Distinct Asset Research Articles

Extreme time-frequency connectedness between energy sector markets and financial markets

The renewable energy market has developed into a distinct asset class that has garnered significant attention from investors worldwide. This study investigates the connectedness between the S&P 500 and various energy sectors, including the Green Bond (Green Bond), S&P GSCI Carbon Emission Allowances Index (GSCI EUA), S&P GSCI Biofuel (GSCI Biofuel), and S&P Global Clean Energy Indices (Global Clean Energy). Combining the quantile connectedness approach of Ando et al. (2022) and the spillover index developed by Chatziantoniou et al. (2022), we investigate the quantile time-frequency connectedness among these markets. Our findings reveal that the impact of tail risk spreading to the energy sector during extremely challenging market conditions is significantly amplified. Most tail risk spillovers between the energy sectors involve short-term risk spillovers, as seen by analyzing the frequency domain. The impact of tail risk spillover is stronger during extreme situations, showing a short-term asymmetry. Global Clean Energy and the S&P 500 play important roles in spreading risk to other sectors, known as tail risk spillover. They add to the overall risk that affects the network system. On the other hand, other energy sectors (GSCI EUA and GSCI Biofuel) as well as green bonds act as net recipients by receiving the risk rather than spreading it further, potentially providing portfolio diversification. It is essential to understand how these key players influence risk in the financial system. Utilizing a variety of techniques to assess portfolio performance shows the importance of understanding the return transmission mechanism in the process of developing a portfolio and suggests that Clean Energy, given its relative independence, may make an excellent diversification investment.

How prevalent are suggestive brand names and Distinctive Assets? An AI-human approach

Despite the concept of a suggestive brand name existing for over one hundred years (Viehoever, 1920), the prevalence of suggestive versus non-suggestive brand names has not been documented. Previously, to do so extensively would have taken considerable time and money. We now show that artificial intelligence can replace manual coding with increased accuracy. We found the coding performances of Chat GPT-4 are 34% more accurate than GPT-3.5 and 44% more accurate than human coders. Systematically expanding our research to over 4,600 brands from consumer goods, services, and durables in major English-speaking markets (United Kingdom, United States, and Australia), we find that overall, slightly more than a quarter of all brand names are suggestive - ranging from 10% of durables to 56% of service brands. Further, we expand the suggestiveness research to non-brand name elements of almost 600 Distinctive Assets (e.g., colours, logos) across consumer goods, services, durables, and retailers (in the same three countries), finding that two in five are suggestive. The brand name and Distinctive Asset prevalence distributions are positively skewed, with most categories falling beneath the respective averages. Furthermore, regarding performance, on average, suggestive Distinctive Assets display lower levels of Fame and Uniqueness than non-suggestive Distinctive Assets.

Relationship between the Rainfall Index and Stock/Agri-commodity Market Indices: Empirical Evidence from India

The rainfall, stock, and agri-commodity indices are the economic indicators for Indian economy. Therefore, research is needed to explore the complex relationship between rainfall and economic indicators and its longterm implications. Only a few studies are available on this relationship, and no study gives complete, conclusive evidence on this relationship. Therefore, the present study focused on determining whether there is any relationship between the rainfall index and stock/agri-commodity indices. This study employed the advanced statistical tools like ADF test, correlation, Granger causality test, and GARCH (1,1) model. The research utilized the monthly average rainfall index and the Sensex index from 1991 to 2020. Similarly, the study employed the monthly average Guarex agri-commodity index for the period from 2018 to 2020. The study found that there is no relationship and causality relationship between the rainfall index and the Sensex index. The GARCH (1,1) model shows that the rainfall index has no impact on the volatility of the Sensex index. There is a moderately negative correlation between the rainfall index and the Guarex index, and rainfall affects the volatility of the Guarex index. This shows that the rainfall index can be a distinct asset class that can be traded through rainfall derivatives. In order to launch rainfall derivatives in India, NCDEX and Skeymet Industries have already approached the SEBI for permission.

Bitcoin as a Distinct Asset Class for Hedging and Portfolio Diversification: A DCC-GARCH Model Analysis

Purpose: Bitcoin, the most popular form of virtual currency, currently holds the highest market capitalization among cryptocurrencies and serves as a benchmark for the typical cryptocurrency. The main goal of this research is to evaluate Bitcoin’s potential as a distinct asset class. This will be achieved by building upon previous studies and investigating its utility as both a hedging instrument and a tool for portfolio diversification. Methodology: In this study, Bitcoin is compared with other asset classes, such as key stock indices of India’s Nifty-50 and Sensex, and key currency pairs with the Indian Rupee, including the US dollar ($), Euro (€), Pound sterling (£), and Japanese Yen (¥). Gold, as one of the most precise commodities, is analyzed using descriptive statistics to verify and confirm its properties as a distinct asset class. Additionally, the study employs the DCC-GARCH model to ascertain whether Bitcoin qualifies as both a hedging instrument and a tool for portfolio diversification. Findings: The findings of this study indicate that Bitcoins constitute a unique and separate category within alternative assets and investment classes. Various descriptive statistics confirm that Bitcoins exhibit characteristics of an asset class. Additionally, the study reveals and verifies the hedging and portfolio diversification capabilities of Bitcoin based on the results of the DCC-GARCH model. Practical Implications: The findings of this study will prove useful for investors considering cryptocurrency (Bitcoin) as an alternative asset class for diversifying their portfolios and hedging against volatility. Originality/Value: This study contributes to the research paradigm of Bitcoin finance by providing a perspective from a developing nation on Bitcoin as an asset class, which differs from other asset classes such as Nifty-50, Sensex, USD–INR, EUR–INR, GBP–INR, JPY–INR, and gold. While previous research has predominantly focused on developed nation contexts, this study underscores the importance of examining Bitcoin’s role in portfolio diversification and hedging strategies. To enhance our understanding, this research presents daily observations of recent economic data spanning from 2011 to 2021. Assessing whether Bitcoin qualifies as an alternative investment and a distinct asset class is crucial, as it could significantly influence investment decisions and serve as a valuable tool for risk management and diversification purposes for investors.

Phenomena complexity, disciplinary consensus, and experimental versus correlational research in psychological science.

The target article ignores the crucial role of correlational methods in the behavioral and social sciences. Yet such methods are often mandated by the greater complexity of the phenomena investigated. This necessity is especially conspicuous in psychological research where its position in the hierarchy of the sciences implies the need for both experimental and correlational investigations, each featuring distinct assets.

Depression and assets during the COVID-19 pandemic: A longitudinal study of mental health across income and savings groups.

The prevalence of depression in U.S. adults during the COVID-19 pandemic has been high overall and particularly high among persons with fewer assets. Building on previous work on assets and mental health, we document the burden of depression in groups based on income and savings during the first two years of the COVID-19 pandemic. Using a nationally representative, longitudinal panel study of U.S. adults (N = 1,271) collected in April-May 2020 (T1), April-May 2021 (T2), and April-May 2022 (T3), we estimated the adjusted odds of reporting probable depression at any time during the COVID-19 pandemic with generalized estimating equations (GEE). We explored probable depression-defined as a score of ≥10 on the Patient Health Questionnaire-9 (PHQ-9)-by four asset groups, defined by median income (≥$65,000) and savings (≥$20,000) categories. The prevalence of probable depression was consistently high in Spring 2020, Spring 2021, and Spring 2022 with 27.9% of U.S. adults reporting probable depression in Spring 2022. We found that there were four distinct asset groups that experienced different depression trajectories over the COVID-19 pandemic. Low income-low savings asset groups had the highest level of probable depression across time, reporting 3.7 times the odds (95% CI: 2.6, 5.3) of probable depression at any time relative to high income-high savings asset groups. While probable depression stayed relatively stable across time for most groups, the low income-low savings group reported significantly higher levels of probable depression at T2, compared to T1, and the high income-low savings group reported significantly higher levels of probable depression at T3 than T1. The weighted average of probable depression across time was 42.9% for low income-low savings groups, 24.3% for high income-low savings groups, 19.4% for low income-high savings groups, and 14.0% for high income-high savings groups. Efforts to ameliorate both savings and income may be necessary to mitigate the mental health consequences of pandemics.

Quantile time-frequency connectedness among G7 stock markets and clean energy markets

The rapid growth of clean energy markets as a distinct asset class has attracted significant investor attention. This study examines the interdependence between G7 stock markets and clean energy indices, specifically Renewable Energy Generation (REG), Energy Efficiency (EE), Advanced Materials (AM), and Clean Fuels (CF). Using a state-of-the-art volatility connectedness network and Maximum Overlaps Discrete Wavelet Transform (MODWT), we investigate the quantile time-frequency connectedness among the markets. Our findings reveal strong volatility linkages among all markets, with the exception of Clean Fuels, which has the least connection. We also observe higher dynamic spillover effects under extreme market conditions than normal conditions, with the US market being the most important transmitter of spillovers under bullish markets. Additionally, we highlight the importance of considering the time-varying nature of connectedness, emphasizing the heterogeneity between short-run, medium-run, and long-run transmission. Our study's implications suggest that investors should consider the dynamic nature of spillovers and connectedness when constructing portfolios containing clean energy and G7 stock market assets. The results also imply that the US market's performance has a substantial impact on other markets under bullish conditions, and that Clean Fuels may present an attractive investment opportunity for diversification purposes due to its relative independence.

Framework to assess the resilience of the motorway network in Austria

In the context of ageing of road infrastructure and increasing hazards due to climate change, it is important to allocate available funds for construction works and maintenance such that functionality loss is minimised in its extent and duration. In other words, the aim is to increase the resilience of infrastructure. In this paper, the outcomes of the project REMAIN (REsilient MotorwAy INfrastructure) are presented. Within REMAIN, a framework was developed to assess the resilience of the whole motorway infrastructure in Austria, considering five distinct asset categories: bridges, tunnels, noise barriers, retaining walls, and roadways. The resilience was assessed regarding 18 hazards of natural, technical, and human origin. The framework is designed to provide the motorway operator with a series of performance indicators solely based on resilience aspects. It is intended to constitute an additional decision-making basis for infrastructure maintenance prioritisation, next to already existing indicators, e.g., condition-based indicators. Emphasise was placed on making the framework executable also in cases of limited data availability, however, additional data can be integrated easily. The ability to predict the resilience of the motorway infrastructure of a whole country regarding all major hazards makes the presented framework unique regarding the comprehensiveness of applicability.

Assessing the scientific value and vulnerability of paleontological sites: a new analytic operational procedure

Introduction:Paleontological heritage rarely receives the same legislative attention as archeological heritage. Part of the problem seems to be, at least in some contexts (e.g., Italy), the difficulty of acknowledging fossils as distinct assets from other cultural heritage objects and the lack of expertise among the administrative functionaries. This study aims to describe and test an objective analytic operational procedure that could allow for the assessment of the relevance of any fossiliferous site and its potential vulnerability in its present state.Methods:The estimations were obtained using several quantitative and qualitative parameters that could describe the probability of fossil recovery for each site (Pr) and the scientific and cultural interest of the locality (In). Each parameter has subcategories for better defining. The product of probability and interest results in the scientific value (S), generally expressed as a percentage (S*). The vulnerability index (V) of productive and active sites considers the use of the land (U) and the natural erosion (E). The parameters were thought to apply to any type of fossil locality. We tested the indexes on 22 localities (7 of which were with paleoichnological records and 15 with direct body-fossil evidence), all different from one another.Results:The results show that the proposed indexes well describe and characterize each locality. Most of the sites are moderately vulnerable (V between 1 and 3) except for large quarry sites (e.g., Pirro Nord, Italy and Solnhofen, Germany) whose vulnerability indexes fell in the maximum degree of risk.Discussion:The operational procedure presented here is a simple, objective, and remotely applicable method allowing paleontologists and non-expert personnel to categorize localities and, therefore, act as a base to plan actions in paleontological heritage management relative to territorial development and land use.

Understanding How the Unique Context of the Minnesota Zoo Shapes Our Local Conservation Initiatives

The field of wildlife conservation is comprised of a variety of players with different contexts and approaches. Zoos and aquariums, historically largely focused on public entertainment, are shifting more towards conservation-minded missions and can play a unique role in wildlife conservation by leveraging their distinct assets. The Minnesota Zoo is an AZA-accredited institution and an agency of the State of Minnesota that has been conducting wildlife conservation for over 40 years. Here, we review our current portfolio of local field projects, including initiatives targeting pollinators, native mussels, turtles, and bison, using several considerations to structure and better understand how our unique context has shaped our work. Our designation as a state agency has impacted our initiatives by necessitating a focus on local efforts and has facilitated many partnerships with other government agencies. Indeed, partnerships have been vital to our success and have shaped our programs significantly since their inception. All of the Zoo’s conservation initiatives are built on a bedrock of sound science, and we continue to contribute to the field through research, utilizing the expertise of department staff. In addition, the various funding streams that support our programs have dramatically shaped our work and have created some siloing of staff within the department. However, grant funding can serve as a buffer against the impacts of economic uncertainty, as evidenced during the COVID-19 pandemic. Lastly, our programs have expanded and our objectives have pivoted over the years in response to changing needs and opportunities; such flexibility—and increased flexibility for our staff—is imperative to the future success of these efforts. The Minnesota Zoo’s narrative is unique and helps us understand how we can continue to most effectively carry out local conservation efforts. As we work to protect habitats and save species from extinction, it is important to utilize the distinct assets that each organization can contribute in order to have the greatest collective impact.

Time-varying price dynamics of clean and dirty energy portfolios

This paper investigates the dynamic relationships between four key instruments related to clean and dirty energy assets: WTI futures, United States Oil Fund (USO), EnergySelect Sector SPDR Fund (XLE), and iShares Global Clean Energy ETF (ICLN). Econometric tests confirm a long-term relationship between all variables, with causality tests showing that clean energy ETF has a causal influence on most instruments. However, the causal patterns are not definitively interpretable in an economic framework. Moreover, using wavelet-based tests on a 1-min interval transaction dataset, we further find convergence delay between WTI and XLE, and to a lesser extent, USO, but not ICLN. This suggests that clean energy has the potential to be a distinct asset class. We also identify the time scales at which arbitrage opportunities and liquidity movements occur: 32–256 and 4–8 min, respectively. These are new stylized facts about clean and dirty energy market assets and contribute to the limited literature available on high-frequency dynamics in the said markets.

A Importância dos Eventos Culturais numa Estratégia de Marketing Territorial: O Caso do "Mosteiro de Emoções"

This article analyzes the importance of cultural events in a territorial marketing strategy, presenting the case of Mosteiro das Emoções (Monastery of Emotions) in Cabeceiras de Basto municipality. Emphasizing the existence of resources, attractions, and distinctive assets in the territory, it discusses the ability to identify significant unique elements that enhance initiatives relevant to the affirmation of a destination. The marketing strategy, supported by the marketing-mix, boosts the relevance of cultural events, recognizing their contribution to the territorial brand. The Mosteiro das Emoções, described in this context, is positioned as a strategic and integrating event, constituting an outstanding happening, capable of generating community involvement and attracting visitors, as well as increasing direct or indirect economic benefits and the the acquisition of the territory’s greater visibility and notoriety.

A Tracking Solution of IT Assets and Resources Management

Asset Management is the most crucial factor that needs to be maintained by an organization. It is an orderly action of operating, updating, and maintaining the resources. Its substances in the business section is undoubtedly remarkable. As we know, among the most crucial assets are information and physical assets, and licenses. So, the proper way of asset management is mandatory. This project aims to enhance asset management, which refers to monitoring, tracking, and tagging assets and maintaining them in real-time, so that an organization can adequately manage its IT assets, including hardware and software, concerning risk, governess, business compliance, control, costs, and performance goal set by that organization. It provides notification alerts via e-mail when tagging an asset or checks out. Distinct assets can be search easily by this digital inventory and monitored from a single window. It will provide a view to the user of which asset he has been tagged. It resembles all the criteria of maintaining the standard called ISO 27001.

Are non-fungible tokens (NFTs) different asset classes? Evidence from quantile connectedness approach

The emerging Non-fungible tokens (NFTs) have received investors’ attention as an alternative asset, whereas the nexus between NFTs and major asset classes remains unsettled and emerges as an issue of unquestionable interest. Using a novel Q-Joint spillover model, we explore the quantile connectedness between NFTs and common asset classes. We reveal that return and volatility cross-asset spillovers are much higher in extreme market conditions than that of normal times. The noticeable directional connectedness and results of hierarchical clustering of directional spillovers hint that NFTs should not be considered as a distinct asset class in extreme market conditions.

Tail risk dependence, co-movement and predictability between green bond and green stocks

ABSTRACT This paper examines the coherence of extreme returns between green bonds and a unique set of green stocks. We use the novel quantile cross-spectral coherence methodology of quantile spectral coherency model, cross-quantilogram correlation approach, windowed time-lagged cross-correlation, and windowed scalogram difference models as estimation techniques. The study period spans from 28 November 2008 to 23 September 2020. Our measure of green stocks comprises the constituents of the MSCI Global Environment Price Index: Alternative Energy, Green Building, Pollution Prevention or Clean Technology while our green bond market is proxied by S&P Green Bond Index. We find the dependency between Green Bonds and green stocks to be weak, and this is high during market downturn periods in the short- to medium-term dynamics. This suggests that Green Bonds do act as a hedge, diversifier, or safe-haven instrument for environment portfolio in the short-term, medium-term and long-term dynamics during bearish market conditions. We conclude that green bonds and green stocks are two distinct asset classes with a distinct risk-return profile despite their common climate-friendly nature.

Three-Step Purification and Characterization of Organic Solvent-Tolerant and Alkali-Thermo-Tolerant Xylanase from Bacillus paramycoides T4 [MN370035

In the present study, an extracellular alkali-thermo-tolerant xylanase from Bacillus paramycoides was produced in the presence of an organic solvent. The enzyme was purified by ammonium sulphate precipitation, gel filtration, and ion exchange chromatography, with an overall recovery of 25.9%. The purified enzyme hada 70 kDa molecular weight (MW) confirmed by SDS-PAGE gel analysis. The maximum enzyme activity was reported at 55 °C and pH 7.0. Xylanase activity and stability were improved in the presence of 30% (v/v) n-dodecane, iso-octane, n-decane, and cyclohexane (7 days). The enzyme activity was improved by Co2+, EDTA, and Triton-X-100 while vigorously repressed by Hg2+ and Cu2+. The purified enzyme showed 1.473 mg/mL Km and 654.017 µg/mL/min Vmax values. The distinctive assets of the isolate verified the potential application in the field of biomass conversion into fuel and other industrial processes. Organic solvent-tolerant xylanases can be used for concurrent saccharification and bioethanol production, the amplification of intoxicating beverages, and the fermenting industry.

Modeling and Designing of Rainfall Derivative Contract in India

There has been a prolonged discussion on the use of rainfall derivatives in the Indian conditions. The use of rainfall derivative instruments that could empower the ecosystem of trading and absorbing rainfall risk. The study adopted a unique approach of designing the rainfall indexation based on proposed metrics which is DRD/ERD index, this could be used as building blocks for designing rainfall derivatives similar to HDDs/CDDs underlying temperature derivatives. DRD/ERD values are computed for 36 meteorological subdivisions of India. The basic rainfall future contract structure is defined and analyse how it can reduce the rainfall risk. Like CAT bonds and weather derivatives, rainfall derivatives constitute potentially a distinct asset class and hence could be an added arsenal in the hands of investors for enriching their portfolios.

Health Datasets as Assets: Blockchain-Based Valuation and Transaction Methods.

There is increasing recognition about health-oriented datasets that could be regarded as intangible assets: distinct assets with future economic benefits but without physical properties. While health-oriented datasets - particularly health records - are ascribed monetary value on the black market, there are few established methods for assessing the value for legitimate research and business purposes. The emergence of blockchain has created new commercial opportunities for transferring assets without intermediaries. Therefore, blockchain is proposed as a medium by which research datasets could be transacted to provide future value. For authorized individuals to verify their transactions, blockchain methodologies offer security, auditability, and transparency. The authors share data valuation methodologies consistent with accounting principles and include discussions of black market valuation of health data. Furthermore, this article describes blockchain-based methods of managing real-time payment/micropayment strategies.

Health Datasets as Assets: Blockchain-Based Valuation and Transaction Methods

There is increasing recognition that health-oriented datasets could be regarded as intangible assets: distinct assets with future economic benefits but without physical properties. While health-oriented datasets—particularly health records—are ascribed monetary value on the black market, there are few established methods for assessing value for legitimate research and business purposes. The emergence of blockchain has created new commerce opportunities for transferring assets without intermediaries. Therefore, blockchain is proposed as a medium by which research datasets could be transacted to provide future value. Blockchain methodologies also offer security, auditability, and transparency to authorized individuals for verifying transactions. The authors will share data valuation methodologies consistent with accounting principles and include discussions of black market valuation of health data. Further, this article describes blockchain-based methods of managing real-time payment/micropayment strategies.

Asymmetric, time and frequency-based spillover transmission in financial and commodity markets

The study examines asymmetric, time and frequency-based spillover transmission in financial and commodity markets by employing the VAR-based generalized forecast error variance decomposition framework. Daily prices of S&P-500 and the US Dollar- Euro exchange rate representing the financial markets and WTI, gold, silver, copper, corn and soybean representing the commodity markets for the period ranging from January 6, 2006 to February 25, 2021 are used. The empirical results show that aggregate spillover transmission in financial and commodity markets exhibit asymmetry as downside spillovers dominate upside spillovers. The time-varying spillover asymmetry plot shows that there is a domination of downside spillovers only during crisis events, such as the Global Financial Crisis, the European Debt Crisis and the Covid-19 pandemic. The cross-spillover measures reveal that the inclusion of distinct asset classes, such as corn and soybean with S&P-500 has the potential to reduce the risk associated with the portfolio due to lower cross-spillovers between them. The time and frequency-based spillover transmission results indicate that overall spillovers in financial and commodity markets increase during uncertain market conditions and are mostly driven by shorter horizons. The findings are helpful to various financial market participants and the regulatory authorities.