Portfolio Performance Research Articles

AI-ENHANCED PORTFOLIO MANAGEMENT: CRAFTING OPTIMAL INVESTMENT STRATEGIES FOR DIVERSE FINANCIAL MARKETS

This study investigates the transformative potential of artificial intelligence (AI) in portfolio management across diverse financial markets. It aims to develop a comprehensive framework that enhances investment strategies in developed, emerging, and frontier markets through AI techniques. The research will employ a mixed-methods approach, combining quantitative and qualitative methodologies. Initially, extensive secondary data will be collected from market reports, financial databases, and previous studies. This data will encompass market-specific characteristics, AI-based portfolio strategies, and financial indicators. AI methods, including neural networks, machine learning models, and natural language processing applications, will then be utilized to analyze portfolio performance across various market scenarios. The anticipated outcome of this study is a versatile AI-driven framework that accommodates the unique aspects of different financial markets. By optimizing asset allocation, risk management, and predictive analytics, this framework will provide portfolio managers with evidence-based recommendations to enhance the stability and performance of their investments. The study aims to demonstrate how AI can mitigate risks associated with market volatility, liquidity issues, and regulatory constraints, leading to a more resilient and data-driven approach to portfolio management on a global scale KEYWORDS: AI integration in finance, Portfolio performance metrics, Compounded Annual Growth Rate (CAGR), Volatility reduction

Quantile volatility connectedness among themes and sectors: Novel evidence from China

Against the backdrop of increasing interest in factor investing, this paper explores volatility connectedness among theme factors and sector indices in the Chinese stock market using the Diebold-Yilmaz approach with quantile factor VAR. Our static analysis reveals significant similarities at extreme quantiles, contrasting with the conditional median. We find that higher connectedness measures at extreme quantiles correspond to improved performance of portfolios based on sectors and themes. Additionally, dynamic analysis indicates a strong link between total connectedness and closely tied risk events in China. Moreover, variations in connectedness between the right and left tails serve as a market-level risk proxy, significantly influencing the performance of both themes and sectors. These findings underscore the importance of understanding volatility connectedness for devising effective investment strategies and enhancing risk management practices in the Chinese stock market.

The Impact of ESG Ratings on Investment Decisions in the Energy Sector During Uncertain Times

With increasing global awareness of sustainability, the financial sector must inevitably adapt. Our research investigates the role of Environmental, Social, and Governance (ESG) ratings in investment decision-making, particularly in the energy sector, by examining their impact on portfolio performance. The study aims to assess the impact of ESG integration on portfolio risk and returns. Using data from the SP500 index, econometric models and Monte Carlo simulations are employed to evaluate how ESG considerations influence portfolio optimization and risk management. The study reveals that integrating ESG criteria into investment strategies, especially during market volatility, may not always directly affect returns, they provide significant benefits in terms of risk mitigation and ethical investment alignment.

ESG Scores’ Impact on Portfolio Performance, An Evidence from Indonesia

This study is to determine the effect of using the Refinitiv ESG score in stock picking and its impact on portfolio performance using the ESG Score. Methodology for this research using a two-sample t-test of Net Asset Value (NAV) price-return portfolios and the Sharpe ratio as a proxy for risk adjustment return for portfolio evaluation. The results of this study indicate that the use of a Refinitiv rating may serve as a suitable metric for stock selection strategy because companies with higher ESG scores tend to exhibit superior performance. Since ESG ratings in Indonesia are still difficult to obtain, those with access to ESG ratings will have more advantages. Greater return performance is followed by an increased level of risk. Given the assumption of a well-diversified portfolio, it is hypothesized that the increased risk can be attributed to a larger variance coefficient. So that the Sharpe ratio must be used for portfolio evaluation to measure risk-adjusted returns.

Beyond REITs, Investing in Real Estate Funds

This study examines the performance of U.S. real estate funds of both exchange-traded funds (ETFs) and mutual funds, including passive ETFs, active ETFs, retail-class mutual funds, institutional-class mutual funds, and index mutual funds. The active ETF portfolio stands out with the highest returns and Sharpe ratio and consistently higher alphas in the factor models. It exhibits more prominent performance in downtrend markets and in recent years, whereas its peer retail-class mutual fund portfolio has consistently shown inferior performance. The passive ETF and the index mutual fund portfolios have never surpassed the performance of the active ETF portfolio. Neither choosing the cheap index strategy nor paying for high-cost mutual fund managers proves to be the optimal option for investors. The outperforming portfolio is found to be active ETFs, which sheds light on the continuing surge in their fund flows.

METODE MEAN-SEMIVARIANCE DALAM PEMBENTUKAN PORTOFOLIO REKSA DANA SAHAM TERBAIK BAROMETER BAREKSA

The most popular investment product today is mutual funds. One of the factors in selecting mutual funds is the low investment risk. This risk can be minimized again by combining several assets and then compiling them into a portfolio. The portfolio formation method used in this study is the Mean-Semivariance method and the Sharpe Index to calculate portfolio performance. The data used is the daily net asset value per unit of Mandiri Investa Atraktif Syariah, Rencana Cerdas, Manulife Saham SMC Plus and BNP Paribas Solaris for the period January 3 2022 to March 9 2023, Jakarta Composite Index (IHSG) data as a benchmark and BI-7 Day Reverse Repo Rate as a riskfree interest rate. The minimum risk of the portfolio will be achieved by compiling a portfolio of two mutual funds, namely Mandiri Investa Atraktif Syariah with a weight of 92,50% and the Smart Plan with a weight of 7,50% with an expected return rate of 0,00019 and a risk of 0,000000663. The Sharpe Index is 0.08971 indicating that the portfolio formed has good performance and can be used as a choice of investment assets by investors.

The Influence of ESG Factors on Portfolio Performance Based on the Perspective of Markowitz Portfolio Theory

Abstract: In this paper, the inclusion of Environmental, Social, and Governance (ESG) factors in portfolios is investigated to determine their impact on portfolio performance and its mechanism. Based on the data collected by Bloomberg for 10 stocks from 2003-2023 and Markowitz's portfolio model, it is found that: (1) the inclusion of ESG constraints negatively affects portfolio performance; (2) the inclusion of ESG constraints shifts the GMVP to the right and reduces the convexity of the efficient frontier, thus lowering the portfolio's performance. This study enriches the literature on the factors affecting portfolio performance as well as responsible investment and ESG investment, and is of value to investors or organizations in making investment strategy choices.

An Empirical Analysis of the Performance of Luxury Watch Portfolios among High-Net-Worth Individuals in India During the COVID-19 Pandemic

This study empirically evaluates luxury watches owned by high-net-worth individuals (HNIs) in India as unconventional alternative assets providing diversifying benefits. During the COVID-19 pandemic, the major stock exchanges in India, NSE and BSE, faced negative returns and high volatility, igniting numerous conservative investors to divest from traditional investments and retain alternative assets, such as luxury watches, due to their low correlation to financial markets. Owing to supply chain disruptions and demand forces, the overall secondary watch market prices surged throughout this period, creating high economic value for investors. Through hypothesis testing and attribution analysis, this paper evaluates the performance of watch portfolios owned by 57 HNIs, comprising of 464 watches, to investigate whether luxury watches are viable investments during economic downturns within the domain of alternative investments. Hence, this study employs suitable attribution tools such as Sharpe ratio, M2 Alpha, Treynor Measure and Jensen’s Alpha to understand the strength of their performance. Using academic literature, market data and primary data, this study found that luxury watches provided substantial portfolio diversification benefits and outperformed traditional assets like the NIFTY50 and gold in terms both nominal and risk adjusted returns during the pandemic. Brands such as Patek Philippe, Rolex, and Audemars Piguet achieved the highest performance, as Patek Philippe demonstrated superior risk-return trade-offs. Despite challenges such as valuation complexities and liquidity constraints, luxury watches provided remarkable upside potential, benefiting from a high retention rate due to their unique emotional features. Ultimately, the findings suggest that luxury watches can be viable alternative investments considering that 65% of these HNIs viewed their watch purchases as investment opportunities.

Online Investor Sentiment via Machine Learning

In this paper, we propose utilizing machine learning methods to determine the expected aggregated stock market risk premium based on online investor sentiment and employing the multifold forward-validation method to select the relevant hyperparameters. Our empirical studies provide strong evidence that some machine learning methods, such as extreme gradient boosting or random forest, show significant predictive ability in terms of their out-of-sample performances with high-dimensional investor sentiment proxies. They also outperform the traditional linear models, which shows a possible unobserved nonlinear relationship between online investor sentiment and risk premium. Moreover, this predictability based on online investor sentiment has a better economic value, so it improves portfolio performance for investors who need to decide the optimal asset allocation in terms of the certainty equivalent return gain and the Sharpe ratio.

Distributionally Robust Portfolio Optimization under Marginal and Copula Ambiguity

AbstractWe investigate a new family of distributionally robust optimization problem under marginal and copula ambiguity with applications to portfolio optimization problems. The proposed model considers the ambiguity set of portfolio returns in which the marginal distributions and their copula are close—in terms of the Wasserstein distance—to their nominal counterparts. We develop a cutting-surface method to solve the proposed problem, in which the distribution separation subproblem is nonconvex and includes bilinear terms. We propose three approaches to solve the bilinear formulation, namely (1) linear relaxation via McCormick inequalities, (2) exact mixed-integer linear program reformulation via disjunctive inequalities, and (3) inner approximation method via a novel iterative procedure that exploits the structural properties of the bilinear optimization problem. We further carry out a comprehensive set of computational experiments with distributionally robust portfolios featuring Conditional Value-at-Risk (CVaR) measures. These tests aim to compare the accuracy of the proposed algorithms, analyze the impact of the radius of the Wasserstein ambiguity ball on the portfolio, and assess portfolio performance. We use a rolling-horizon approach to conduct the out-of-sample tests, which show the superior performance of the portfolios under marginal and copula ambiguity over the equally weighted and ambiguity-free Mean-CVaR benchmark portfolios.

Investment Horizon and Portfolio Performance: A Study on Indian Stock Market

Investment Horizon and Portfolio Performance: A Study on Indian Stock Market

Promoters as social controls to facilitate knowledge sharing, conflict management and innovation project portfolio performance

Organizational control theory emphasizes aligning members' actions with organizational goals through formal and social controls. In innovation management, formal controls like project management or stage‐gate processes are limited to measurable and standardized areas. For situations that are complex, unpredictable and highly idiosyncratic, social controls need to be applied for alignment. Knowledge sharing and competitive conflicts are two such innovation‐related phenomena that elude formal control and instead need social controls for alignment. In this research, we propose that promoters—individuals who actively support innovation—serve as social control agents. While previous research has shown the positive effect of single promoters on individual innovation project success, we propose a comprehensive implementation of all four promoter roles, and we test their joint effect on the intermediate outcomes of knowledge sharing and competitive conflict management facilitating innovation project portfolio performance. Drawing on cross‐industry data of 125 firms collected from 986 employees, this article provides empirical evidence that comprehensive implementation of all four promoter roles enhances knowledge sharing and reduces competitive conflicts, thereby improving innovation project portfolio performance. The research reframes promoters as social control agents, emphasizing their collective necessity for managing complex organizational issues and contributing to overall project success.

Do retail investors gamble more during lockdown?

AbstractRetail investors are known to favor stocks with lottery‐like features and trade too much. Less is known about their intertemporal demand and risk‐taking behavior in lottery‐type stocks. We use intraday transaction data between September 2019 and June 2020 from the Stock Exchange of Thailand to test how individual's risk attitude changes with respect to decline in their wealth prospects during the COVID‐19 lockdown. The behavior of the investors supports a reference dependent preference. Confronted with lowered wealth prospects, retail investors substantially reduce their underweighting in nonlottery stocks while increasing overweighting and turnover frequency in lottery stocks resulting in deteriorating portfolio performance.

Momentum on historical high

This paper decomposes the long side of momentum portfolio holdings by comparing the location of recent prices to historically high prices. Stocks with prices near historical highs represent 45 percent of holdings in momentum and 70 percent of returns. Momentum portfolios formed in the stock universe with stocks closed to historical highs provide 6.2% alpha in comparison with 1.3% for momentum formed from stocks out of historical highs. The historical high momentum portfolio performance is sustainable to control for the lagged momentum of Novy-Marx (2012) and the 52-week high ratio of George and Hwang (2004).

Hedging political risk in international portfolios

We show that internationally diversified portfolios carry sizeable political risk premia and expose investors to tail risk. We obtain political efficient frontiers with and without hedging political risk using a portfolio selection model for skewed distributions and develop a new asymptotic inference test to compare portfolio performance. Politically hedged portfolios outperform a broad market index and the equally weighted portfolio for US, Eurozone, and Japanese investors. Political risk hedging is not subsumed by currency hedging, and the diversification gains of politically hedged portfolios persist under currency hedging and transaction cost frictions. Hedging political risk induces equity home bias but does not fully explain the puzzle.

Portfolio framing and diversification in a disposition effect experiment

We experimentally test an intervention designed to reduce investors’ disposition effect by prompting them to identify their worst asset, from the standpoint of its impact on future portfolio performance. We find that this intervention is mildly effective, and significantly more so for participants who correctly identify their worst asset, and/or sell the asset they identify. We also find that participants who correctly understand diversification in a financial literacy questionnaire exhibit larger disposition effects in the experiment. The latter finding raises concerns over the external validity of standard experimental paradigms used to study the disposition effect.

Gender gap in investment performance revisited: The role of attention

AbstractThis paper revisits the effect of gender on portfolio performance, exploring the hypothesis that investors may derive fewer benefits from increased financial attention due to disparities in financial confidence. Using data from trading accounts of over 745,000 investors, we find that the difference in investment performance between men and women depends on the level of attention that they pay to their portfolios. Furthermore, our results indicate that the positive effects of investor attention are primarily attributable to young men, who appear to benefit the most from heightened attentiveness.

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

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

Advancing ESG Portfolio Optimization: Methods, Progress, and Future Directions

Objective - The integration of environmental, social, and governance (ESG) criteria into investment portfolios has emerged as a critical field of study, underscoring the interconnectedness between financial markets and global sustainability objectives. Methodology/Technique - This systematic literature review analyzes 157 academic documents, focusing on ESG portfolio optimization methodologies and identifying emerging trends. Key methods reviewed include genetic algorithms, dynamic optimization models, multi-objective optimization frameworks, and machine learning techniques. Findings - Despite considerable advancements, gaps remain, such as the need for broader application across diverse markets and asset classes, improved risk-return assessments, and standardized ESG data reporting. Future research should also investigate the role of central banks and regulators in fostering sustainable finance. Novelty - By addressing these gaps, stakeholders can better align investment practices with sustainability goals, contributing to a more resilient and inclusive global economy. Type of Paper: Review JEL Classification: G11, Q56, G28, G32 Keywords: Sustainable Investment, Sustainable Finance, ESG Portfolio Performance, ESG Risk Management, ESG Portfolio Optimization Reference to this paper should be referred to as follows: Billah, A.L; Koesrindartoto, D.P; Faturohman, T. (2024). Advancing ESG Portfolio Optimization: Methods, Progress, and Future Directions, Acc. Fin. Review, 9(2), 65 – 73. https://doi.org/10.35609/afr.2024.9.2(2)

Risk and Return Analysis of Stocks of Nepalese Commercial Banks

This research article analyzes the impact of risk and return of Nepalese commercial bank stocks on portfolio returns to assist investors in making informed investment decisions. It aims to examine the effects of individual bank stock returns, risks, market return, and market risk (beta) on overall portfolio performance. The study utilizes a quantitative approach, employing descriptive statistics, comparative (trend) analysis, correlation analysis, and hypothesis testing. Secondary data was collected from 18 commercial banks in Nepal, including post-merger banks, covering the fiscal years from 2015/16 to 2021/22. Statistical tools such as SPSS and EViews were used for analysis. The findings indicate that investors seeking higher returns might consider Prabhu Bank, which offers high mean returns but also comes with higher volatility. In contrast, risk-averse investors may prefer banks like NMB and Nabil, which provide lower mean returns but more stable performance. Notably, this research contributes to the understanding of the risk-return relationship in the context of 18 Nepalese commercial banks post-merger, providing new insights for investors. This study highlights the importance of analyzing individual bank stocks and their associated risks for portfolio construction. By understanding the dynamics of risk and return, investors can optimize their investment strategies and enhance portfolio performance. Overall, this research fills a gap in existing literature by focusing on the Nepalese commercial banking sector and its implications for investor decision-making. The insights gained from this study can guide investors in navigating the complexities of the stock market, ultimately leading to more informed and strategic investment choices. Future research could expand on this work by exploring additional factors influencing stock performance and investor behavior in the Nepalese context.