Asset Performance Research Articles

The Impact of Geopolitical Conflicts on the Volatility of the International Financial Markets

This paper aims to explore the specific impact of geopolitical conflicts on the international financial market. By analyzing the volatility of financial markets, investor sentiment, commodity prices, and the performance of various assets, the short-term and long-term financial impacts of conflict are revealed. Studies show that geopolitical conflicts have a significant impact on global markets, especially in energy and commodity markets, with different volatility effects on different regions and asset classes.

The Impact of Research and Development Investment on the Performance of Portuguese Companies

This study investigates the impact of Research and Development (R&D) investment on the performance of Portuguese companies, specifically addressing the gap in understanding how R&D influences a company’s value and performance. We employ a dynamic panel data model estimated using the Generalized Method of Moments (GMM) to account for potential endogeneity issues. This approach allows us to analyze the influence of R&D investment on the Return on Operating Assets (ROA) for Portuguese companies with significant R&D investments between 2012 and 2019. The analysis reveals that while R&D investment itself may not have a statistically significant short-term impact on ROA, lagged financial performance, leverage, asset turnover ratio, and accounts payable turnover all demonstrate a statistically significant relationship with the dependent variable.

Motivation and Performance Analysis of Spin-offs and Listings: A Case Study of Ningbo-Zhoushan Port

Spin-off and listing is one of the means of contractile asset operation. This paper takes Ningbo Zhoushan Port (hereinafter referred to as Ningbo Port), the first case of "A split A" of China's port and shipping enterprises, as the research object, explores the motivation of Ningbo Port's spin-off and listing of Ningbo China Ocean Shipping(Group) Company (COSCO), and analyzes the risks of the spin-off to enterprises and market investors based on some financial indicators of the parent and subsidiary before and after the spin-off. The results show that from the perspective of the overall spin-off effect, the spin-off effect of Ningbo Port is not significant. From the perspective of the realization of specific motivations, the spin-off of Ningbo COSCO by Ningbo Port conforms to the external development trend and the characteristics of the enterprise in its own mature stage. From the perspective of market reaction, the market is not optimistic about the prospect of this spin-off, and the stock price of Ningbo Port has fallen before and after the spin-off. At the same time, after Ningbo Port spun off Ningbo COSCO and listed, Ningbo Port's control over Ningbo COSCO has declined, which also makes investors worried. This study hopes to provide a reference for the spin-off and listing of Chinese port enterprises in terms of broadening financing channels and reducing market information asymmetry.

Research on the Motivation and Effect of Longfor Group's Transformation to Asset-light Operation Mode

Since the real estate marketization reform in 1998, China's real estate industry has continued to focus on asset operation mode, at that time in the golden period of the industry, real estate enterprises only need to hoard a lot of land, wait for the appreciation of the land and then resell, you can get considerable returns. However, in the context of the current slowdown in the economic growth of China's real estate industry, it is difficult for commercial real estate enterprises to continue to operate with heavy assets, so such enterprises begin to seek transformation, and want to change a profit model to match the current market. As a new way for enterprises to accumulate core competence and maximize value, "asset-light operation" model has been highly valued by the academic and business circles. This paper takes Longfor Group, a representative real estate enterprise, as the research object, and makes an in-depth analysis of the company's finance from the perspective of its financial characteristics and financial performance, in order to provide certain theoretical references for the successful application of the transformation and development of similar companies.

Accounting for bubbles: A discussion of Arif and Sul (2024)

A signal that identifies asset pricing bubbles would be valuable so investors could reposition their portfolios to weather the bubble, yet ex ante bubble identification has proven illusory. Arif and Sul (2024) study whether industry-level investment in net operating asset (NOA) accruals is an ex ante accounting-based signal that predicts bubbles. Using industry-level price run-ups across 49 countries, they find that NOA accruals predict a higher likelihood of a future crash, lower future returns, and larger analyst forecast errors, especially following run-up periods. The authors attribute these patterns to sentiment-driven overinvestment. My discussion summarizes the contributions of Arif and Sul's findings to the asset pricing bubbles, behavioral finance, and aggregate accruals literatures. I also outline empirical challenges faced by studies investigating bubbles and recommend approaches to further strengthen inferences. Finally, I propose opportunities for future research to integrate deeper accounting knowledge into bubble research.

Does accounting information identify bubbles for Fama? Evidence from accruals

Economists have long observed that stock price bubbles are associated with corporate overinvestment. We study the ex-ante identification of bubbles (i.e. stock price booms followed by busts) by examining industry-level investments in net operating asset (NOA) accruals and stock returns for 49 countries around the world. Consistent with overinvestment in operating assets being key to bubble formation, we document five findings: (1) NOA accruals positively forecast the eventual crash of an industry price run-up; (2) NOA accruals negatively forecast stock returns following a run-up; (3) NOA accruals are positively associated with investor sentiment; (4) higher NOA accruals forecast more disappointing earnings relative to analysts’ expectations for run-up industries; and (5) NOA accruals are sharply stronger predictors of crashes, returns and analyst forecast errors following run-ups compared to other periods. Our results provide the first evidence that accounting information identifies stock price bubbles and suggest that financial statements are important for detecting and anticipating industry- and market-level inefficiencies.

The Influence of Asset Valuation, Asset Inventory, and Legal Audit on Asset Optimization

This study aims to fill a gap in the asset management literature by analysing the impact of asset inventory, legal audits, and asset valuation practices on asset optimization. The study involved 106 employees who participated in the completion of the questionnaire. The data was analysed using multiple regressions to test the proposed hypothesis. The results showed that asset inventory has a significant influence on asset optimisation. Asset inventory aims to ensure that company assets are recorded completely and accurately. A legal audit has a significant effect on asset optimisation. The implementation of legal audits to ensure regulatory asset control can increase asset optimisation. Asset valuation has a significant effect on asset optimisation. Consistent and proper asset valuation helps determine market value or tax needs. This research makes an empirical contribution to asset management theory, showing that planning, procurement, operation, and maintenance of assets are necessary to achieve optimisation. The findings provide a foundation for companies to balance policies and best practices to sustainably increase asset value. In addition, these findings are expected to be a reference for further research in the field of asset management and provide practical solutions for other companies facing similar problems.

Fixed Assets Performance with Reference to Ultra Tech Cement

Fixed Assets Performance with Reference to Ultra Tech Cement

A Re-examination of Housing Investment Performance in Nigeria

Arising from the lack of a holistic performance analysis of housing investment in Nigeria, this paper re-examines the return-risk performance of residential property assets by focusing on the tier 1 property markets of Lagos, Abuja, and Port Harcourt. Data on the rental and capital values of residential property assets, comprising bungalows, blocks of flats, and detached houses, from 1999 to 2022 were obtained from estate surveying and valuation firms in the three locations. Mean return and standard deviation were employed to analyse return and risk profiles. Variations in return and risk profiles were further examined using a four-year sub-period analysis. The return-risk ratio was also employed to measure the attractiveness of the investment. The downside risk measure of the Sortino ratio was utilised to determine the risk-adjusted performance of the residential property assets. The results revealed that, on mean return and return-risk tradeoff bases, bungalow investments had superior performance compared with other property types across the geographic areas. When aggregated, residential property assets in Port Harcourt experienced superior return-risk performance relative to other locations. On sub-period analysis, the study established variations in the performance of the residential property assets across time periods and locations. On the risk-adjusted performance measure, it was found that bungalows in Lagos had the highest risk-adjusted performance. Detached house investments across the three locations were also found to exhibit low downside risk-adjusted performance. The study concluded that investors could gain high and attractive returns when making bungalow housing investment decisions with a huge potential for downside risk-proof returns. Moreover, investors could further expand this potential by concentrating more housing investment activities in Port Harcourt, as returns in this location are insulated from downside risk. However, investors should be cautious when investing in detached house assets across the three locations, as returns from this asset might be susceptible to downside risk.

Balancing the maintenance strategies to making decisions using Monte Carlo method

This study aims to develop comprehensive maintenance strategies tailored to enhance the dependability, performance, and lifespan of critical assets within industrial and organizational settings. By integrating proactive, preventive, predictive, and corrective maintenance tactics, our strategy seeks to minimize downtime, reduce costs, and optimize asset performance. Drawing from extensive case studies across various industrial sectors, our research utilizes robust data analysis to inform strategy development.We employ mathematical cost models and simulations using the Monte Carlo Method in MATLAB to evaluate the performance and robustness of different maintenance strategies, including time-based and condition-based approaches. Our findings demonstrate that a holistic maintenance approach significantly improves operational efficiency and asset longevity. Specifically, our analysis reveals that integrated maintenance strategies lead to reduced downtime, lower maintenance costs, and enhanced asset reliability.Policy implications of our research suggest that organizations should adopt integrated maintenance strategies to enhance asset reliability and performance, ultimately achieving sustained operational excellence. By emphasizing the importance of proactive maintenance measures alongside traditional reactive approaches, organizations can effectively manage their critical assets, leading to improved operational outcomes and long-term success.–Integration of proactive, preventive, predictive, and corrective maintenance tactics–Evaluation of performance and robustness through mathematical cost models–Application of the Monte Carlo Method in MATLAB for comparative analysis

Hedging the climate change risks of China's brown assets: Green assets or precious metals?

A large discrepancy exists between the dire impact of climate change projected by most natural scientists and the modest estimates of damages calculated by mainstream economists. In this article, we first measure the climate risk, including the transition and physical risks, in China using textual analysis. Then, considering the heterogeneity of climate change's effect, we investigate the impact of climate risks on the brown and green assets of China (including price, volatility, and correlation) for the period from February 2012 to April 2022. In addition, the performance of China's green assets and international precious metal assets is examined in hedging the climate risk exposure of China's brown assets. The results reveal that transition and physical risks lead to contrary changes in the prices of brown and hedging assets. Transition risk causes the volatility of brown and green assets to change in the opposite direction, while physical risk causes the volatility of the two types of assets to change in the same direction. Under extreme climate risk conditions, the correlation between brown and hedging assets decreases. Finally, the findings show that the performance of international precious metals in hedging climate risk exposure is better than that of China's green equity assets.

Performance evaluation and benchmarking to inform dispatching rules for hydropower plants

Hydropower currently generates more than all other renewable energies combined. Considering the challenges of climate change and the transition to green energy, it is expected to remain the world’s largest source of renewable electricity generation. This paper proposes a tool for performance evaluation and benchmarking of hydropower generation to inform dispatching. Through them, strengths and weaknesses of asset operations can be set, identifying areas with the best performance, gathering insights from their strategies and best practices, and comprehending factors that lead to variations in performance levels. The results allow for optimising energy resource use by indicating the dispatching rules with maximum power production and minimum wear-and-tear impact. This framework allows the formulation of practical guidelines for dispatching policies. The proposed methodology is applied to analyse two real-world case studies: the Vogelgrün run of river hydropower plant (France) and the Frades 2 pump-storage powerplant (Portugal).

Energy Transition: The Impact of Increasing Energy Production from Renewable Sources on the Commercial Optimization Process of Conventional Power Generation Assets

Abstract Changing the way electricity is produced, as part of the energy transition process, brings new challenges to the energy industry and in particular to the power generation practices. The switch from energy systems based on fossil fuels to generation technologies based on renewable sources is proving to be much more complex than expected. Multiple recent studies have shown that the intermittency in renewable production processes is putting pressure on the system and increasing balancing and maintenance costs of the grid, calling for an efficient management of the electricity produced. Therefore, a complete phase-out of conventional power generation units (e.g. coal, gas and nuclear) is still difficult to imagine in practice, mainly because of their role in balancing the system during the hours when renewables are not available (e.g. no wind, no sun or reduced hydraulicity). From the perspective of technical and commercial management aspects, the operation of conventional assets involves the consideration of multiple constraints (such as a longer operating time before they are shut down, or a longer preparation time before they can be restarted) in order to avoid financial loss and further damages. Therefore, the aim of this is to: 1. study the impact brought by the large installed capacity of renewable assets on the energy system; 2. analyse the options for gradual phase-out of conventional assets, from the perspective of system stability; 3. draw conclusions on how the commercial optimization of the production assets should develop as the energy transition advances. The novelty of this paper lies in the fact that it makes a business study of this transition process, which does not really exist yet, and case and simulation studies, along with statistical and time series analysis were used as a methodological approach for the research.

Enhanced Wind Farm Maintenance Scheduling Including Wake Effects

With the expansion and dissemination of offshore wind farms, the costs associated with asset maintenance and operation become ever more relevant. Among maintenance activities, preventive interventions represent a significant share of the costs and, as opposed to corrective interventions, may be calendarized according to the farm operator’s strategy. In an offshore wind farm there is often aerodynamic interaction between different machines, namely as a given upstream turbine extracts energy from the wind, it will necessarily reduce the energy available for a turbine that is downstream in the farm. This is broadly referred to as wake effects. The relative proximity of turbines within a farm means such an interaction results in lower energy yield for downstream turbines. Maintenance activities require the shutdown of the turbine, hence the turbine under maintenance effectively produces no wake effect. It follows that, depending on weather conditions, the sequence of wind turbines to be deactivated for large preventive maintenance campaigns may impact the total energy production of an offshore wind farm, especially when the wind direction is considered. The present study investigates the potential of incorporating wake effects in the scheduling of offshore wind farm maintenance activities, considering a reference farm layout and using historical climate data for a real offshore site. Different maintenance scenarios are considered, including distinct maintenance vessels and different intervention criteria. Results show there is a small but relevant potential gain in energy yield when the maintenance scheduling is determined including wake effects, with annual energy production increase of up to 0.18% for the parametric values considered.

Maintenance & failure data analysis of an offshore wind farm

Offshore Wind (OW) continues to grow globally at a rapid pace, with growth estimates of 630GW by 2050. To facilitate this rapid growth, costs must continue to be reduced. Reducing operations and maintenance (O&M) costs, which are estimated at 30% of the lifetime costs of wind farms, offers opportunity. This could be achieved by moving current maintenance strategies to a prescriptive strategy. Prescriptive strategies use the turbine monitoring data to determine component remaining useful lifetimes or predict failure windows and then provide an optimised maintenance plan. The first stage of a framework, that can be applied to operational assets, for improving maintenance schedules with failure predictions is presented. Analysis of the SCADA system and the maintenance logs, at an operational offshore wind farm (OWF), with the purpose of identifying turbine failure rates, availabilities and losses and costs from maintenance and failures has been performed. The analysis has revealed two types of maintenance actions, one is cost of maintenance driven and the other cost of downtime driven. It is proposed that, given different characteristics, they should be approached differently in the context of failure predictions. It is also revealed that electrical components are critical to the failure rate and energy losses due to maintenance at the OWF. Electrical components represent approximately 28% of all failures and nearly 40% of revenue loss due downtimes from failure for the period analysed. The power converters drive most electrical failures and are of key commercial interest to the farm. As a result, the power converters should be the target for future prognostic model development. The analysis also shows that with perfect prediction and maintenance scheduling, this OWF could generate an extra 0.26% revenue and a generic 1GW OWF could generate an extra 0.6% extra energy and approximately £1.4m in revenue. This analysis did not reveal the benefit of taking fewer maintenance actions, which should be assessed in future work. Producing a combined prognostic maintenance scheduling method will generate extra wind farm revenues, reduce the number of maintenance actions taken and facilitate the work of maintenance teams.

PENGARUH PERTUMBUHAN ASET LABA BERSIH DAN ARUS KAS OPERASI TERHADAP KEBIJAKAN DIVIDEN (STUDI EMPIRIS PADA PERUSAHAAN SEKTOR PERBANKAN DI BURSA EFEK INDONESIA TAHUN 2018-2022)

This study aims to test and obtain empirical evidence regarding the Effect of Asset Growth, Net Profit, and Operating Cash Flow on Dividend Policy. The population in this study are banking sector companies listed on the Indonesia Stock Exchange in 2018-2022. The data used is secondary data using Purposive Sampling sampling techniques. The population used in this study were 45 companies with 13 selected companies with a total sample of 65 data. The analysis technique used in this study is panel data regression. The results of the study show that simultaneously Asset Growth, Net Profit and Operating Cash Flow together affect Dividend Policy. while partially Asset Growth does not affect Dividend Policy where the rise and fall of assets will not affect Dividend Policy, Net Profit has a significant effect on Dividend Policy meaning that net profit can be used as absolute information in predicting dividends that will be received by investors in the current period. While Operating Cash Flow does not have a significant effect on Dividend Policy, this shows that operating cash flow is not the main determining factor in dividend distribution policy.

Application of information technology (IT) in Iraq's petroleum industry

The crucial role of information technology (IT) in operating and managing industrial systems is widely recognized, and Iraq's IT capabilities hold great promise for its industrial and other economic sectors. The demand for IT services has risen considerably, particularly for oil and gas companies, which face the challenge of boosting capital asset returns while ensuring safety and sustainability. They need to manage rising demands as well as competition for access to oil reserves while driving improved asset reliability, productivity, and performance. This application show how information technology is used in the petroleum industry. It specifically examines information technology applications in the upstream, midstream, and downstream important segments of the petroleum industry during the drilling process. The increased price volatility's noteworthy effect on the profitability of the energy industry is just one of the current supply chain management challenges. Better supply chain management aids in lowering operational costs, a challenge that many businesses are under demand to address right away. The study's theoretical and practical value is in exposing the characteristics and issues with the infrastructure supporting the Iraqi oil industry and in creating a control algorithm for the evolution of its Regular visual inspections of pipelines, offshore oil rigs, and other infrastructure may be carried out swiftly and safely thanks to technology. Light devices that enable temperature checks using infrared scanning are available in modern applications. Hazards like poisonous substances can be identified by other sensors from a safe distance. Enhancing oil and gas safety with artificial intelligence technologies protects the environment and ensures worker safety

Flood Risk Exposures and Mortgage-Backed Security Asset Performance and Risk Sharing

Flood Risk Exposures and Mortgage-Backed Security Asset Performance and Risk Sharing

Asset management and risk based process safety management approaches to the energy trilemma

The global energy landscape is transforming towards a carbon-neutral future, necessitating strategic and systematic approaches to address the energy trilemma of security, affordability, and sustainability. Two critical elements of this transformation include the large-scale global adoption of hydrogen for energy use and carbon capture, usage, and storage (CCUS), including carbon sequestration. These efforts require effective management from a lifecycle perspective, considering net emissions and economics, including the life-cycle cost of energy systems, and a risk based process safety (RBPS) management approach that ensures public safety. Embracing asset management principles, which encompass lifecycle management, risk management, and performance optimisation, will be key in facilitating this transition. By analysing energy generation, demand patterns, and storage capacity, optimising the use of renewable energy, systematically, and dynamically monitoring asset performance, and process safety assurance metrics, operators can optimise resource allocation, reduce costs, and improve sustainability and public safety. Furthermore, adopting good risk engineering practices, including RBPS management, will manage risks to as low as reasonably practicable, ensuring a tolerable residual public risk level. This article highlights the correlation between the energy trilemma and asset management practices and suggests practical strategies to manage these major changes by implementing principles of asset management and RBPSmanagement, including a supporting case study.

Urban Resilience Index for Critical Infrastructure: A Scenario-Based Approach to Disaster Risk Reduction in Road Networks

Floods pose a significant threat to road networks globally, disrupting transportation, isolating communities, and causing economic losses. This study proposes a four-stage methodology (avoidance, endurance, recovery, and adaptability) to enhance the resilience of road networks. We combine analysis of constructed assets and asset system performance with multiple disaster scenarios (Reactive Flood Response, Proactive Resilience Planning, and Early Warning Systems). Advanced flood Geospatial-AI models and open data sources pinpoint high-risk zones affecting crucial routes. The study investigates how resilient assets and infrastructure scenarios improve outcomes within Urban Resilience Index (CRI) planning, integrating performance metrics with cost–benefit analysis to identify effective and economically viable solutions. A case study on the Lisbon Road network subjected to flood risk analyzes the effectiveness and efficiency of these scenarios, through loss and gain cost analysis. Scenario 2, Proactive Resilience Planning, demonstrates a 7.6% increase compared to Scenario 1, Reactive Flood Response, and a 3.5% increase compared to Scenario 3, Early Warning Systems Implementation. By considering asset performance, risk optimization, and cost, the study supports resilient infrastructure strategies that minimize economic impacts, while enabling communities to withstand and recover from flood events. Integrating performance and cost–benefit analysis ensures the sustainability and feasibility of risk reduction measures.