball energy and the inner race energy have statistically significant long-term effects on the oil temperature, with p-values < 0.01. The adjusted R² of 0.785 and the root mean square error (MSE) of 0.008 confirm the model’s robustness. The wavelet coherence analysis showed strong time–frequency correlations, especially in the 8–16 scale range, while the frequency-domain causality (FDC) tests confirmed a bidirectional influence between the oil temperature and several condition indicators. The FDC analysis showed that the oil temperature significantly affected the BGCIs, with evidence of feedback effects, suggesting a mutual dependency. These findings contribute to the advancement of predictive maintenance frameworks in HUMSs by providing practical insights for enhancing system reliability and optimizing maintenance schedules. The integration of dynamic econometric approaches demonstrates a robust methodology for monitoring critical mechanical components and encourages further research in broader aerospace and industrial contexts. Full article

This study examines the relationship between crude oil returns (CRT) and Islamic stock returns (ISR) in BRIC countries during the Global Financial Crisis (GFC), employing wavelet-based comovement analysis and regression models that incorporate both contemporaneous and lagged CRT across 40 cases. The wavelet analysis reveals strong long-term comovement at low frequencies between ISR and CRT during the GFC. Contemporaneous regressions show that increases (decreases) in CRT align with corresponding movements in ISR. Lagged regressions indicate that CRT can predict ISR up to one week ahead for Brazil, Russia, and China, and up to two weeks for India, although the predictive strength weakens beyond this window. These findings challenge the perception that Islamic stocks were immune to the GFC, showing they were affected by global oil market dynamics, albeit with varying degrees of resilience across countries and time horizons. Full article

Environmental sustainability constitutes a strategic priority for Germany, with the circular economy serving a crucial function in its realization. Circular practices foster sustainable development by decreasing reliance on finite resources, minimizing waste, and reducing greenhouse gas (GHG) emissions. The circular economy provides ecological advantages and strengthens economic resilience through the promotion of innovation, enhancement of supply chain efficiency, and creation of green jobs. Complementary measures, including the preservation of natural capital, the enactment of structural economic reforms, and the implementation of environmental taxes, enhance sustainability objectives. Ecosystem conservation enhances carbon absorption, structural changes facilitate low-emission industries, and environmental taxes incorporate environmental costs. In contrast, industrial activity continues to be a significant contributor to GHG emissions, necessitating policy examination. This study analyzes the relationships between the circular economy, natural capital, structural change, environmental taxation, and industrial activities on GHG emissions in Germany from the first quarter of 2010 to the fourth quarter of 2022. The study employs wavelet coherence analysis (WCA), fully modified ordinary least squares (FMOLS), and dynamic ordinary least squares (DOLS), demonstrating that circular economy practices, natural capital, structural changes, and environmental taxes significantly reduce GHG emissions. Conversely, industrial activities continually elevate GHG emissions in Germany. Moreover, WCA further reveals the time–frequency dynamics and co-movement patterns between key variables and GHG emissions, enabling the detection of both short-term and long-term dependencies. The results indicate that enhancing environmental sustainability in Germany could be effectively achieved by mandating the integration of recycled materials within key industrial sectors to improve environmental sustainability, which would help lower resource extraction and related GHG emissions. Full article

This paper investigates systemic tail dependence within the crypto-asset ecosystem by examining interconnectedness across eight major tokens spanning Layer 1 cryptocurrencies, DeFi tokens, stablecoins, and infrastructure/governance assets. We employ a novel partial correlation-based network framework and quantile-specific connectedness measures to examine how co-movement patterns evolve under normal and extreme market conditions from September 2021 to March 2025. Unlike conventional correlation or variance decomposition approaches, our methodology isolates direct, tail-specific transmission channels while filtering out standard shocks. The results indicate strong asymmetries in dependence structures. Systemic risk intensifies during adverse tail events, particularly around episodes such as the Terra/Luna crash, the USDC depeg, and Bitcoin’s 2024 halving cycle. Our analysis shows that ETH, LINK, and UNI are key assets in spreading losses when the market falls. In contrast, the stablecoin DAI tends to absorb some of the stress, helping reduce risk during downturns. These results indicate critical contagion pathways and suggest that regulation targeting protocol-level transparency, liquidity provisioning, and interoperability standards may reduce amplification mechanisms without eliminating interdependence. Our findings contribute to the emerging literature on crypto-systemic risk and offer actionable insights for regulators, DeFi protocol architects, and institutional investors. In particular, we advocate for the incorporation of tail-sensitive network diagnostics into real-time monitoring frameworks to better manage asymmetric spillover risks in decentralized financial systems. Full article

There has been growing interest among investors to include cryptocurrencies in their portfolios because of their diversification potential. However, the diversification role of cryptocurrencies when added to South African bank equities is yet to be determined. This study rigorously evaluates asset co-movement and diversification benefits of integrating cryptocurrencies into South African bank equity portfolios. Using advanced financial engineering techniques, including multi-asset particle swarm optimizer (MA-PSO), random optimizer, and a static equal-weighted portfolio (EWP) model, this study analyzed the dynamic portfolio performance and diversification of cryptocurrencies in the 2017–2024 period. The portfolio performance of the three methods is also compared with the results from the traditional one-period mean–variance optimization (MVO) method. The findings underscore the superiority of dynamic models over static EWP in assessing the impact of cryptocurrency inclusion in bank equity portfolios. While pre-COVID-19 studies identified cryptocurrencies as effective hedges against market downturns, this protective role appears attenuated in the post-COVID-19 era. The dynamic MA-PSO model emerges as the optimal approach, delivering better-diversified portfolios. Consequently, South African portfolio managers must carefully evaluate investor risk tolerance before incorporating cryptocurrencies, with regulators imposing stringent guidelines to mitigate potential losses. Full article

This paper examines the extent of stock-returns’ co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that merges four weight matrices—geographical distance, bilateral trade, sector similarity, and company size—into one global matrix. Our results reveal strong spatial stock-market dependence, show that spatial proximity is better captured by financial-distance measures than by pure geographical distance, and indicate that the weight matrix based on sector similarities outperforms the other linkages in explaining firms’ co-movements. Extending the traditional SAR model, the study simultaneously evaluated cross-country and within-country dependencies, providing insights valuable to investors building optimal portfolios and to policymakers monitoring contagion and systemic risk. Full article

The cosmic time dilation observed in Type Ia supernova light curves suggests that the passage of cosmic time varies throughout the evolution of the Universe. This observation implies that the rate of proper time is not constant, as assumed in the standard FLRW metric, but instead is time-dependent. Consequently, the commonly used FLRW metric should be replaced by a more general framework, known as the Conformal Cosmology (CC) metric, to properly account for cosmic time dilation. The CC metric incorporates both spatial expansion and time dilation during cosmic evolution. As a result, it is necessary to distinguish between comoving and proper (physical) time, similar to the distinction made between comoving and proper distances. In addition to successfully explaining cosmic time dilation, the CC metric offers several further advantages: (1) it preserves Lorentz invariance, (2) it maintains the form of Maxwell’s equations as in Minkowski spacetime, (3) it eliminates the need for dark matter and dark energy in the Friedmann equations, and (4) it successfully predicts the expansion and morphology of spiral galaxies in agreement with observations. Full article

This study seeks to quantify the rising financial linkages between mainland China, Australia, Hong Kong, New Zealand, and the six largest Association of Southeast Asian Nations (ASEAN group). Stock market co-movements would be consistent with growing trade ties. Our sample runs from 2010 through 2022, including the coronavirus pandemic. Markov switching analysis allows for changing effects as we move from periods of low market volatility to periods of high volatility. The results offer support for the premise that growing trade and investment ties between China, Australasia, Hong Kong, and the ASEAN region have been accompanied by significant financial market integration, as reflected in stock market co-movement. US effects are also significant and tend to be stronger during high-volatility episodes. Under low-volatility conditions, Shanghai effects become more important and are significant for all six ASEAN group countries. Full article

Improvements in quality of life, new technologies and population growth have significantly increased energy consumption in Brazil and around the world. The Paris Agreement aims to limit global warming and promote sustainable development, making green hydrogen a fundamental option for industrial decarbonization. Green hydrogen, produced through the electrolysis of water using renewable energy, is gaining traction as a solution to reducing carbon emissions, with the global hydrogen market expected to grow substantially. This study applies the ${\rho }_{DCCA}$ method to evaluate the cross-correlation between the green hydrogen market and various financial assets, including the URTH ETF, Bitcoin, oil futures, and commodities, revealing some strong positive correlations. It highlights the interconnection of the green hydrogen market with developed financial markets and digital currencies. The cross-correlation between the green hydrogen market and the index representing global financial markets presented a value close to 0.7 for small and large time scales, indicating a strong cross-correlation. The green hydrogen market and Bitcoin also presented a cross-correlation value of 0.4. This study provides valuable information for investors and policymakers, especially those concerned with achieving sustainability goals and environmental-social governance compliance and seeking green assets to protect and diversify various traditional investments. Full article

It is possible to formulate an immiscible and incompressible two-phase flow in porous media in a mathematical framework resembling thermodynamics based on the Jaynes generalization of statistical mechanics. We review this approach and discuss the meaning of the emergent variables that appear, agiture, flow derivative, and flow pressure, which are conjugate to the configurational entropy, the saturation, and the porosity, respectively. We conjecture that the agiture, the temperature-like variable, is directly related to the pressure gradient. This has as a consequence that the configurational entropy, a measure of how the fluids are distributed within the porous media and the accompanying velocity field, and the differential mobility of the fluids are related. We also develop elements of another version of the thermodynamics-like formalism where fractional flow rather than saturation is the control variable, since this is typically the natural control variable in experiments. Full article

Wavelet coherence analysis (WCA) examines the dynamic interactions between economic policy uncertainty (EPU) in Brazil, Chile, Colombia, and Mexico and key external variables, using monthly data from 2010 to 2022. The findings reveal the following: (i) medium-term co-movements (4–16 months) between EPU and global financial indicators, including the Chicago Board Options Exchange (CBOE) Market Volatility Index (RVIX), Merrill Lynch Option Volatility Estimate Index (RMOVE), and Global EPU Index (RGEPU), emphasizing the sustained influence of financial volatility on domestic policy environments, particularly during global turbulence; (ii) significant interactions between EPU and the Climate Policy Uncertainty Index (RCPU) in resource-dependent economies like Brazil and Colombia, with pronounced effects in medium- and long-term horizons; (iii) bidirectional relationships between Brent crude oil prices (RBRENT) and EPU in Brazil, Colombia, and Mexico, where oil price fluctuations shape policy uncertainty, especially during global market disruptions; and (iv) notable co-movements between EPU and the Dow Jones Sustainability World Index (RW1SGI) in Brazil, Chile, and Mexico, highlighting sensitivity to shifts in sustainability-driven markets. These results underscore the need for economic diversification, strengthened financial safeguards, and integrated climate risk management to mitigate external shocks. By exploring the time–frequency dynamics of global uncertainties and domestic policy environments, this study provides actionable insights for fostering resilience and stability in Latin America’s interconnected economies while addressing vulnerabilities to global market volatility and sustainability transitions. Full article

The motivation for this research stems from the United Nations Sustainable Development Goals (UN SDGs), specifically SDGs 7, 11, 12, and 13, which focus on the mitigation of climate change and sustainable economic development. This study examined the impact of renewable energy use, institutional quality, and production expansion on consumption-based carbon dioxide (CCO₂) emissions in BRICS countries (Brazil, Russia, India, China, and South Africa) from 1996 to 2020. To achieve this, we applied advanced econometric techniques, including second-generation cointegration and unit root tests, along with the novel panel method of moments quantile regression (MMQR). The Westerlund cointegration test confirmed the presence of a long-run co-movement among renewable energy usage, economic growth, institutional quality, and environmental quality, suggesting a stable equilibrium relationship between these variables. The results from MMQR reveal that GDP has a positive and statistically significant effect on CCO₂ emissions across all quantiles, indicating that economic expansion contributes to environmental degradation. In contrast, renewable energy consumption and institutional quality show negative and significant impacts on CCO₂ emissions, indicating their mitigating effect on environmental deterioration. As a robustness check, the findings from fixed-effect OLS (FE-OLS), generalized method of moments (GMM), and common correlated effects mean group (CCEMG) estimations broadly confirm the results of MMQR. These findings underscore the importance of renewable energy consumption and strong institutional frameworks in promoting environmental sustainability. Full article

The co-movement of multi-asset markets in emerging markets has become an important determinant for investors seeking diversified portfolios and enhanced portfolio returns. Despite this, studies have failed to examine the determinants of the co-movement of multi-asset markets such as investor sentiment and changing market conditions. Accordingly, this study investigates the effect of investor sentiment on the co-movement of South African multi-asset markets by introducing alternating market conditions. The Markov regime-switching autoregressive (MS-AR) model and Markov regime-switching vector autoregressive (MS-VAR) model impulse response function are used from 2007 March to January 2024. The findings indicate that investor sentiment has a time-varying and regime-specific effect on the co-movement of South African multi-asset markets. In a bull market condition, investor sentiment positively affects the equity–bond and equity–gold co-movement. In the bear market condition, investor sentiment has a negative and significant effect on the equity–bond, equity–property, bond–gold, and bond–property co-movement. Similarly, in a bull regime, the co-movement of South African multi-asset markets positively responds to sentiment shocks, although this is only observed in the short term. However, in the bear market regime, the co-movement of South African multi-asset markets responds positively and negatively to sentiment shocks, despite this being observed in the long run. These observations provide interesting insights to policymakers, investors, and fund managers for portfolio diversification and risk management strategies. That being, the current policies are not robust enough to reduce asset market integration and reduce sentiment-induced markets. Consequently, policymakers must re-examine and amend current policies according to the findings of the study. In addition, portfolio rebalancing in line with the findings of this study is essential for portfolio diversification. Full article

The aim of this work is to demonstrate that all linear derivatives of the tensor algebra over a smooth manifold M can be viewed as specific cases of a broader concept—the operation of derivation. This approach reveals the universal role of differentiation, which simplifies and generalizes the study of tensor derivatives, making it a powerful tool in Differential Geometry and related fields. To perform this, the generic derivative is introduced, which is defined in terms of the quantities $Q_k^{\left(i\right)}\left(X\right)$. Subsequently, the transformation law of these quantities is determined by the requirement that the generic derivative of a tensor is a tensor. The quantities $Q_k^{\left(i\right)}\left(X\right)$ and their transformation law define a specific geometric object on M, and consequently, a geometric structure on M. Using the generic derivative, one defines the tensor fields of torsion and curvature and computes them for all linear derivatives in terms of the quantities $Q_k^{\left(i\right)}\left(X\right)$. The general model is applied to the cases of Lie derivative, covariant derivative, and Fermi derivative. It is shown that the Lie derivative has non-zero torsion and zero curvature due to the Jacobi identity. For the covariant derivative, the standard results follow without any further calculations. Concerning the Fermi derivative, this is defined in a new way, i.e., as a higher-order derivative defined in terms of two derivatives: a given derivative and the Lie derivative. Being linear derivative, it has torsion and curvature tensor. These fields are computed in a general affine space from the corresponding general expressions of the generic derivative. Applications of the above considerations are discussed in a number of cases. Concerning the Lie derivative, it is been shown that the Poisson bracket is in fact a Lie derivative. Concerning the Fermi derivative, two applications are considered: (a) the explicit computation of the Fermi derivative in a general affine space and (b) the consideration of Freedman–Robertson–Walker spacetime endowed with a scalar torsion field, which satisfies the Cosmological Principle and the computation of Fermi derivative of the spatial directions defining a spatial frame along the cosmological fluid of comoving observers. It is found that torsion, even in this highly symmetric case, induces a kinematic rotation of the space axes, questioning the interpretation of torsion as a spin. Finally it is shown that the Lie derivative of the dynamical equations of an autonomous conservative dynamical system is equivalent to the standard Lie symmetry method. Full article

Stablecoins are crypto assets designed to maintain stable value by bridging fiat currencies and volatile crypto assets. Our study extends previous research by analyzing the instability and co-movement of major stablecoins (USDT, USDC, DAI, and TUSD) during significant economic events such as the COVID-19 pandemic and the collapses of Iron Finance, Terra-Luna, FTX, and Silicon Valley Bank (SVB). We investigated the temporal volatility and dynamic connections between stablecoins using wavelet techniques. Our results showed that the announcement of USDT’s listing on Coinbase in April 2021 significantly impacted the stability of stablecoins, evidenced by a decline in the power spectrum. This phenomenon has not been explored in the literature. Furthermore, the collapse of SVB was highly relevant to the stablecoin market. We observed high coherence between pairs during the pandemic, the Coinbase listing, and the collapse of SVB. After the collapse of Terra-Luna, USDT, USDC, and DAI became more connected in the medium term, with USDC and DAI extending in the long term despite a negative co-movement between USDT and the others. This study highlights the impact of exchange listings on the volatility of stablecoins, with implications for investors, regulators, and the cryptocurrency community, especially regarding the stability and safe integration of these assets into the financial system. Full article