Value Of Assets Research Articles

BIOLOGICAL ASSETS OF ORGANIC PRODUCTION IN THE SYSTEM OF ACCOUNTING CATEGORIES AND CONCEPTS

The present article is dedicated to the pertinent issue of accounting for biological assets in the context of organic production. A critical analysis of extant theoretical approaches to the definition, recognition and valuation of biological assets has been conducted. The research revealed the absence of a proper accounting system for organic production objects, particularly biological assets, both in Ukraine and in international accounting practice. The primary issue identified pertains to the inconsistency of terminology and the definitions of categories employed in accounting, along with their ambiguous interpretation in regulatory acts. The purpose of the present article is to define key terms for the accounting of biological assets, taking into account the specifics of organic agricultural production. The object of research is land and biological assets of organic production. The subject of the study is the theoretical, methodological and practical aspects of accounting for biological assets in organic production. The following methodological approaches were utilised in the study: theoretical analysis (for systematisation of literary and regulatory sources), comparative analysis (for identifying discrepancies and comparing methodologies), systems approach (for identifying biological assets in the accounting system), and generalisation method (for drawing conclusions and defining terminology). An analysis has been conducted of the state and trends of organic production development on a global, European, and Ukrainian scale. It has been established that the positive impact of organic production on the ecosystem is not taken into account by traditional accounting methods. The foundation of the agroecosystem is agricultural land, which is a strategic resource for Ukraine and an indispensable tool for agricultural producers. The specific characteristics of this asset include biological processes and transformations that occur with it and affect its fertility, as well as the absence of a defined useful life and depreciation. Agricultural land constitutes an element of natural capital with the capacity for biological assimilation. The article under discussion herein justifies the necessity to integrate agricultural land into the category of biological assets. The integration of agricultural land into the category of biological assets will facilitate the development of a comprehensive methodology for assessing this type of asset, considering both economic and environmental aspects, including its positive impact on the agroecosystem and the environment. The main results of the study: in order to ensure a unified approach to accounting in organic production, the necessity of developing a separate accounting standard is substantiated. The authors' own definition of the category “biological assets of organic production” is proposed, which takes into account both economic and environmental aspects. The criteria for recognising biological assets of organic production in accounting are determined.

MASIP: A Methodology for Assets Selection in Investment Portfolios

This paper proposes a Methodology for Assets Selection in Investment Portfolios (MASIP) focused on creating investment portfolios using heuristic algorithms based on the Markowitz and Sharpe models. MASIP selects and allocates financial assets by applying heuristic methods to accomplish three assignments: (a) Select the stock candidates in an initial portfolio; (b) Forecast the asset values for the short and medium term; and (c) Optimize the investment portfolio by using the Sharpe metric. Once MASIP creates the initial portfolio and forecasts its assets, an optimization process is started in which a set with the best weights determines the participation of each asset. Moreover, a rebalancing process is carried out to enhance the portfolio value. We show that the improvement achieved by MASIP can reach 147% above the SP500 benchmark. We use a dataset of SP500 to compare MASIP with state-of-the-art methods, obtaining superior performance and an outstanding Sharpe Ratio and returns compared to traditional investment approaches. The heuristic algorithms proved effective in asset selection and allocation, and the forecasting process and rebalancing contributed to further improved results.

Designing a Digital Marketplace Platform for Optimizing the Exchange of Distressed Oilfield Assets in Emerging Markets

The efficient exchange of distressed oilfield assets in emerging markets is a critical challenge due to market inefficiencies, regulatory constraints, and valuation complexities. This study proposes a digital marketplace platform designed to optimize the buying, selling, and repurposing of distressed oilfield assets. By leveraging advanced digital technologies, data analytics, and blockchain, the platform aims to enhance transparency, streamline transactions, and improve asset valuation accuracy. The proposed platform integrates key features such as a secure listing system, automated asset valuation, smart contract-enabled transactions, and real-time market analytics. A structured framework for asset due diligence is incorporated, ensuring compliance with local regulations while mitigating risks associated with asset depreciation and operational inefficiencies. Furthermore, machine learning algorithms are employed to assess asset viability and predict market demand trends. Case studies from emerging markets highlight the existing challenges in distressed oilfield asset transactions, including limited access to buyers, inconsistent valuation methodologies, and bureaucratic hurdles. By implementing a digital marketplace, stakeholders—ranging from oil and gas operators to financial institutions and government agencies—can benefit from increased liquidity, faster asset turnover, and improved investment decision-making. The study also explores the role of blockchain technology in ensuring transaction security and authenticity, reducing fraud, and enhancing contractual enforcement. Smart contracts facilitate automated escrow services, enabling seamless and trust-based transactions. Additionally, real-time data analytics empower market participants with actionable insights for strategic asset acquisition and disposal. This research contributes to the digital transformation of the oil and gas sector by presenting an innovative model for distressed asset management. The findings suggest that an integrated digital marketplace can bridge the gap between asset sellers and potential buyers, fostering a more resilient and dynamic oilfield asset exchange ecosystem. Future research should explore scalability across different energy sectors and assess the regulatory adaptability of blockchain-based transactions.

Pengaruh Ukuran Pemda Dan Tingkat Efisiensi Terhadap Opini Lkpd Studi Pada Pemerintahan Daerah Lampung

Opinion LKPD Lampung still has not received a unqualified opinion in the 2015-2021 fiscal year period. The aim of the research is to test and analyze the influence of regional government size and level of efficiency on local financial statement opinions in the Lampung Regional Government.The observation population of the population in this study is all local governments in Lampung Province, there are 16 regional governments (districts and cities). The research uses secondary data, explanatory descriptive research using binary logistic regression analysis tools. The research period is from 2015 to 2021. The results of testing the first hypothesis show that regional government size has a positive effect on local financial statement opinion, meaning the hypothesis is accepted. The second hypothesis of the level of efficiency shows a negative influence, thus the hypothesis is rejected. Even though the size of the regional government is not large in terms of asset value, it does not necessarily mean that the local financial statement will not receive a unqualified opinion. the results of measuring the level of regional government efficiency concluded that it was not efficient, it does not necessarily mean that the local financial statement did not get a unqualifie opinion.

Quasi-Maximum Likelihood for Estimating Structural Models

Abstract The estimation of the structural model poses a major challenge because its underlying asset (the firm asset value) is not directly observable. We consider an extended structural model that accommodates alternative underlying Markov processes, arbitrary debt payment schedules, several seniority classes, multiple intangible assets, and various intangible corporate securities. We derive the likelihood function given the observed time series of the firm equity values. Then, we use dynamic programming to solve the model and, simultaneously, extract the associated time series of the firm asset values (the pseudo-observations). Finally, the likelihood function is approximated and optimized, which results in the quasi-maximum likelihood (QML) estimates of the model’s unknown parameters. QML is highly flexible and effective. To assess our construction, we perform an empirical investigation, highlight the credit-spread puzzle, and discuss a partial remedy via jumps and bankruptcy costs.

Hyperinflation and its Accounting and Tax Impact on Financial Statements and Disclosures in Zimbabwe, Argentina, Turkey and Egypt

This study examines the financial and tax implications of hyperinflation, analyzing its impact on companies and government policies. Hyperinflation is one of the most severe economic challenges facing emerging markets, leading to significant distortions in financial statements and tax systems. It is characterized by an excessive and rapid increase in price levels, resulting in the collapse of local currency value and creating substantial difficulties for both businesses and governments. This study explores the effects of hyperinflation on financial reporting, asset valuation, tax liabilities, and business decision-making. It highlights the challenges companies face in maintaining accurate financial records, managing cash flows, and complying with tax regulations in inflationary environments. Additionally, the study investigates how governments respond to hyperinflation, particularly concerning monetary policies and tax adjustments. Through case studies from Zimbabwe, Argentina, Turkey, and Egypt, between 2015 to 2024. The research provides practical insights into how businesses and policymakers adapt to hyperinflation.

A time-series stock price prediction and asset portfolio optimization model based on long- and short-term memory networks

Aiming to address shortcomings in existing time series prediction models, this paper proposes an LSTM model enhanced by fused multi-scale convolutional attention (MCA-LSTM). We design the experimental parameters, construct a stock price dataset, and model the improved LSTM using individual stock closing prices, with prediction accuracy evaluated via RMSE, MAPE, and MAD. To assess the arbitrage and generalization performance of the MCA-LSTM portfolio model, we compare the application of the MCA-LSTM-BL model. Furthermore, within the framework of a mean semi-absolute deviation (MSAD) portfolio optimization model, we develop a new portfolio optimization approach based on return forecasting (MCA-LSTM+MSAD). The asset values and return predictions of various portfolio models are analyzed under transaction cost considerations, and the proposed MCA-LSTM+MSAD model achieves an excess return of 56.98%, consistently maintaining the highest portfolio value throughout the trading period. Overall, our findings indicate that the MCA-LSTM+MSAD model is a promising tool for portfolio optimization and warrants further development for real investment applications.

Identifying and Measuring Architectural Design Features for Financial Asset Valuation

In the realm of architectural design and real estate development, a significant tension exists between design and finance. Design, with its emphasis on functionality, aesthetics, and human experience, often struggles to assert its value in a financial landscape dominated by quantifiable metrics. Traditional real estate valuation models frequently overlook the nuanced contributions of architectural design due to the absence of systematic approaches for identifying, measuring, and standardizing architectural data collection. This oversight has profound implications for the built environment, where design decisions must be financially justified to gain acceptance. The widening gap between design and finance in real estate development has fueled a trend toward the increasing financialization of new projects, often at the expense of design innovations that promote health, resilience, and sustainability. As the industry continues to prioritize evidence-based decision-making, there is an urgent need to develop systematic methods for measuring and evaluating design features to better understand their significance and contribution to economic value. This paper identifies and catalogs 19 building design features, surveys existing measurement techniques, and proposes methods for their measurement using existing tools and technologies.

Farmer typology and adoption of improved cassava production technologies in the Eastern Democratic Republic of the Congo

Abstract This study aimed to examine the factors driving the adoption of improved cassava seeds and fertilizers among smallholder farmers in South Kivu and Tanganyika provinces, Eastern Democratic Republic of the Congo (DRC), using data from 1317 farming households. Data were analyzed using principal component analysis (PCA) and cluster analysis by classifying farmers based on their cassava agricultural practices while capturing their preferences, attitudes, and socioeconomic characteristics. Logistic regression was then applied to evaluate the adoption of improved cassava seeds and fertilizers across different farmer-type groups. Therefore, farmers were classified into five distinct groups in both provinces. In general, for cassava-improved seed, farming experience increases its adoption by 15.1% per year in Cluster 5. At the same time, primary education boosts adoption in Cluster 1 by 17.4%, and university education raises it by 20.1% in Cluster 5. Larger land areas significantly enhance adoption by 46.9% in Cluster 4 and 79.6% in Cluster 1, reflecting the benefits of larger farms. Livestock ownership raises adoption by 26.8% in Cluster 1, highlighting the value of assets in agricultural investment. Agriculture training and income are highly effective, improving adoption by 18.2% in Cluster 5 and 8% overall. Specifically, in South Kivu, gender influences fertilizer adoption by 18.0% (Cluster 1) and 14.9% (Cluster 5) while marital status enhances fertilizer adoption and with being married raising the probability by 0.52% (Cluster 4). These findings emphasize the importance of education, gender, income resource access, and targeted interventions to improve agricultural technology adoption. Furthermore, promoting farmer engagement in agricultural activities is recommended through enhanced extension services and cooperative memberships.

Research On Auction Value Assessment Of Finan-cial Non-Performing Assets Based On Bp Neural Network

The proportion and quality of financial non-performing assets is a direct re-flec-tion of the risk management ability of banks and financial institutions. Re-search on the auction value of non-performing assets and the construction of a reliable non-performing asset value assessment model can help improve the effi-ciency of resource allocation. Taking the first-hand data from Alibaba auction website as the data source, the main influencing factors affecting the auction value of non-performing assets are explored. Again on the basis of BP neural network to construct a model of non-performing assets auction value assessment, and fur-ther make empirical analyses for testing, the model has accuracy, enriches the research of financial non-performing assets assessment.

Research On Auction Value Assessment Of Finan-cial Non-Performing Assets Based On Bp Neural Network

The proportion and quality of financial non-performing assets is a direct re-flec-tion of the risk management ability of banks and financial institutions. Re-search on the auction value of non-performing assets and the construction of a reliable non-performing asset value assessment model can help improve the effi-ciency of resource allocation. Taking the first-hand data from Alibaba auction website as the data source, the main influencing factors affecting the auction value of non-performing assets are explored. Again on the basis of BP neural network to construct a model of non-performing assets auction value assessment, and fur-ther make empirical analyses for testing, the model has accuracy, enriches the research of financial non-performing assets assessment.

Global Banking Industry Financials : An Analysis of Derivative Usage on The Financial Performance of Major Banks

Hedging has become a vital strategy for the banking sector, given the complexity and volatility of today's global financial markets. Hedging is also used as one of the strategies to reduce risks associated with fluctuations in the value of assets and liabilities. In Indonesia, the Banking Sector faces challenges in managing risks associated with economic and financial variability. This study focuses on micro and macro factors that can influence hedging decisions in the banking sector. The micro factors considered in this study are liquidity and leverage. On the other hand, the macro factors considered in this study are interest rates and exchange rates. The sampling method used is nonprobability sampling, namely the purposive sampling method. The samples in this study were 15 banking sector companies listed on the IDX for the period 2020-2023. This study uses the help of Eviews 12 used to test the goodness of the model, and logistic regression and hypothesis relationships designed in this study. The findings in this study indicate that interest rates have a negative and significant impact on hedging decisions, and liquidity has no significant effect on hedging decisions. This can happen because market liquidity is stable and not volatile, while exchange rates and leverage positively and significantly affect hedging decisions.

The risk effects of corporate digitalization: exacerbate or mitigate?

This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.

Sustainable Rural Development in Osing Traditional Village, Banyuwangi Regency: A Perspective from the Sustainable Livelihood Approach

Sustainable development balances economic growth, social inclusion, and environmental preservation to promote long-term community welfare. This study examines rural development in Osing Traditional Village, Banyuwangi Regency, using the Sustainable Livelihood Approach (SLA) to identify key assets, vulnerabilities, and sustainability strategies. Employing a quantitative descriptive method, the study integrates pentagonal asset analysis, vulnerability assessment, and SWOT analysis with data collected through surveys and interviews. Findings reveal that natural capital is the dominant asset (value: 9.75), supported by social and physical capital. However, vulnerabilities such as fertilizer scarcity, rising input costs, and agricultural land conversion pose significant threats to sustainability. This study addresses a critical research gap by analyzing asset interactions in a rapidly transforming, tourism-dependent village, offering novel insights into the integration of cultural preservation, economic development, and risk mitigation. Beyond the case study, it contributes to the theoretical discourse on sustainable rural development and provides actionable policy recommendations. These include agricultural land protection, improved financial access, and community-driven initiatives to ensure long-term prosperity without compromising ecological integrity.

The Influence of Investment Opportunity Set, Leverage, and Profitability on Earnings Management with Audit Quality as a Moderating Variable (Empirical Study on Manufacturing Companies Listed on the Indonesia Stock Exchange for the Period of 2018-2022)

This study aims to examine whether investment opportunity set (IOS), leverage, and profitability influence earnings management practices with audit quality as a moderating variable. Earnings management is measured using discretionary accruals (DA) which was calculated using the Modified Jones Model. IOS used market value to book value of assets (MVBA), while leverage used debt-to-equity ratio (DER), and profitability used return on assets (ROA) as their proxies, respectively. This research used 36 manufacturing companies listed on the Indonesia Stock Exchange between 2018 and 2022 as its sample. The findings show that investment opportunity set and profitability have a significantly positive impact on earnings management practices, with a significance level of ?=1%. Meanwhile, leverage does not affect earnings management practices. The results further indicate that audit quality can moderate the impact of the investment opportunity set and profitability on earnings management practices. This highlights that the investment opportunity set and profitability significantly influence earnings management practices while audit quality can moderate their impact.

ANALISIS ASPEK PEMBUKTIAN DALAM KASUS TINDAK PIDANA PENCEMARAN NAMA BAIK PASCA KUHP BARU

important aspect that needs to be considered by business people in the digital era. This research aims to analyze the various forms of IPR protection that can be applied to website design, including copyright and trademark. Website designs and the resulting content are automatically protected by copyright in accordance with Law No. 19 of 2002, which is valid for 50 years from publication. Although copyright registration is not required, it provides advantages in terms of legal defense against infringement. In addition, elements such as logos and product names require brand registration to obtain stronger legal protection. The research also identifies the challenges that work owners face in prosecuting IPR infringement in cyberspace, including cost and time. With the increasing use of the internet in business, awareness of the importance of IPR protection has become essential to maintain the authenticity and value of digital assets. The results of this analysis are expected to provide insight for businesses in protecting their works online. The results showed that the Indonesian evidentiary system, which is regulated in the Criminal Procedure Code (KUHAP), requires at least two valid pieces of evidence to convict the defendant. This is in accordance with Article 183 of KUHAP, which emphasizes the importance of the validity of evidence in the judicial process. This research also found that the application of the reverse burden of proof in defamation cases is often controversial, as it is considered contrary to the principle of presumption of innocence and human rights.

ANALISIS PERLINDUNGAN HAK KEKAYAAN INTELEKTUAL ATAS DESAIN WEBSITE ATAU HOMEPAGE DALAM KEGIATAN USAHA ONLINE

Protection of intellectual property rights (IPR) on website design or homepage in online business activities is an important aspect that needs to be considered by business people in the digital era. This research aims to analyze the various forms of IPR protection that can be applied to website design, including copyright and trademark. Website designs and the resulting content are automatically protected by copyright in accordance with Law No. 19 of 2002, which is valid for 50 years from publication. Although copyright registration is not required, it provides advantages in terms of legal defense against infringement. In addition, elements such as logos and product names require brand registration to obtain stronger legal protection. The research also identifies the challenges that work owners face in prosecuting IPR infringement in cyberspace, including cost and time. With the increasing use of the internet in business, awareness of the importance of IPR protection has become essential to maintain the authenticity and value of digital assets. The results of this analysis are expected to provide insight for businesses in protecting their works online

PENGARUH INTENSITAS, KUALITAS, DAN SIKAP ATAS KOMUNIKASI ELECTRONIC WORD OF MOUTH TERHADAP KEPUTUSAN INVESTASI

Investment decisions are the process of allocating funds to various investment options with the aim of gaining profit or increasing the value of assets in the future. Students are interested in joining GI KSPM FEB Universitas Mataram because of their desire to learn more about the world of investment, financial instruments, and capital markets. Financial behavior refers to the actions or behavior of individuals in managing finances in various ways, in accordance with the Finance Behavior Theory. However, this does not happen by chance where there are other influential factors such as marketing communications which today rely more on digital, specifically the intensity of viewing or watching, the quality of what is watched, and attitudes towards electronic Word of Mouth communication. This research was conducted in the Mataram City Area and was more specifically at GI KSPM FEB Universitas Mataram. The research time was 2024. This research is an associative research with a quantitative approach using data collection methods in the form of distributing questionnaires. The statistical analysis used includes descriptive statistical tests, validity tests, reliability tests, normality tests, multicollinearity, heteroscedasticity, determination coefficient tests, F tests and t tests. Data analysis using multiple linear regression analysis. The results show that intensity has a positive effect, the quality of electronic word of mouth does not have a significant effect, and attitudes towards electronic word of mouth communication have a positive effect on investment decisions.

REIT Price-to-Net Asset Value, Performance, and Managerial Entrenchment

This study examines P/NAV dynamics in the REIT industry, utilizing NAV estimates from SNL Financial and stock returns and distributions from CRSP. The findings reveal that REITs typically trade at a premium to their NAVs around IPOs, transitioning to a discount approximately 30 months later. The analysis also shows a positive association between P/NAV and future excess NAV returns, consistent with Chay and Trzcinka (1999). Furthermore, the results suggest high past excess stock returns indicate managerial ability, creating market expectations reflected in premiums. However, when controlling cross-sectional correlation, this relationship loses statistical significance. Additional findings indicate that REITs with positive excess NAV returns, longer public trading histories, or CEO replacements are likelier to trade at a premium to NAV. In contrast, those led by older CEOs, CEOs with longer tenures, or recent outside appointments tend to trade at a discount. Although the negative relationship between CEO tenure and P/NAV is not statistically significant, it supports Berk and Stanton’s (2007) assertion that entrenched CEOs contribute to NAV discounts.

Does the Asset‐Type Matter in Vulnerability Reduction? Evidence From Rural Indian Households

ABSTRACTThe importance of assets for household emanates from its consumption‐smoothing ability and also for providing self‐insurance. However, the extent of cushion provided by assets against economic shock is contingent on the type of asset. This paper examines the relation between asset ownership and vulnerability of households and whether the asset types owned by the households can help generate value. We use household level asset data from eight villages of the Indian state of Bihar to study the type of assets rural households own and their contribution in mitigating poverty levels. Our results confirm that there is significant heterogeneity in asset ownership across social groups with low value asset being owned by households belonging to the disadvantaged castes. Poorer households are trapped in a spiral of low assets and low income which inhibits further generation of high value assets and income therefrom. In general, ownership of unproductive assets across households is quite high compared to productive assets indicating the poor development of capital in Bihar providing little buffer against possible economic shocks.