ABSTRACT This paper examines how incorporating regret aversion affects portfolio construction and performance in emerging stock markets. Using daily data from 2015–2025, the paper builds multivariate six-asset portfolios for Central and Eastern Europe (CEEC), East Asia, and Latin America, alongside a G7 benchmark. A regret-minimising portfolio is compared with traditional minimum-variance and maximum-Sharpe portfolios across pre-crisis and crisis periods. Results show that regret-averse portfolios are more diversified and place greater emphasis on low-correlation assets, reducing the likelihood of extreme underperformance relative to the best-performing asset. Emerging markets exhibit higher regret than developed markets, with the Latin American portfolios showing the largest regret levels. Notably, the CEEC portfolio consistently demonstrates the strongest performance, delivering the lowest regret and favourable risk-return outcomes in both subsamples. Robustness checks, including bootstrapping, variance-equality tests, and varying regret preferences, confirm the stability of the regret-minimising approach and highlight its practical relevance for behaviourally sensitive investors.

Purpose — This study aims to address issues in the preparation of passive investment portfolios using stocks listed on the Iraq Stock Exchange. The main focus is to build a common stock portfolio that can achieve the best trade-off between return and risk, adjusted to the preferences and risk tolerance of investors in the financial market. Design/methodology/approach — This study uses an explanatory quantitative approach by applying the fuzzy time series method to handle ambiguity and volatility in the monthly closing price data of eight banks listed on the Iraqi Stock Exchange during the period 2012–2021. The analysis was conducted by comparing the performance of the passive investment portfolio against the market portfolio performance. Findings — The results show that passive investment portfolios with high beta values (βpt) outperform other portfolios because they achieve an optimal balance between return and risk. However, it was found that bank stock returns are highly sensitive to market movements, and their performance was limited by sectoral concentration and inefficiencies in bank management. Practical implications — Investors in the Iraqi capital market are advised to adopt modern portfolio formation models and prioritize high-beta strategies, while still considering other factors such as company size, profitability, and liquidity to diversify risk. In addition, financial analysts and brokers are encouraged to expand passive portfolio models to sectors other than banking. Originality/value — This article presents a comprehensive algorithm for the passive portfolio formation process in the context of the Iraqi capital market, which has specific challenges in the form of an unstable environment and limited financial instruments. The use of fuzzy time series in this study contributes to the literature on estimation methods in emerging markets.

Market equilibrium is characterized by a state wherein aggregate demand equals aggregate supply for all assets, a condition arising from consumers maximizing utility within budget constraints and producers maximizing profits. This paper investigates a financial market populated by non-homogeneous investors who may employ heterogeneous deviation measures to formulate their risk functions. By integrating the minimax risk diversification principle with the framework of individual utility maximization, we analytically derive the master fund for each investor. Furthermore, we establish the necessary and sufficient conditions for the existence of a unique non-negative equilibrium price system for risky assets and provide its explicit formula. A key finding is that the market portfolio is a convex combination of all investors’ master funds.

ABSTRACT The capital asset pricing model (CAPM) is a widely adopted model in asset pricing theory and portfolio construction because of its intuitive nature. One of its main conclusions is that there exists a global market portfolio that each rational investor should hold in proportion to the risk‐free asset. In this paper, we demonstrate theoretically and through an example that the CAPM cannot hold in a multi‐currency environment. This is because it produces different market risk premia depending on the investor's base currency unless each exchange rate is uncorrelated with the asset prices in the portfolio.

This study examines the performance of multi-asset portfolios in global emerging markets, emphasizing their exposure to systemic risk and risk-adjusted returns. The analysis encompasses portfolios from regions such as Southeast Asia, the Middle East and Central Asia, Central and Eastern Europe, Africa, and Latin America. The research uses daily data, covering a 10 years period. Two advanced methodologies are applied in the portfolio construction – the Mahalanobis distance and the Stutzer ratio. The financial turbulence index constructed for the systemic risk measurement reveals a pronounced allocation bias toward a single asset, driven by its distinctive attributes. Interestingly, the asset with the highest weight in the portfolio originates from frontier markets, which are less integrated into the global financial system and thus more insulated from global economic shocks. The Stutzer ratio, through its calculation of the decay parameter theta, provides insights into whether an emerging market portfolio is characterized by high volatility and frequent market fluctuations or is more aligned with long-term investment strategies that emphasize stability and consistent performance. The results indicate that all emerging markets portfolios have higher Stutzer ratio than the developed portfolio, which indicates better risk-adjusted results. However, the theta parameter is mostly lower in the emerging markets portfolios, suggesting higher risk in these markets. The highest Sharpe ratio is found in the African countries portfolio, while the best portfolio, when using the more advanced Stutzer ratio, is with Latin American countries. This study provides insightful guidance for international investors exploring opportunities in emerging markets, focusing on systemic risk and evaluating returns through a risk-adjusted lens.

Using novel technologies to provide flexibility to distribution systems by exploiting a market portfolio approach

The Capital Asset Pricing Model (CAPM) has long been a foundational framework in finance for predicting asset returns based on systematic risk. It assumes that expected returns are a linear function of an assets beta relative to the market portfolio. This study evaluates CAPMs predictive performance across four U.S. sectors: Technology, Financials, Energy, and Retail, using monthly data from 2020 to 2025. Beta estimates are obtained through static OLS, rolling regressions, Blume adjustment, Vasicek shrinkage, and conditional betas based on a rolling covariance approximation to DCC-GARCH. The in-sample and out-of-sample predictive performance of CAPM is tested, and the results are benchmarked against the FamaFrench 3-factor model. The findings indicate heterogeneous CAPM performance across sectors: predictive accuracy is stronger in Technology and Financials, and weaker in Energy and Retail. Beta estimation improvements, particularly shrinkage and conditional betas, consistently reduce forecasting errors, while multi-factor models add further explanatory power. Practical, sector-specific recommendations for enhancing the application of CAPM are provided.

Quantile analysis of ESG diversification benefits in CEE stock market portfolios

This study aims to estimate the β-CAPM for firms listed on the Mexican Stock Exchange Price Index (IPC) by incorporating Value at Risk (VaR) measures during periods of high market volatility. We apply five risk estimation methodologies: (1) Historical Simulation VaR (VaR-SH), (2) Delta-Normal VaR (VaR-δN), (3) Monte Carlo Simulation VaR (VaR-MC), (4) Threshold-GARCH-based VaR (TGARCH-VaR), and (5) Expected Shortfall (ES). The results demonstrate consistency across the different methodologies during high-volatility periods. Nonetheless, we identify two important limitations: β-CAPM is constrained to equity portfolios, and VaR-based methods may underestimate tail risk during extreme market events. This study enhances the understanding of market risk exposure in the Mexican stock market by offering a comparative analysis of multiple VaR methodologies. It provides a valuable reference for assessing the relative riskiness of individual securities against the market portfolio, especially under conditions of financial stress.

In this study, we aim to provide a comprehensive analysis of the risk management potential of sectoral Credit Default Swaps (CDSs) within financial portfolios. Our objectives are threefold: (i) to investigate the safe haven properties of sectoral CDSs; (ii) to assess their hedging effectiveness and evaluate the diversification benefits of incorporating sectoral CDSs into both conventional and Islamic stock market portfolios; and (iii) to compare these findings with those obtained from alternative assets such as the VSTOXX, gold, and Bitcoin indices. To achieve this, we estimate time-varying hedge ratios using a range of multivariate GARCH (MGARCH) models and subsequently compute hedging effectiveness metrics. Conditional correlations derived from the Asymmetric Dynamic Conditional Correlation (ADCC) model are employed in linear regression analyses to assess safe haven characteristics. This methodology is applied across different subperiods to capture the impact of the crypto currency bubble and the COVID-19 pandemic on hedging performance.

This study aims to evaluate the performance of LQ45 stocks against systematic risk using the Capital Market Line (CML) approach. The CML, derived from the Capital Asset Pricing Model (CAPM), represents the risk-return relationship between efficient portfolios and the market portfolio, incorporating both the risk-free rate and the total risk (standard deviation). Unlike the Security Market Line (SML), which uses beta as a measure of systematic risk, the CML emphasizes total risk in the context of portfolio efficiency. This research employs a quantitative descriptive method, analyzing secondary data of LQ45 constituents listed on the Indonesia Stock Exchange (IDX) for the period from January 2023 to December 2024. The Sharpe Ratio was calculated to assess the performance of individual stocks, followed by comparison with the CML benchmark. The findings reveal that only a limited number of stocks demonstrate efficiency by lying above CML, while the majority fall below, indicating suboptimal risk-adjusted returns. These results support the theoretical proposition that in efficient markets, only well-diversified portfolios, not individual assets, can consistently align with the CML. This study contributes to the growing literature on asset pricing by emphasizing the role of total risk in portfolio evaluation and provides practical implications for investors in constructing efficient portfolios.

Studying and comprehending the eigenvalue distribution of the correlation matrices of stock returns is a powerful tool to delve into the complex structure of financial markets. This paper deals with the analysis of the role of eigenvalues and their associated eigenvectors of correlation matrices within the context of financial markets. We exploit the meaningfulness of Random Matrix Theory with the specific aspect of the Marchenko-Pastur distribution law to separate noise from true signal, but with a special focus on giving an interpretation of what these signals mean in the financial context. We empirically show that the highest eigenvalue serves as a proxy of market spillover. Furthermore, based on an analysis of portfolio betas, we prove that the eigenvector associated with this eigenvalue is the market portfolio. These analyses of portfolio betas also reveal that the second- and third-highest eigenvalues, and their associated eigenvectors, result in some cases of counter-behavior that makes them suitable to be a safe haven during high-volatility periods. The analysis is performed on a set of indices coming from developed and emerging countries over a time period ranging from 2015 to 2024.

This paper analyzes the volatility relationship between the Romanian BET index and the U.S. SFT-500 index during the period 2019–2024, with a particular focus on the impact of political and geopolitical shocks. The study investigates whether financial markets in emerging economies react symmetrically or asymmetrically to external shocks originating from mature markets, especially during periods of political uncertainty. The research period includes four major systemic events: the COVID-19 pandemic, the military conflict in Ukraine, the 2024 U.S. presidential elections, and the 2024 Romanian elections, all of which generated significant volatility in global markets. The methodological approach combines time series econometrics with the Impulse Indicator Saturation (IIS) technique to identify structural breaks and outliers, without imposing exogenous assumptions about the timing of events. The econometric model includes autoregressive and lagged exogenous variables to estimate the influence of the SFT-500 index on the BET index, while IIS variables capture unanticipated political and economic shocks. Additionally, a Fractionally Integrated GARCH (FIGARCH) specification is applied to model the persistence of volatility over time, capturing the long-memory behavior often observed in emerging markets like Romania. The results confirm a statistically significant but partial synchronization between the two markets, with lagged and contemporaneous effects from the SFT-500 index on the BET index. Volatility in Romania is markedly higher and longer-lasting during domestic political episodes, confirming that local factors are a primary source of market instability. For investors, this underscores the need to embed political risk metrics into emerging market portfolios. For policymakers, it highlights how stronger institutions and transparent governance can dampen election- and crisis-related turbulence.

ABSTRACTThis paper develops an empirical methodology for extracting pricing factors from investor portfolio data. We apply this approach to the stockholdings of Norwegian individual investors from 1997 to 2017. A two‐factor model, featuring the market portfolio and a long‐short portfolio constructed from the holdings of investors sorted by age or wealth, explains both the common variation in portfolio holdings and the cross section of stock returns. Portfolio tilts toward the long‐short investor factor correlate with indebtedness, macroeconomic exposure, gender, and investment experience. Our paper illustrates the benefits of using holdings data for explaining the risk premia of financial assets.

Abstract It is already well established that neither the bias inherent in, nor the extent to which a multifactor specification of the Capital Asset Pricing Model (CAPM) prices behaviors (priors), as opposed to rationality (risk preferences) is decipherable from the output of any such model. Hitherto, empirical structures that facilitate either inference have been lacking. This study’s formal theory directly spans an empirical structure which nests inferences in respect of the bias inherent in a CAPM in inferences in respect of the extent to which the same CAPM prices risk preferences, as opposed to priors that are systemically realized (‘systemic priors’) within populations of agents. The resulting empirical evidence in respect of the Fama and French three factor model is unequivocal, namely that it solely prices systemic priors, not agents’ risk preferences, a finding that is consistent with the suspicion, in prior studies, that the market betas that are generated by the model are so high, it is unlikely they evince rational pricing. Contrarily, conditional on the presence, in markets, of non-globally risk averse agents, a multifactor CAPM which incorporates the market portfolio and market skewness factors prices agents’ risk preferences and systemic priors and outperforms all other candidate models.

We examine the unexplored relationships among performance pressures, bricolage, and innovation control systems in startups. Bricolage is a key strategy employed by entrepreneurs to create resources for their startups when they are faced with contextual challenges that lead to resource constraints. Bricolage involves using ‘whatever is at hand’ to create something new, combining available resources to address problems and seize opportunities. Given the necessity arising from the performance pressures exerted by several stakeholders on startups, we propose that bricolage is a means of addressing this challenge. In the context of pressures, scarce resources, and the search for opportunities, we contend that innovation control systems also play a significant role. The reason is that the various types of information content that they provide, whether financial (e.g. costs or forecasts) or non-financial (e.g. product market portfolios, roadmaps, or milestones), influence decision-making in an environment of pressure to innovate. In a sample of 335 startups, we identified higher levels of bricolage among those facing performance pressures. Furthermore, our findings reveal that non-financial (financial) innovation control systems positively (negatively) moderate the effect of performance pressures on bricolage.

This research paper aims to study the influence of Bitcoin (BTC), Crude Palm Oil (CPO), Crude Oil (WTI), the Dollar Rate (USD), and Gold (XAU), on Stock Market Portfolios (KLSE). Time series data for this investigation was obtained from Yahoo Finance and Investing.com. Furthermore, the Unit Root Test conducted found that the variables are stationary after 1st differencing. Moreover, since there was no Cointegration discovered between the variables, VAR was performed to determine the long-run causality effect, while the Wald Test was conducted to examine the short-run causality effect. The findings revealed that none of the variables contained a long-run relationship, whereas Bitcoin (BTC), Crude Palm Oil (CPO), and Gold (XAU) contained a short-run relationship with the independent variable (KLSE).

The socialization and education on investment and capital market portfolios at SMA Negeri 2 Bengkalis, Riau, is motivated by the lack of basic knowledge about the capital market among students, which can hinder their ability to make smart financial decisions in the future. This activity aims to provide comprehensive information about investments, portfolio management, and the importance of financial planning. The purpose of this socialization is to introduce students to various investment instruments such as stocks, bonds, and mutual funds, as well as techniques for analyzing risks and potential returns. This activity also aims to equip students with practical skills in managing their own portfolios. The methods used include presentations by capital market experts, Q&A sessions, and investment simulations. This approach is designed to actively engage students and provide hands-on experience in the world of investing. The expected outcomes include an increase in students' knowledge about investments and capital markets, the ability to make better investment decisions, and an awareness of the importance of personal financial planning.

This study evaluates the financial performance of investment firms using the Treynor-Black Method, which optimizes portfolios by combining high-alpha assets with the market portfolio to enhance risk-adjusted returns. The study applies the method to a sample of investment firms to examine its effectiveness in improving key performance metrics, including the Sharpe Ratio, Treynor Ratio, and Jensen's Alpha. The findings indicate that the Treynor-Black Method substantially improves portfolio performance, with optimized portfolios exhibiting higher Sharpe and Treynor Ratios and positive Jensen's Alpha. These results suggest systematic risk management and effective value addition through active management. However, the study acknowledges limitations such as reliance on historical data, potential data quality issues, and challenges in estimating alpha and beta. These constraints highlight the need for careful interpretation and suggest future research directions, including the use of real-time data and alternative optimization approaches. The study provides practical insights for investment managers, offering an enhanced framework for portfolio construction and performance evaluation. It contributes to the field by validating and extending the Treynor-Black Method, enhancing strategies for aligning portfolios with risk-return objectives.

This research note evaluates the suppliers’ perceived tourism potential of destination attributes and discusses the product and market portfolio identification issues in ethnic minority destinations at their infancy development stages. Findings from a field study in Congjiang County, China, show the emphasis on different values between the public and private suppliers – cultural values for the former and product values for the latter – may confuse market identification and targeting. Thus, this study suggests a market portfolio that bridges such differences and contributes to fulfilling immediate needs and long-term needs for sustainable ethnic cultural resource management and the residents’ well-being.