Asset Returns Research Articles

A new portfolio approach integrating three-way decision and Encoder–Decoder network

In the stock market, it can be challenging to predict stock trends and identify stocks with investment potential due to uncertainty and risk. Accurate predictive models and reliable asset preselection methods are essential for portfolio management. This paper proposes an integration of the deep learning model, the three-way decision (3WD) theory, and the Mean-Variance (MV) method for asset preselection and optimal asset allocation. In the initial stage, an attention-based Encoder–Decoder model is used to predict asset returns and calculate volatility. It outperforms other benchmark models regarding relative error, absolute error, and directional accuracy. The subsequent stage involves selecting stocks based on expected returns and volatility characteristics. The 3WD theory is then used to identify the delayed decision set for implementing additional investment strategies to hedge portfolio risk and enhance returns. Finally, the MV model is employed for investment portfolio optimization. The proposed model is validated using a substantial dataset from the A-share market’s SSE 50 Index from January 2010 to December 2022. Results indicate that the proposed model outperforms benchmark models in terms of daily average returns, annualized Information ratio, Sortino ratio, and other aspects under certain trading costs. However, further exploration is required to establish a mechanism that limits the quantity of preselected assets to ensure its broad applicability.

An insight into the signaling role of Sharia status: a case from an emerging IPO market

Purpose This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing. Design/methodology/approach This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market. Findings The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments. Practical implications The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making. Originality/value This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

Mimicking crypto portfolios in sustainable investment

In this paper, considering the difference in the energy demand level, we utilize the daily pricing data from 10/01/2019 to 06/30/2023 to construct mimicking crypto portfolios with 12 clean cryptocurrencies to replace the dirty cryptocurrency, Bitcoin (BTC). With a monthly rebalancing strategy, the mimicking portfolio closely matches the exposures to the risk factors of the BTC but with fewer specific risks. Furthermore, relying on the bivariate dynamic conditional correlation (DCC-) GARCH model, we compare the hedging capability of BTC and the corresponding mimicking crypto portfolio against movements of returns of sustainable assets. The empirical results show that the mimicking crypto portfolio provides ESG investors with a cheaper hedge tool of higher hedge effectiveness compared to the BTC. Moreover, we find that the mimicking crypto portfolio can act as a strong safe haven for the S&P Global Clean Energy Index and S&P Latin America Emerging LargeMidCap ESG Index during periods of market stress. Therefore, the mimicking crypto portfolio is a more attractive option for ESG investors due to its superior hedging efficiency and the added environmental advantages.

Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review

Traditional mean-variance (MV) models, considered effective in stable conditions, often prove inadequate in uncertain market scenarios. Therefore, there is a need for more robust and better portfolio optimization methods to handle the fluctuations and uncertainties in asset returns and covariances. This study aims to perform a Systematic Literature Review (SLR) on robust portfolio mean-variance (RPMV) in stock investment utilizing genetic algorithms (GAs). The SLR covered studies from 1995 to 2024, allowing a thorough analysis of the evolution and effectiveness of robust portfolio optimization methods over time. The method used to conduct the SLR followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The result of the SLR presented a novel strategy to combine robust optimization methods and a GA in order to enhance RPMV. The uncertainty parameters, cardinality constraints, optimization constraints, risk-aversion parameters, robust covariance estimators, relative and absolute robustness, and parameters adopted were unable to develop portfolios capable of maintaining performance despite market uncertainties. This led to the inclusion of GAs to solve the complex optimization problems associated with RPMV efficiently, as well as fine-tuning parameters to improve solution accuracy. In three papers, the empirical validation of the results was conducted using historical data from different global capital markets such as Hang Seng (Hong Kong), Data Analysis Expressions (DAX) 100 (Germany), the Financial Times Stock Exchange (FTSE) 100 (U.K.), S&P 100 (USA), Nikkei 225 (Japan), and the Indonesia Stock Exchange (IDX), and the results showed that the RPMV model optimized with a GA was more stable and provided higher returns compared with traditional MV models. Furthermore, the proposed method effectively mitigated market uncertainties, making it a valuable tool for investors aiming to optimize portfolios under uncertain conditions. The implications of this study relate to handling uncertainty in asset returns, dynamic portfolio parameters, and the effectiveness of GAs in solving portfolio optimization problems under uncertainty, providing near-optimal solutions with relatively lower computational time.

Kedudukan Hukum Justice Collaborator dalam Sistem Peradilan Pidana di Indonesia

Justice collaborators play an important role in law enforcement. The role or function of a justice collaborator includes disclosing a criminal act or the impending occurrence of a criminal act, so that the return of assets resulting from criminal acts can be achieved to the state, providing information to law enforcement officials, providing testimony in the judicial process. The aim of this research is to analyze the legal position of justice collaborators in the criminal justice legal system in Indonesia. This research uses a type of normative juridical research by analyzing primary, secondary and tertiary legal materials. The results of the research are that the legal position of justice collaborator has a very important role in uncovering a well-organized criminal act, or a particular criminal case, so that the suspect or defendant's request to become a justice collaborator must be granted. considered based on the evidence at trial in this case. It is within the judge's authority to grant the justice collaborator's request, because this will affect the sentence. In conclusion, justice collaborators are not regulated in the criminal procedural law book in Indonesia, but are regulated in Law Number 31 of 2014 concerning Protection of Witnesses and Victims, as well as Joint Regulations for Law Enforcement Officials and Witness and Victim Protection Institutions concerning Protection of Witnesses and Victims. Complainant, Reporting Witness and Perpetrator Witness Working Together.

An Investigation of the Impact of Sustainability Reports on Investment Decisions: A Study of BIST 30 Companies

As the world's resources diminish, ensuring a sustainable planet for future generations has become a crucial issue that demands attention from all stakeholders. Consequently, various domains of life encounter the concept of sustainability. In this study, we analyzed the sustainability standards published by the Accounting, Public Oversight, and Auditing Standards Authority (KGK), which is the regulatory and supervisory body. Our aim was to clarify the connection between investment decisions and sustainability reports on businesses. This study employed the literature review method to examine the sustainability reports of the top 30 companies listed on the Borsa Istanbul (BIST 30) for the year 2022, using the S1 and S2 standards issued by KGK, with a focus on four key criteria. We allocated one (1) point to the company if it complied with these four criteria when preparing its sustainability report; otherwise, we assigned zero (0) points. Subsequently, we conducted diverse financial analysis on the 2022 financial data of these organizations and employed the Spearman correlation test to investigate the association between the outcomes and sustainability reporting. A strong correlation was found between sustainability reporting and the leverage ratio, earnings per share, firm size, asset return, and P/E ratio. The study highlights the significance of offering comprehensive explanations in line with applicable requirements when drafting sustainability reports, while also considering the influence of investor decisions on firms.

Earning Per Share as a Market Perfomance Measure in Increasing Stock Returns of Pharmaceutical Companies

Stock prices serve as a benchmark for investors to assess a company's success. A positive stock return is an indicator of business success for a company. This study has three main objectives: to examine the influence of Earnings Per Share (EPS) on stock returns, to investigate the relationship between Return On Assets (ROA) and stock returns, and to determine the extent to which the Debt to Equity Ratio (DER) affects stock returns. The population of this study consists of 11 pharmaceutical companies listed on the Indonesia Stock Exchange during the period of 2018-2023. Simple random sampling was used to randomly select samples from the population, resulting in 264 quarterly financial data samples. The type of data used in this study is quantitative data obtained from semi-annual reports downloaded from www.idx.co.id and from the respective pharmaceutical companies' websites. Data analysis was conducted using Eviews version 10. The study found that only one variable, Earnings Per Share (EPS), significantly influences stock returns. The other two variables, Return On Assets (ROA) and Debt to Equity Ratio (DER), do not have a significant effect on stock returns.

Declining research productivity and income inequality: A centenary perspective

Research productivity has been sharply declining since 1920. This decline has significant implications for inequality. Using an open-economy Schumpeterian growth model, we show that domestic research productivity influences income inequality through two opposing forces: a positive effect from increased asset returns and a negative effect from the erosion of innovation rents through creative destruction. In contrast, foreign research productivity affects inequality solely through the asset returns channel. By constructing a long historical data series for 21 OECD countries, we find that the asset returns channel has been the dominant driver of inequality over the past century. The reduction in both domestic and foreign R&D productivity accounts for 25% to 35% of the observed downward trend in income inequality over this period.

An endogenous evolution mechanism model of asset prices based on time-varying risk aversion coefficient

In the traditional heterogeneous agent model, investors are assumed to be risk averse, and the wealth expected utility function maximization principle is used to form the optimal asset quantity demand. In such models, the risk aversion coefficient of investors is often assumed to be constant. This paper considers that the risk aversion coefficient of investors is time-varying and changes with the change of wealth, and establishes an endogenous evolutionary mechanism model formed by fundamental analysts, technical analysts, and market makers. Compared with the fixed risk aversion coefficient model, this paper analyzes the investor’s behavior, the interaction between investor behaviors, and the influence of different types of investors on the stability of the market. At the same time, we test asset price and asset behavior and conclude that investor behavior affects the stability of the system model. The numerical simulation of the corresponding stochastic model shows that the model can simulate the basic characteristics of financial time series, such as the partial peak and thick tail of asset return series, and the long memory of fluctuations.

AN EMPIRICAL STUDY AND STATE OF PLAY OF THE LINK BETWEEN M&A OPERATIONS AND PERFORMANCE OF COMPANIES

Objective: The objective of this study is to investigate the impact of external growth on firm's performance, with the aim of verify the changes that performance may have before and after M&A operation. Theoretical Framework: In this topic, the main concepts and theories that underpin the research are presented. Efficiency theory, Value theory stand out among theories that better justify reasons why shareholders choose to deal with M&A, and thus provid a solid basis for understanding the context of the investigation. Method: The methodology adopted for this research comprises regression analysis of Return of assets of selected firms. Data collection was carried out through CapitalIQ5 platform based in firms that belong to MENA region and carried out M&A operations between 01/01/2022 and 31/12/2022 Results and Discussion: The results obtained revealed the global evolutions of effect on the short term of the M&A operations on the companies’ performance, represented by the RoE, is globally negative by the linear hypothesis considered. In the discussion section, these results are in lign with general expectations of the operations that are basically long term. Research Implications: The practical and theoretical implications of this research proove the negative short term impact of the M&A operations on financial performance of firms which allowed us to judge that a study spread over time will lead us to more meaningful conclusions. Originality/Value: This study contributes to the literature by trying to study the impact of M&A opperations on financial perfomance in theoretical and empircal ways. The relevance and value of this research are evidenced by using regressions and t test statistics in order to deduct the impact of M&A operations.

Risk factor aggregation and stress testing

Stress testing refers to the application of adverse financial or macroeconomic scenarios to a portfolio. For this purpose, financial or macroeconomic risk factors are linked with asset returns, typically via a factor model. We expand the range of risk factors by adapting dimension-reduction techniques from unsupervised learning, namely PCA and autoencoders. This results in aggregated risk factors, encompassing a global factor, factors representing broad geographical regions, and factors specific to cyclical and defensive industries. As the adapted PCA and autoencoders provide an interpretation of the latent factors, this methodology is also valuable in other areas where dimension-reduction and explainability are critical.

Valuing Financial Data

Abstract How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others’ characteristics. Our approach values public or private data, data about one or many assets, and data relevant for dividends or sentiment. While different data types, of course, have different valuations, heterogeneous investors also value the same data very differently. This finding suggests a low price elasticity for data demand. Heterogeneous investors’ data valuations are also affected very differentially by market illiquidity.

Market Power and Price Informativeness

Abstract We study the distributional effects of asset ownership on price informativeness in a general equilibrium model. The model features investors (oligopolists) with different degrees of price impact and abilities to learn about individual asset payoffs from private and price signals, and a competitive fringe that only learns from asset prices. We show that price informativeness is non-monotonic in the oligopolists’ aggregate size, decreasing in the sector’s concentration and in the size of the passive sector. We further show that the size effect can be decomposed into a learning channel capturing investors’ quality of private signals and an information pass-through channel measuring the sensitivity of investors’ trades to private signals, with the latter one being the primary source of variation in price informativeness relative to the size distribution.

Application of Multi-Factor Financial Models in Asset Pricing

This paper explores the theoretical underpinnings and practical applications of multi-factor models in stock portfolio management. It outlines the theoretical frameworks of multi-factor asset pricing models such as APT theory, Fama-French three-factor, and five-factor models, analyzing how various risk factors influence asset returns. The study then discusses methods for identifying core risk factors empirically, constructing portfolios, optimizing weight allocations, and evaluating investment performance. Empirical testing using data from the CSI 300 and CSI 800 indices confirms that optimized multi-factor portfolios achieve significant excess returns while managing risk effectively, showcasing the practical utility of this quantitative investment framework in the Chinese A-share market.

Firms’ financing and debt maturity choices: An empirical analysis from the perspective of asset value dynamics

AbstractWe examine empirically the relationship between the dynamics of firm value and their financing and debt maturity choices. Theoretical studies show that the actual drift of firm value is a key determinant of firms’ leverage and debt maturity by incorporating the conflicts between undiversified insiders (managers) and well‐diversified outside investors. We empirically analyze firms’ incremental leverage and debt maturity choice important determinants of firms’ leverage and debt maturity, we find that the drift, or the expected return of total assets, does affect the firms’ choices of incremental leverage and debt maturity, as predicted by theoretical studies. Our results provide the evidence that the divergence of interests between undiversified managers and well‐diversified shareholders has significant impact on firms’ financing policies that are generally controlled by managers, and the resulting leverage and maturity choices may deviate from maximizing shareholders’ value.

Phenomenological Study: The Role Of The Financial Services Authority In Resolving Islamic Banking Customer Problems

Problems in the banking world often make customers as disadvantaged parties both materially and immaterially. This certainly encourages customers to make efforts that can avoid losses both in litigation and non-litigation. The purpose of this study is to determine the role of the financial services authority in solving problems experienced by Islamic bank customers. The method used in this study is a qualitative method with a phenomenological approach. Phenomenological studies with data collection methods, namely by observation and interviews. The results of this study show that the financial services authority has an important role in solving customer problems and customer legal protection. The manifestation of the role of the financial services authority can be seen from its authority in terms of taking actions both legally and reprimands to the banking industry to respond and resolve Problems experienced by customers, in addition to their authority in terms of filing claims for compensation or return of customer assets lost due to the bank's fault.

Option‐Implied Ambiguity and Equity Return Predictability

ABSTRACTWe propose a model‐guided option‐implied ambiguity measure to capture uncertainty regarding the return distribution of a risky asset underlying a set of options, and investigate its predictive power on the asset return. A representative investor's ambiguous beliefs or prior distributions on the underlying asset returns are extracted from the market prices of options, the expected volatility of which is then defined as the option‐implied ambiguity and is calculated in line with Brenner and Izhakian. Simulated paths of the calibrated models are utilized to compute all pertinent probability characteristics from a forward‐looking perspective. The empirical results with SSE 50 ETF options indicate that the proposed option‐implied ambiguity has strong predictive power for future returns of SSE 50 ETF. Out‐of‐sample tests also verify the significant predictive ability of the option‐implied ambiguity to the equity returns.

Quantitative easing and correlation dynamics in the aftermath of the Great Recession: A dynamic conditional correlation with exogenous variables approach

AbstractIdentifying the effects of quantitative easing (QE) on asset return correlations is critical to assessing such policies’ impact across financial markets. In this paper, we use a dynamic conditional correlation model that allows us to measure the impact of unconventional monetary policy on time‐varying correlations. Our results suggest that QE significantly affected correlations between stocks and bonds after the Great Recession via short‐term portfolio balance effects. The findings are critical for policy‐makers and practitioners alike. Central banks should consider the impact of monetary policy on asset correlations in their cost–benefit analyses. Likewise, portfolio managers are encouraged to factor in the effects of monetary policy on correlations to optimize portfolios and reduce potential losses strategically.

A Canonical Representation of Block Matrices with Applications to Covariance and Correlation Matrices

Abstract We obtain a canonical representation for block matrices. The representation facilitates simple computation of the determinant, the matrix inverse, and other powers of a block matrix, as well as the matrix logarithm and the matrix exponential. These results are particularly useful for block covariance and block correlation matrices, where evaluation of the Gaussian log-likelihood and estimation are greatly simplified. We illustrate this with an empirical application using a large panel of daily asset returns. Moreover, the representation paves new ways to model and regularize large covariance/correlation matrices, test block structures in matrices, and estimate regressions with many variables.

The impact of cryptocurrency-related cyberattacks on return, volatility, and trading volume of cryptocurrencies and traditional financial assets

We investigate the impact of cryptocurrency-related cyberattacks on the cryptocurrency market and traditional financial markets. The dataset consists of historical cyberattack data and trading data for twenty cryptocurrencies, three cryptocurrency uncertainty indices, five payment companies, four stock indices, a commodity index, and gold. We find that cyberattacks are associated with negative returns, increased volatility, and increased trading volume not only for the cryptocurrencies but also for the payment companies, the financial and technology sectors, and the general stock market. However, the impact of cyberattacks on cryptocurrencies has been decreasing over time, while the impact on payment companies and the financial sector has been increasing. Moreover, gold prices have shown a positive response to these cyberattacks. These results underscore the need for enhanced cybersecurity measures in the fintech sector and may inform both policymakers and market participants.