Asset Portfolio Research Articles

КРИТЕРИИ ЭФФЕКТИВНОСТИ УПРАВЛЕНИЯ ИНВЕСТИЦИОННЫМ ПОРТФЕЛЕМ ФИНАНСОВЫХ АКТИВОВ В ПРАКТИКЕ СТРОИТЕЛЬНОЙ ОРГАНИЗАЦИИ

The purpose of the article is to analyze the key criteria that are used in the assessment of the investment portfolio of financial assets in the practice of construction organizations. The author systematized and investigated the conclusions of the authors’ scientific papers, which reveals that the definition of the main performance criteria should be used in the process of managing an investment portfolio of financial assets. For this reason, issues related to the optimization of the investment portfolio remain unresolved in the practice of construction organizations. The relevance of the study requires identifying key indicators that can be used by construction companies to solve the tasks that are set when deciding on the allocation of free financial resources and funds for their investment in specific securities and financial assets. The conditions that contribute to a higher efficiency of managing the investment portfolio of financial assets of the organization, taking into account the specifics of the activities of construction companies, are determined. In addition, the scientific article contains different approaches to criteria and indicators, with the help of which it is possible to more accurately determine how appropriate it is to manage an organization’s investment portfolio.

ТЕНДЕНЦИИ И ПЕРСПЕКТИВЫ УПРАВЛЕНИЯ ПОРТФЕЛЕМ ФИНАНСОВЫХ АКТИВОВ В СТРОИТЕЛЬСТВЕ

Target. Conduct a research analysis of trends and prospects for a portfolio of financial assets in construction, where transformational changes are taking place due to the negative impact of international trade and economic sanctions, as well as an increase in the key rate in Russia. Tasks. Consider the practical significance of financial assets for the development of construction enterprises. Analyze the dynamics and structure of the main indicators that reflect the economic state of the financial assets of enterprises in the Russian construction industry. Identify current problems and difficulties that form barriers to the development of financial assets of enterprises in the construction industry. Methodology. As part of the conducted scientific research, the following methods were used: scientific observation, comparison, private and special methods: economic-statistical, analytical-calculation and expert. Results. Indicators of the development of portfolios of financial assets of enterprises in the Russian construction industry demonstrate an increase in capital investments, however, the degree of depreciation of fixed assets does not decrease, but, on the contrary, increases. This inverse correlation reflects the low efficiency of financial assets, which are not enough to create high competitiveness of enterprises in the construction industry. Conclusions. The authors substantiate the conclusions that the trends and prospects for the development of portfolios of financial assets of construction enterprises in Russia are characterized by economic instability in the external environment, which is caused by the adoption of large-scale international trade and economic sanctions in 2022.

ВЛИЯНИЕ ФИНАНСОВОГО КРИЗИСА НА СТРАТЕГИИ УПРАВЛЕНИЯ ПОРТФЕЛЕМ ФИНАНСОВЫХ АКТИВОВ

The subject of the study is global changes and the crisis in financial markets, which obviously have a great influence on the formation of changes in investor preferences, as well as related approaches to compiling an investment portfolio of financial assets. Currently, a modern investment portfolio is a collection of different financial assets, selected because of the different reactions of their prices to volatility in market trends, mainly during periods of financial crises. The main issues of forming and managing an investment portfolio using Smart Beta funds were also presented, allowing to reduce risks and uncertainties, ensuring the effective formation and management of a portfolio of financial assets, and its diversification.

Сучасні реалії функціонування страхового ринку України

The aim of the article is to evaluate the indicators of the insurance market of Ukraine as part of the financial sector, analyze the patterns of its development and determine the impact of full-scale military operations on its dynamics. Analyzing trends in the development of the insurance market of Ukraine its active recovery in 2023 was noted as evidenced by an increase in gross premiums by 18.7% and the number of concluded insurance contracts by 7.6% compared to 2022. The article evaluates the structure of the financial sector of Ukraine, defines the place and role of the insurance market. It is revealed that the financial sector of Ukraine is dominated by banking institutions which have increased the volume of their assets over the past 7 years more than 2 times, at the same time, the insurance sector has increased its portfolio of assets by only 29.4%. An analysis of the depth of the insurance market was carried out through the indicator of the level of insurance penetration the value of which reaches 0.8% at the end of 2022. It is noted that in Ukraine, unlike the developed countries of the world, the insurance market is characterized by the dominance of risk insurance companies, the size of their assets significantly exceeds the assets of life-insurers. Along with that, during 2021–2023 life insurance companies have significantly increased their asset portfolios. Quantitative parameters of the insurance market of Ukraine were monitored and it was found that insurers receive the most premiums from automobile types of insurance – about 50% of all premiums, personal types of insurance provide slightly less than 30% of premiums. A list of conditions that would allow insurance companies to more effectively meet the requirements of consumers of insurance services is given. Prospects for further research in this direction are the study of theoretical and empirical aspects of the relationship between the indicators of the insurance market and economic growth.

Liquidity Jump, Liquidity Diffusion, and Portfolio of Assets with Extreme Liquidity

Liquidity Jump, Liquidity Diffusion, and Portfolio of Assets with Extreme Liquidity

Analysis of Implicit Strategy Optimization and Economic Returns of Machine Learning Techniques in Financial Asset Management

Abstract This paper formulates and adjusts investment portfolios based on machine learning techniques, adopts the B-L model after combining the GJR-GARCH-M model and the RBF model, combines the subjective view of the investor with the market equilibrium rate of return, and realizes the optimization of the implicit strategy in the management of the financial assets in the process, and finally analyzes the economic returns through the B-L model. The return of the asset portfolio under the improved B-L model is 0.37% higher than that of the market capitalization-weighted asset portfolio. The Improved B-L model’s asset allocation improves economic returns. In terms of cumulative return, the mean cumulative return of the improved B-L model is 50.7%, which is higher than the economic return of the regular B-L model and the equal-weight portfolio strategy.

Платформенные экосистемы: накануне нового прорыва в области коммерциализации интеллектуальных прав

The aim of the work is to analyze the new investment capabilities that appeared as a result of the development of new platform ecosystems that form the economic circulation of digital intellectual assets of copyright. The productive ideas of the possible use of intellectual assets in financial engineering were voiced back in the 1980s, i.e., almost at the dawn of the emergence of financial engineering as a science itself. For example, in one of the first reference books on financial engineering and financial innovation, the growing use of legislation on intellectual property protection was mentioned as one of the aspects of financial engineering, the significance of which would grow in the coming years. The main stage of development is characterized by a massive transformation of business models and the transition to platform ecosystems, much more mobile and susceptible to organizational and financial innovations. A huge role in this process was played by the rapid development of information technology. The work shows that, by analogy with the period preceding the first transactions of the intellectual property secretion in the 1990s, there is currently a steady increase in the income of microstock platforms. In addition to ordinary investors, the ecosystem of microstocks includes an extensive contingent of the so-called creative investors – authors of digital images, video and sound files posted in the collections of such companies. Investors of this category are participants in the total intellectual capital successfully controlled by microstocks. The basics of the business of microstocks were laid back in the early 2000s, in fact, in the wake of the “dot-com”, when there was a stir of exciting, sound and literary content from the multimillion-dollar army of creators of the modern Internet. On the basis of ten-year observations of the portfolio of digital images, the study confirms that (1) the position of the author/investor on digital assets is not exposed to losses in the classical sense; (2) a correlation between the yield of the portfolio of digital images of the individual author and the profitability of the action of the microphotostock company, in the collection of which the portfolio is located, is absent. The results prove that the portfolio of digital intellectual assets of the author/investor can be used as a hedging element as part of a hybrid investment position that includes the shares of a microstock company. In addition, preliminary quantitative assessments of the possible contingent of investors who are interested in implementing the ideas of the proposed hybrid tool are made in the work. The study allows predicting the emergence of new ideas and investment capabilities in the field of commercial circulation of digital intellectual assets.

Can equity mutual funds outperform the benchmark and simple passive portfolios?

This study evaluates the risk-adjusted performance of equity mutual funds in Nigeria against the market benchmark and two alternative passive portfolios available to investors. Data on monthly net asset values (NAVs) of 30 actively managed, equity-based mutual funds that operated in Nigeria between 2012 and 2021 were collected and analyzed. Risk-adjusted performance measures including the Treynor ratio, Sharpe ratio, Jensen’s alpha, information ratio, Modigliani–Modigliani (M2) measure, Sortino ratio, and the Fama-French 3-factor regression model are used to evaluate the performance of mutual funds. Evidence shows that the Nigerian equity mutual fund portfolio does not deliver excess risk-adjusted returns, and underperforms the three simple passive portfolios against which it was benchmarked. However, mutual fund portfolios provide robust, low-cost diversification benefits and could be considered as part of a well-diversified portfolio of assets. This study explores investment strategies, with practical implications for investors, industry professionals, regulation, and academia. It provides a useful guide to retail investors and their advisers on managing their investment portfolios in the Nigerian stock market. In addition, it validates the veracity of the efficient-market hypothesis (EMH), implying that, on average, seeking alpha is, perhaps, a futile effort.

Financial Asset Allocation and Portfolio Optimization Strategies Based on Stochastic Optimization Methods

Abstract Financial market uncertainty necessitates sophisticated asset allocation and portfolio optimization strategies for enhanced returns and risk mitigation. This study explores stochastic optimization methods to overcome the limitations of traditional models in complex market environments. By employing expected utility theory and the Lagrange multiplier method, we develop an optimization model that facilitates fair equity pricing and enables dynamic allocation of financial assets, outperforming traditional approaches in simulated markets. Specifically, our method yields mean allocations for state-owned and non-state-owned enterprises at 17.4112 and 16.9297, respectively, demonstrating its superiority. Analysis of bank asset portfolios reveals significant improvements in asset structure and yields, underscoring the effectiveness of stochastic optimization in financial asset management, offering substantial benefits in efficiency and investment returns.

Sectoral Asset Concentrations and Insurance Solvency Regulation

Historical evidence, like the global financial crisis from 2007–2009, highlights that sectoral asset concentrations can play an important role in the solvency of insurers. Yet, current regulatory frameworks, such as the U.S. risk-based capital (RBC) framework, neglect sectoral asset concentrations in the determination of capital requirements, potentially underestimating the asset portfolio’s systematic loss exposure and reducing incentives for corresponding risk mitigation. By creating a detailed data sample of U.S. insurers’ asset holdings from 2009 to 2018 by means of their statutory filings, we find that insurers concentrate their assets particularly toward the financial, public, and real estate sector and that sectoral asset concentrations toward the public sector are associated with improved solvency, while concentrations toward the real estate sector weaken solvency. Our findings can serve as a starting point to revise current regulatory practices, particularly in terms of creating proactive incentives for insurers to mitigate the accumulation of systematic risk exposures associated with sectoral asset concentrations.

Financial Collaboration Technology Based on Deep Deterministic Strategy Gradient Algorithm

With the rapid development of modern financial technology, the use of machine learning methods to assist enterprises in financial decision-making has become an important trend. This article investigates financial decision-making problems based on the Deep Deterministic Policy Gradient (DDPG). By building a simulation environment and organically integrating the algorithm with the real financial decision-making process, the effectiveness and accuracy of the DDPG algorithm in financial decision-making were verified. The value of the investment portfolio steadily increases with the increase of time step. From the initial $10000 to the final $10985, this indicates that the algorithm is highly effective in optimizing asset portfolios. This development trend demonstrates that the DDPG algorithm can efficiently manage assets in a stable market, thereby achieving the goal of preserving and increasing value. The research results of this article can expand the application of DDPG method in unconventional data processing, and provide new ideas and methods for the research of financial technology and other related issues, which has important theoretical significance and practical value.

Investment Weightings of Technology and Traditional Stocks: Investor Choice and Risk Management

In the era of big data, the financial landscape is undergoing transformative changes through the integration of advanced technologies. This research delves into the dynamic realm of asset portfolios within the information technology industry, traditional sectors, and amalgamated portfolios containing popular giant stocks. Employing Python and machine learning, the study focuses on predicting expected returns, comparing and analyzing diverse portfolios to identify optimal investment strategies for risk management. Evaluation metrics include annual return, annual volatility, Sharpe ratio, and statistical charts. The findings highlight the lucrative potential of investing in the information technology sector, revealing an impressive annual return rate of 40.1%. In contrast, traditional industry portfolios not only underperform but also exhibit high-risk profiles and diminished returns. This research underscores the critical role of technological advancements and data-driven methodologies in shaping contemporary financial strategies for robust portfolio management. his research advocates for the strategic incorporation of technology-driven insights in financial decision-making, emphasizing the significant outperformance potential of information technology portfolios in navigating the complexities of modern investment.

지식재산권에 대한 담보권설정과 자산유동화 - 특허권을 대출에 활용하기 위한 측면에서 일괄담보 -

This article analyzes the point that the method for setting appropriate collateral varies depending on the type of intellectual property rights due to their differing characteristics. Intellectual property securitization is the structure that a company holding intellectual property rights transfers its intellectual property rights to a special purpose company (SPC), which then issues securities based on the cash flow from the intellectual property royalties. Securitization is suitable for copyrights and trademarks. However, for patents, there are challenges in securitization due to the possibility of invalidation of a patent and difficulties in valuation. In actual cases of intellectual property securitization, there are many related to copyrights and trademarks. To activate finance utilizing patents, the introduction of a universal security system is necessary. A universal security refers to a framework where a debtor's entire asset portfolio is pooled together to establish a comprehensive collateral. In the case of patents, since multiple related patents are required to produce a single product, the introduction of the universal security interests system is necessary. The creation of security interests in patent rights, therefore, becomes meaningful when it allows for universal security interests, encompassin
 other personal properties. In cases where the debtor (security provider) i s a company, it is necessary to consider registering movables security interests, receivables security interests and universal security interests all in the company registration, similar to the UK system. Furthermore, it is important to consider the flexible approach of U.S. case law, such as Moldo v. Matsco, Inc. , which acknowledged the effectiveness of security interests without registration in the patent registry, once universal security interests, including patent rights, are registered.

Tail connectedness between artificial intelligence tokens, artificial intelligence ETFs, and traditional asset classes

We examine extreme connectedness between the artificial intelligence (AI) tokens, artificial intelligence ETFs, and other asset classes, using the quantile VAR approach of Ando et al., (2022). We find moderate connectedness levels at mean and median quantiles, with AI ETFs (AI tokens) acting as strong (weak) net emitters (receivers) of return spillovers. Findings, confirmed by alternative testing, suggest that, during normal market conditions, AI tokens may offer utility as diversifiers for portfolios of traditional assets. However, at both lower and upper quantiles, connectedness levels increase, consistent with AI tokens and ETFs being sensitive to extreme shocks. Results suggest that AI tokens and ETFs do not diversify the risk of other assets during extreme market conditions. Finally, AI tokens, especially, may offer effective hedging at low cost for traditional assets (gold, equity, real estate, bonds, and currency), except for the oil and cryptocurrency market. Investors including AI assets in portfolios need to diligently monitor for changing market conditions.

Modeling and solving a multi‐objective optimal portfolio of upstream oil and gas assets

AbstractThis paper focuses on optimizing project investments in oil and gas companies. It proposes a multi‐objective method for investing in oil and gas assets, considering factors such as scale and efficiency. The model takes into account the presence of nonlinear equations and integer constraints, and establishes a nonlinear multi‐objective mixed integer programming portfolio model for oil and gas. The weights of multiple objectives are determined using support vector machines. The optimization model incorporates the displacement transfer concept of particle swarm optimizer and the mutation operation of genetic algorithm using the transfer strategy of Gaussian particle swarm. The effectiveness of the model and algorithm is demonstrated through two examples.

Empirical Research on Optimizing Company Investment Strategy Based on Asset Portfolio Strategy -Taking the Pharmaceutical Industry as an Example

In recent years, the pharmaceutical industry has developed rapidly due to the COVID-19. At the same time, with the development of modern asset theory, a variety of asset portfolio strategies can be used by people. In the capital market, the pharmaceutical industry has also become an emerging ideal investment industry, and various related investment portfolio products and trading methods are constantly being updated and improved. This article is based on modern asset portfolio strategies, through relevant worldwide asset allocation models, sharpe theory and CPAM model, and uses the optimal selection of asset portfolios and market portfolios in Markowitz asset portfolio theory to conduct empirical research on the current stock investment portfolio products in the pharmaceutical industry. To test, use Python and Excel to process and analyze two years of stock data and group assets into groups to test the combination to verify the effectiveness of the model for fund investment portfolios in the pharmaceutical industry and better optimize the asset allocation, thereby effectively avoiding risks and increasing returns.

Liquidity Creation and its Impact on Economic Growth: Moderating Role of Firm Size

The study aims to examine the influence of Liquidity Creation (LC) on Pakistan's Economic Development (GDP) to investigate the moderating role of firm size and its abiding association in this relationship. Banks create liquidity by managing their portfolios of assets and liabilities with various maturities. The current study used an estimated amount of liquidity created by commercial banks in Pakistan using the "Catfat" model over the last twenty-two years. The estimated LC is employed in this study to assess its influence on GDP growth. Additionally, the research examines the moderating role of firm size between LC and GDP. Furthermore, secondary time series data for this research was collected from the financial statements and World Bank Data from 2000-2021. The study employs a regression technique to test the hypotheses. The outcomes indicate that LC has a significant positive impact on GDP. It implies that when commercial banks create liquidity, it boosts economic growth. The results revealed that firm size does not moderate the relationship between the LC and GDP, neither strengthens nor weakens. The study put forward that conventional banks play a substantial role in contributing to Pakistan's economic growth by creating liquidity in the market. The study holds importance in its ability to shape economic policies, provide financial institutions direction, and offer investors advantages. It contributes to academic research, provides practical insights, and has worldwide applicability in enhancing comprehension of financial systems and their influence on economic growth.

Optimization investment portfolio of ESG capital market in Indonesia: An investigation of Polynomial Goal Programming based on higher moments

The development of capital market investors in Indonesia has experienced rapid growth, leading to increasingly volatile movements in the domestic market. Companies or investment managers must form asset portfolios with optimal expected returns and measurable risks to address this issue. This study aims to analyze the potential combinations that can be formed using ESG Capital Market Indonesia 2022 and safe-haven instruments, utilizing the Markowitz theory and Polynomial Goal Programming (PGP) method. This research uses secondary data, and the research variables used are ESG Capital Market Indonesia 2022 and Gold from January 2007 to December 2022. Based on the previous research, the formation of portfolio combinations using safe-haven instruments, employing the Markowitz theory and Polynomial Goal Programming (PGP) method can provide better investment portfolio combinations during crises. Furthermore, the performance of each formed combination is measured using the Sharpe Ratio. The findings indicate that Markowitz's theory can generate better performance than the PGP method. However, it exhibits suboptimal skewness and kurtosis values compared to the PGP method.

Evaluating household's risk management strategies considering heterogeneities in the livelihood diversification: Evidence from farm households of Bangladesh

Enterprise risk management has become one of the crucial steps for households in attaining resilience in their livelihood decisions. However, households must prioritize diversifying their enterprises to effectively tackle the risk factors that propagate negative externalities (i.e., poverty) and obtain resilience in livelihood decisions. As such, this paper assesses households' risk management strategies considering the heterogeneities in the diversification levels in rural Bangladesh by harnessing data from 90 participating farm households from September 2016 to March 2017. We also explore the deterministic factors linked to diversification strategies. The findings of the multivariate regression analysis depict that education, occupation choice, asset portfolio, and family size are the significant determinants of a household's livelihood diversification choices. Shannon diversity index and livelihood typologies like ‘Type 66’ and ‘Type 75’ strategies have been used to assess household risk levels and family earning diversities. The overall diversity index (4.3) reveals that the respondents were moderately diversified. Typology studies confirm that the households in Ishwarganj and Haluaghat are more diversified (earning from multiple sources) than in Gouripur. For instance, under the ‘Type 75’ strategy, households in Ishwarganj earn 33% of the total income from crop-non-farm combined, and households in Haluaghat earn only 3% of their income solely from livestock. However, respondents in Gouripur earn most of their income from single sources (24% solely from crops under ‘Type 66’), and therefore, they are the least diversified and are most likely to be affected by risk. Moreover, FGT and Sen index outcomes of poverty show that BDT 4126 and 5776/year, respectively, are required to improve the poor status of the households where the poverty line is BDT 58,947.

ASSET-BACKED SECURITIES AS AN ALTERNATIVE TO MUSLIM INVESTMENTS IN THE MAQASHID ASY-SHARIAH FRAMEWORK

The advantages of asset-backed securities are many, namely that investors can invest in quality assets, there is low default due to the division of receivables into many debtors, it is suitable for investors with faster principal return needs, and the high-profit rating of asset-backed securities can increase the overall investment portfolio. This research examines the analysis of asset-backed securities (ABS) in the study of Maqashid Shariah. The method used in writing this research is library research, with data collection directed directly to the search for data and information through books, literature, or library materials, including written documents, photographs, pictures, and electronic documents. The results of this research indicate that ABS is a financial instrument in the form of a collective investment contract unit that contains a portfolio of financial assets. The practice of asset securitization in ABS transactions has several advantages and risks. ABS has participated in various state projects and is generally very useful. To unravel liquidity problems on the originator's side and at the same time present alternative instruments with low risk for investors, it can be seen that it has included Maqashid Ash-Shari'ah, namely Hifdz Al-Maal which is included in the Dharuriyyat category from the originator's side as a solution to asset liquidity and Hajiyyat from the investor's side.