Search Results (222)

We develop a robust continuous time portfolio optimization framework that incorporates time-varying ESG risk through dynamically evolving drift ambiguity. Building on the equivalence between linear ESG penalties in mean-variance optimization and robust formulations under drift uncertainty, we extend the analysis to a dynamic setting with time-dependent, ESG-weighted ellipsoidal ambiguity sets. The model admits a tractable solution under CRRA preferences: the worst-case drift is obtained in closed form, and the optimal portfolio strategy is characterized as the unique maximizer of an ESG-adjusted Markowitz-type objective at each point in time. Economically, the framework provides a rigorous justification for penalty-based ESG portfolio models, while offering time-consistent robustness, forward-looking risk management, and dynamic hedging against sustainability-related model risk. Full article

This study proposes a hybrid model that integrates Wavelet frequency decomposition, convolutional neural networks (CNNs), and Transformers to predict correlation structures among eight major cryptocurrencies. The Wavelet module decomposes asset time series into short-, medium-, and long-term components, enabling multi-scale trend analysis. CNNs capture localized correlation patterns across frequency bands, while the Transformer models long-term temporal dependencies and global relationships. Ablation studies with three baselines (Wavelet–CNN, Wavelet–Transformer, and CNN–Transformer) confirm that the proposed Wavelet–CNN–Transformer (WCT) consistently outperforms all alternatives across regression metrics (MSE, MAE, RMSE) and matrix similarity measures (Cosine Similarity and Frobenius Norm). The performance gap with the Wavelet–Transformer highlights CNN’s critical role in processing frequency-decomposed features, and WCT demonstrates stable accuracy even during periods of high market volatility. By improving correlation forecasts, the model enhances portfolio diversification and enables more effective risk-hedging strategies than volatility-based approaches. Moreover, it is capable of capturing the impact of major events such as policy announcements, geopolitical conflicts, and corporate earnings releases on market networks. This capability provides a powerful framework for monitoring structural transformations that are often overlooked by traditional price prediction models. Full article

Objective: Preterm birth has been associated with an elevated risk of a broad range of neurodevelopmental impairments, including attentional deficits. This systematic review and meta-analysis aimed to synthesize the existing evidence on sustained and selective attention in school-aged children born preterm. Methods: Following PRISMA guidelines, a comprehensive literature search was conducted across PubMed, Ovid MEDLINE, EMBASE, and Web of Science. Eligible studies included assessments of sustained and/or selective attention in children aged 5–12 years born before 37 weeks of gestation. Data from 15 studies (sustained attention) and 12 studies (selective attention) were analyzed using random-effects meta-analyses. Additionally, subgroup analyses were performed based on gestational age. Results: Preterm-born children showed significantly poorer performance in sustained (Hedges’ g = −0.31, p < 0.001) and selective attention (Hedges’ g = −0.27, p < 0.001) compared to term-born controls. While sustained attention deficits were consistent across all gestational age subgroups, selective attention deficits were more pronounced in very early and extremely early preterm-born children. Moderate to late preterm-born children showed less impairment in selective attention tasks. Conclusions: Preterm birth is associated with measurable and persistent deficits in both sustained and selective attention, with greater vulnerability in children born before 32 weeks of gestation. These findings underscore the importance of implementing early monitoring and intervention strategies specifically designed to support attentional development in this high-risk population. Full article

Background/Objectives: Gait dysfunction is a major contributor to disability and reduced quality of life in Parkinson’s disease (PD). Although pharmacological treatments and exercise-based rehabilitation programs provide partial improvement, residual gait dysfunction often persists. Given these limitations, there has been growing interest in non-pharmacological and non-invasive strategies such as vibration therapy (VT). However, previous systematic reviews and meta-analyses have yielded inconsistent findings, largely summarizing the presence or absence of treatment effects without clarifying the clinical or therapeutic conditions under which VT may be most effective. Therefore, this study aimed to systematically review and synthesize evidence on the efficacy of VT for improving gait in PD and to identify clinical and therapeutic factors influencing treatment outcomes. Methods: A systematic search of PubMed, Web of Science, Embase, and the Cochrane Library was conducted with no restrictions on the search period, including studies published up to July 2025. Eligible studies included randomized and quasi-experimental clinical trials that evaluated the effects of VT on gait-related outcomes in patients with Parkinson’s disease. Data extraction followed the PRISMA 2020 guidelines, and the risk of bias was assessed using the Cochrane RoB 2 and ROBINS-I tools. Multilevel random-effects meta-analyses were conducted to estimate pooled effect sizes for gait outcomes, and meta-regression and subgroup analyses were performed based on disease stage, medication status, and vibration parameters. Results: A total of 14 studies (11 randomized and 3 non-randomized) were included. The pooled analysis showed that VT significantly improved gait performance in PD (Hedges’ g = 0.270, 95% CI: 0.115–0.424; 95% PI: −0.166–0.705). The sensitivity analysis restricted to randomized controlled trials yielded a comparable significant effect (g = 0.316, 95% CI: 0.004–0.628). Greater benefits were observed in patients with higher clinical severity, while the moderating effect of levodopa dosage was not significant. Optimal effects were identified with frequencies of 51–100 Hz, session durations ≤3 min, and 2–3 sessions per week. Improvements were evident in gait speed, cycle, and magnitude, whereas no consistent effects were observed for freezing of gait or gait variability. Conclusions: VT yields small but statistically significant improvements in fundamental gait parameters in Parkinson’s disease, particularly under optimized stimulation conditions and in individuals with greater disease severity. Although the pooled effect was modest and the certainty of evidence was rated as very low according to GRADE, these findings cautiously support the potential of vibration-based interventions as a supportive, non-pharmacological, and non-invasive adjunct within broader rehabilitation programs, rather than as a stand-alone treatment. Full article

This study is designed to investigate the dynamic risk transmission processes between clean energy ETFs and ESG indices in the BRICS countries—Brazil, India, China, and South Africa—while excluding Russia due to the lack of consistent data availability during the study period, which coincides with the Russia–Ukraine conflict. The analysis is conducted on daily data obtained from DataStream, spanning from 27 October 2021 to 5 January 2024. By applying a time-varying parameter vector autoregression (TVP-VAR) modeling framework, we considered examining the global market conditions and economic shocks’ effects on these indices’ interconnectedness, including COVID-19 and geopolitical tensions. In this context, clean energy ETFs turned out to stand as net shock transmitters throughout volatile market spans, while ESG indices proved to act as net receivers. Moreover, we undertook to estimate both of the minimum variance and minimum connectedness portfolios’ hedging efficiency and performance. The findings highlight that introducing clean energy indices into investment strategies helps boost financial outcomes while maintaining sustainability goals. Indeed, the minimum connectedness portfolio consistently delivers superior risk-adjusted returns across varying market circumstances. In this respect, the present study provides investors, regulators, and policymakers with practical insights. Investors may optimize their portfolios by integrating clean energy and ESG indexes, useful for achieving financial and sustainability aims. Similarly, regulators might apply the findings to establish reliable green investment norms and strategies. Thus, this work underscores the crucial role of dynamic portfolio management in optimizing risk and return in the globally evolving green economy. Full article

Background/Objectives: As global aging accelerates, prevalence of mild cognitive impairment (MCI) continues to rise, challenging healthcare systems and diminishing older adults’ quality of life. There is great interest in better understanding the neuroprotective/anti-inflammatory properties of omega-3 polyunsaturated fatty acids but the results from many published studies in humans come to different conclusions. This review aims to clarify the efficacy of n-3 fatty acids as a preventive or therapeutic strategy for cognitive health and to inform future clinical recommendations within aging populations. Methods: Following PRISMA guidelines and a registered PROSPERO protocol, we reviewed systematic reviews (SRs) from 2014 to 2024 assessing exclusive n-3 fatty acid supplementation and cognitive outcomes via MMSE. Data were extracted on intervention details and cognitive scores. Meta-analyses used fixed and random-effects models, with Hedges’ estimating overall impact. Quality was assessed using AMSTAR-2, and statistical analyses were performed (SPSS 28). Results: A total of nine SRs incorporating 14 RCTs were included, representing 26,881 participants aged 40 years or older. The pooled random-effects meta-analysis showed a statistically significant but modest improvement in MMSE scores (effect size: 0.16; 95% CI: 0.01–0.32). Heterogeneity was moderate (I² = 42.8%), and no publication bias was detected. Further analyses revealed no significant associations between treatment duration or dosage and cognitive outcomes, suggesting a threshold effect rather than a dose–response relationship. Conclusions: These findings support n3-PUFA supplementation as a complementary approach to lifestyle-based strategies for cognitive health, including diet, physical activity, sleep optimization, and cognitive training. While benefits appear modest, consistent effects across studies warrant further high-quality research and well-designed studies to strengthen clinical recommendations. Full article

This study explores the new insights into the integration and dynamic asymmetric volatility risk spillovers between Bitcoin, currency pairs (USD/ZAR, GBP/ZAR and EUR/ZAR), and traditional financial assets (ALSI, Bond, and Gold) in South Africa using daily data spanning the period from 2010 to 2024 and employing Time-Varying Parameter Vector Autoregression (TVP-VAR) and wavelet coherence. The findings revealed strengthened integration between traditional financial assets and currency pairs, as well as weak integration with BTC/ZAR. Furthermore, BTC/ZAR and traditional financial assets were receivers of shocks, while the currency pairs were transmitters of spillovers. Gold emerged as an attractive investment during periods of inflation or currency devaluation. However, the assets have a total connectedness index of 28.37%, offering a reduced systemic risk. Distinct patterns were observed in the short, medium, and long term in time scales and frequency. There is a diversification benefit and potential hedging strategies due to gold’s negative influence on BTC/ZAR. Bitcoin’s high volatility and lack of regulatory oversight continue to be deterrents for institutional investors. This study lays a solid foundation for understanding the financial dynamics in South Africa, offering valuable insights for investors and policymakers interested in the intricate linkages between BTC/ZAR, currency pairs, and traditional financial assets, allowing for more targeted policy measures. Full article

As one of the main sources of global greenhouse gas emissions, the low-carbon transformation and emission reduction in the construction industry are inevitable requirements for addressing climate change. Under cap-and-trade regulations, Carbon emission rights have become a key production factor. However, the price of carbon emission rights is highly random. Taking the EU carbon market in 2024 as an example, the carbon price fluctuated by more than 35%, soaring from 65 euros per ton to 80 euros per ton and then falling back. Such sharp fluctuations not only increase the cost uncertainty of enterprises but also complicate the investment decisions for emission reduction. Therefore, enterprises can enhance the flexibility of carbon emission rights trading decisions through option strategies, helping them hedge against the risks of carbon price fluctuations, and at the same time improve market liquidity and risk management capabilities. Against this background, based on the carbon cap-and-trade policy, this paper introduces the two-way option strategy into the construction supply chain game model composed of general contractors and subcontractors, and studies to obtain the optimal carbon reduction volume, carbon option purchase volume, maximum expected profit of general contractors, subcontractors and profit distribution ratio. This study shows that two-way options play a crucial role in optimizing supply decision-making and emission reduction strategies. Under the decentralized model, emission reduction responsibilities are often shifted to subcontractors by the general contractor, resulting in a decline in overall mitigation effectiveness. Furthermore, appropriately lowering the carbon emission benchmark can strengthen enterprises’ incentives for emission reduction and significantly enhance the profitability of the supply chain. The study further suggests that general contractors should enhance their competitiveness by developing environmentally friendly technologies and improving their ability to reduce emissions on their own. Meanwhile, subcontractors need to actively participate in the collaborative efforts through revenue-sharing contracts. This study reveals the strategic value of two-way carbon options in construction supply chain carbon trading and provides theoretical support for the formulation of carbon market policies, contributing to the low-carbon transition of the construction supply chain. Full article

This paper investigates the use of reinforcement learning (RL) algorithms to learn adaptive hedging strategies for derivatives under realistic market conditions, incorporating permanent market impact, execution slippage, and transaction costs. Market frictions arising from trading have been explored in the optimal trade execution literature; however, their influence on derivative hedging strategies remains comparatively understudied within RL contexts. Traditional hedging methods have typically assumed frictionless markets with only transaction costs. We illustrate that the dynamic decision problem posed by hedging with frictions can be modelled effectively with RL, demonstrating efficacy across various market frictions to minimize hedging losses. The results include a comparative analysis of the performance of three RL models across simulated price paths, demonstrating their varying effectiveness and adaptability in these friction-intensive environments. We find that RL agents, specifically TD3 and SAC, can outperform traditional delta hedging strategies in both simplistic and complex, illiquid environments highlighted by 2/3rd reductions in expected hedging losses and over 50% reductions in 5th percentile conditional value at risk (CVaR). These findings demonstrate that DRL agents can serve as a valuable risk management tool for financial institutions, especially given their adaptability to different market conditions and securities. Full article

Using high-frequency financial data, this study investigates volatility spillovers between five renewable energy subsectors (wind, solar, geothermal, bioenergy, and fuel cells), five conventional energy markets (oil, gas, coal, uranium, and gasoline), and carbon emissions for five industrial sectors (power, industry, ground transportation, domestic aviation, and residential) based on a Diebold–Yilmaz VAR-based spillover framework. The results document that the industry and power sectors are the key players in the transmission effects of carbon shocks. In contrast, the reverse is true for the residential and aviation sectors. For renewable energy, fuel cells, and geothermal power, strong forward linkages appear to significantly reduce carbon emissions, while reverse linkages that increase carbon emissions in response to shocks in clean-energy and carbon-intensive industries are relatively high for coal and oil. We also find that the total volatility connectedness exceeds 84%, indicating significant systemic risk transmission. The clean-energy subsectors, particularly wind and solar, now compete in fossil-fuel markets during geopolitical crises. Applying the DCC-GARCH t-copula method to assess portfolio hedging strategies, we find that fuel cell and geothermal assets are the most effective in hedging against volatility in fossil-fuel prices. In contrast, nuclear and gas assets provide benefits from diversification. These results underscore the growing strategic importance of clean energy in mitigating sector-specific emission risks and fostering resilient energy systems in alignment with the United States’ net-zero carbon goals. Full article

Background/Objectives: Spasticity is a common and disabling sequela of stroke that limits voluntary movement and functional recovery. Vibration therapy (VT) has been proposed as a non-invasive neuromodulatory intervention, but the existing studies report inconsistent outcomes due to methodological heterogeneity. This study aimed to evaluate the overall effectiveness of VT in reducing post-stroke spasticity and to identify optimal stimulation parameters via meta-analytic and meta-regression approaches. Methods: A systematic review and meta-analysis were conducted following the PRISMA 2020 guidelines. Standardized effect sizes (Hedges’ g) were calculated based on the within-group pre–post changes and compared across the groups. Meta-regression and subgroup analyses explored seven potential moderators, including the vibration frequency, amplitude, and time since stroke onset. Results: Thirteen randomized controlled trials (RCTs) involving whole-body or focal vibration interventions in stroke populations were included. Vibration therapy significantly reduced spasticity, yielding a moderate overall effect size (Hedges’ g = −0.50; 95% CI: −0.65 to −0.34; p < 0.001). The greatest treatment effects were observed when VT was applied during the late subacute to early chronic phase (6–12 months post-stroke), with low-frequency (<20 Hz) and low-amplitude (≤0.5 mm) stimulation. The frequency, amplitude, and stroke onset emerged as significant moderators (p < 0.05). Conclusions: Vibration therapy is an effective and clinically meaningful intervention for post-stroke spasticity, particularly when delivered with low-intensity parameters during the optimal recovery window. These findings support the development of individualized VT protocols and provide evidence to guide future rehabilitation strategies. Full article

The South African exchange rate has been volatile in recent years affecting the competitiveness of commodities in the market. Consequently, South African agricultural exporters have faced lower profitability or entire losses. More South Africa is among the top agricultural exporters in Africa. Thus, the purpose of this study was to examine the effect of exchange rate volatility on agricultural exports in South Africa using the Exponential Generalized Autoregressive Conditional Heteroskedastic (EGARCH) model over the period extending from first quarter of 2013 to first quarter of 2024. The study finds that the exchange rate affects agricultural export negatively in South Africa. The findings display that the exchange rate is statistically significant in explaining agricultural exports in South Africa. In addition, this study finds interest rate affects agricultural exports negatively whereas investment and trade openness affect agricultural export positively in South Africa. This infers that agricultural exports in South Africa are explained by various economic factors. Therefore, this study proposes implementing currency stabilisation policies is a crucial strategy to reduce exchange rate volatility, thereby reducing the negative impact on agricultural exports in South Africa. The policymakers can use currency hedging as tool to lessen the negative impact associated with the exchange rate volatility. Full article

Futures and forward contracts together offer farmers of all sizes important tools for shifting and managing production risk. This risk shifting is particularly apparent in the U.S. grain complex, where the United States also has a significant export position. Because of this international reach, we argue that the futures and forward markets play a critical role in reducing world food insecurity and thus contribute to satisfying Sustainable Development Goal #2: Zero Hunger. We further argue that the presence of investors willing to take the opposite side of the farmers’ natural short hedge helps futures markets perform their key functions of price discovery and risk management. In addition to these roles, futures markets also enable farmers to finance their crops more efficiently over the production cycle, supporting operational stability. Finally, we highlight that agricultural markets in the United States are supported by significant regulation at the county, state, and federal levels. These farming regulations, coupled with federal oversight of agricultural futures markets, provide sufficient confidence that the goal of Zero Hunger is being pursued in an appropriate and effective manner, reinforcing the case for agricultural futures as a meaningful component of a broader sustainable investment strategy. Full article

Interest in the wine sector focusing on no- or low-alcohol wines is growing. De-alcoholation, typically a post-fermentation process, faces restrictions in some countries and is often quite costly. Using raw materials like low-sugar grapes suitable for this purpose seems logical, yet the literature currently lacks contributions in this area. In this review paper, we outline an ideal ripening process where the goal of producing “low-sugar grapes” can be achieved through various methodologies applied at (i) the whole-canopy level (minimal pruning, hedge mechanical pruning with or without hand finishing, cane pruning combined with high bud load and no cluster thinning, applications of exogenous hormones, late irrigation, and double cropping); (ii) the canopy microclimate level, involving changes in the leaf area-to-fruit ratios (netting, apical or basal leaf removal, late shoot trimming, use of antitranspirants); and (iii) through new technologies (high-yield plots from vigor maps and the adoption of agrivoltaics). However, the efforts in this survey extend beyond merely achieving the production of low-sugar grapes in the vineyard, which is indeed primary but not exhaustive. Therefore, we also explore solutions for obtaining low-sugar grapes while simultaneously enhancing features such as lower acidity, increased phenolics, and aroma potential, which might boost consumer appreciation. The review emphasizes that (i) grapes intended for low-alcohol wine production should not be viewed as a low-quality sector but rather as an alternative endeavour, where the concept of grape quality remains firmly intact and (ii) viticulture for low sugar concentration is a primary strategy, rather than merely a support to dealcoholization techniques. Full article

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article