Portfolio Theory Research Articles

Relationship between Risk Appetite and Investment Decisions in High-Risk Ventures in South Korea

Purpose: The aim of the study was to examine the relationship between risk appetite and investment decisions in high-risk ventures in South Korea. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The relationship between risk appetite and investment decisions in high-risk ventures in South Korea reveals a strong correlation where investors with higher risk tolerance are more likely to engage in high-risk ventures. These investors are driven by the potential for substantial returns, despite the associated volatility and uncertainty. The findings indicate that cultural factors, economic conditions, and market dynamics in South Korea play a significant role in shaping this risk appetite. Unique Contribution to Theory, Practice and Policy: Prospect theory, risk parity theory & behavioral portfolio theory may be used to anchor future studies of relationship between risk appetite and investment decisions in high-risk ventures in South Korea. Practically, businesses should focus on several strategies to optimize the effectiveness of their insurance coverage in managing business interruption risks.

Is the volatility of yields for major crops grown in Germany related to spatial diversification at county level?

Abstract Recent evidence suggests a stabilizing effect of crop diversity on agricultural production. However, different methods are used for assessing these effects and there is little systematic quantitative evidence on diversification benefits. The aim of this study was to assess the relationship between volatility of combined crop yields (denoted as standard deviation) and diversity (denoted as Shannon’s Evenness Index SEI) for standardized yield data of major crop species grown in Germany between 1977 and 2018 (winter wheat, winter barley, silage maize and winter rapeseed) at the county level. Portfolio theory was used to estimate the optimal crop area share for minimizing yield volatility. On average, results indicated a weak negative relationship between volatility and the SEI during the past decades for the case of Germany. Optimizing crop area shares for minimizing volatility reduced yield variance on average by 24 % but was associated with a decrease in SEI for most counties. This was related to the finding that the stability of individual species, i.e., barley and wheat, was more effective in reducing the volatility of combined yields than the asynchronous variation in annual yields among crops. Future studies might include an increased number of crop species and consider temporal diversification effects for a more realistic assessment of the relation between yield volatility and crop diversity and test the relationship in other regions and production conditions.

The impact of local content curriculum on students’ cultural awareness and identity in Indonesian elementary schools

ABSTRACT This study investigated how local content curriculum (LCC) affected students’ cultural awareness and identity in Indonesian elementary schools. LCC lets schools tailor 20% of the instruction to local contexts and needs. The study used a mixed-methods approach with 200 students from 10 schools in Banten, a diverse province. The data collection and analysis methods involved a questionnaire, a test, a portfolio, an interview, statistics, and thematic analysis. The study found that LCC improved students’ cultural awareness and identity significantly and was implemented in different ways with various partners. However, the study also uncovered that LCC clashed with the national standardised examination (NSE), which neglected LCC. The study suggested that LCC had potentials for enhancing students’ cultural competence and readiness for the globalised world. The study contributed to the literature on LCC, NSE, cultural awareness, and cultural identity, and offered some recommendations for policy makers, practitioners, and researchers.

Efficient convex PCA with applications to Wasserstein GPCA and ranked data

Convex PCA, which was introduced in Bigot et al. (2017), modifies Euclidean PCA by restricting the data and the principal components to lie in a given convex subset of a Hilbert space. This setting arises naturally in many applications, including distributional data in the Wasserstein space of an interval, and ranked compositional data under the Aitchison geometry. Our contribution in this paper is threefold. First, we present several new theoretical results including consistency as well as continuity and differentiability of the objective function in the finite dimensional case. Second, we develop a numerical implementation of finite dimensional convex PCA when the convex set is polyhedral, and show that this provides a natural approximation of Wasserstein GPCA. Third, we illustrate our results with two financial applications, namely distributions of stock returns ranked by size and the capital distribution curve, both of which are of independent interest in stochastic portfolio theory. Supplementary materials for this article are available online.

The marginal cost of capital: a portfolio theory perspective

Markowitz’s portfolio theory is shown to have profound implications for one of the core issues in corporate finance: the marginal cost of capital. Most researchers and practitioners would agree that if a firm’s projects are all similar, they should all be discounted at the same marginal cost of capital (MCC), which is also the firm’s average cost of capital (ACC). However, when a firm expands by accepting a new project, its weight in investors’ portfolios increases, and investors will be willing to accept this only if the firm’s expected return increases. Thus, the new project’s MCC must be higher than the ACC. We derive the MCC in a portfolio context. The difference between the MCC and the ACC is economically significant for large and volatile firms, and for firms that are not widely held. The portfolio theory perspective provides a unified explanation for the price reaction to SEOs, IPOs, and stock repurchases.

Research on the Development of Investment Portfolio Theory

This paper provides a comprehensive analysis of portfolio theory evolution and its practical applications, tracing its development since Harry Markowitz introduced Modern Portfolio Theory (MPT) in 1952. The urgency to enhance capital market efficiency, optimize asset portfolios, and effectively measure and manage risks has intensified due to the rapid transmission of risk across global financial markets. This study reviews historical advancements and recent achievements in portfolio theory and practice. Furthermore, it constructs a theoretical research framework to guide the future development of quantitative investment strategies, focusing on active portfolio management. This framework also delineates several prospective research avenues. The advent of artificial intelligence and big data has transformed portfolio theory into a multidisciplinary nexus involving mathematical statistics, machine learning, and behavioral finance. This integration is crucial for refining asset portfolio optimization and understanding the dynamics of risk spillover and its determinants. The findings and theoretical advancements discussed herein are vitally important for fostering the sustainable development of capital markets and ensuring economic and financial stability. This study not only revisits foundational theories but also sets the stage for pioneering future research in financial analysis and portfolio management.

Portfolio resampling in the Brazilian stock market

Markowitz optimization plays a crucial role in modern portfolio theory. However, it is well known that Markowitz optimization is highly affected by estimation errors in the mean vector and covariance matrix, resulting in extreme and/or unrealistic portfolio weights, lack of diversification, and poor out-of-sample performance. In response to these challenges, Michaud and Michaud (1998) proposed a heuristic portfolio resampling approach aimed to deliver more diversified and better out-of-sample portfolio performance. This approach has received both criticism and praise among academics and practitioners, with the main critique being the unclear economic benefits of applying this method to empirical data. To contribute to this ongoing debate, our study assess the performance of the Michaud and Michaud (1998) portfolio resampling approach using data from the Brazilian stock market. Additionally, we evaluate whether a resampling approach based on factor structure can yield superior out-of-sample performance. Our findings indicate no evidence of superiority over Markowitz optimization, reinforcing criticisms of the portfolio resampling approach.

Research on the Optimal Portfolio of New Energy Industry Based on Markowitz Model

Based on Markowitz's portfolio theory, the risks and returns of stocks can be obtained from calculating the historical data, ensuring effective returns with low risk by decentralized investment, which has a considerable degree of practical significance to China's public investment under the current situation. In recent years, the total market capitalization of the new energy industry and the attainable gains from it are growing rapidly, in which case investors need to analyze and evaluate the volatility to determine how to invest. This paper extracts the historical closing price of new energy automobile related industry 7 stocks from June 2018 to March 2024 through the SuperMind database and establishes the mean-variance model, showing the optimal portfolio of new energy industry in the market with short-selling and the market without short-selling and giving a practical investment proposal on weights allocation.

Research on the Investment Portfolio in Technology and Consumer Goods Industries

This research investigates investment portfolios in the U.S. technology and consumer goods sectors, employing Modern Portfolio Theory (MPT) and the Markowitz Model to analyze and compare their risk-return profiles. The study highlights that the technology sector demonstrates a high-risk and high-return profile, making it attractive for risk-seeking investors aiming for significant gains amidst market volatility. In contrast, the consumer goods sector, with lower volatility, appeals to risk-averse investors who prefer stable and predictable returns. Key findings strongly emphasize the importance of aligning investment choices with individual investor preferences, illustrating how specific industry characteristics can influence investment strategies. The research suggests that investment success is considerably enhanced when portfolios are tailored to match individual risk tolerance and investment goals. This strategic approach provides a robust framework for guiding investors to make informed decisions that reflect their personal preferences and financial objectives, thereby helping them navigate market complexities and enhance portfolio performance.

Comparison of Markowitz Model and Single Index Model with ESG Factors Involved

ESG considerations have become increasingly prominent within the realms of investor and corporate decision-making, underscoring the importance of employing robust methodologies for incorporating ESG factors into portfolio construction. This study aims to leverage the Markowitz Model and Single Index Model to construct portfolios utilizing a selection of 10 stocks, evaluating their applicability across various conditions, particularly investors' risk tolerance levels. Utilizing the solver function within Microsoft Excel, graphical representations will be generated under four distinct constraints, facilitating comparisons based on both graphical depictions and accompanying data analysis. The findings reveal that, under specified conditions, the two models exhibit negligible differences, while highlighting the significant role of ESG constraints in portfolio construction. Nonetheless, given the distinct assumptions and conditions underlying each model's calculations, investors retain the flexibility to choose either approach for portfolio analysis. This research underscores the impact of ESG factors on asset allocation outcomes within both models, offering valuable insights into ESG investing practices and the comparative performances of the Markowitz Model and the Single Index Model.

Toward a portfolio theory of talent development: Insights from financial theory, illustrations from the Asia-Pacific

We propose Talent Portfolio Theory (TPT) as a new framework for studying human resource development. Drawing insights from Modern Portfolio Theory in financial investment, TPT views a nation’s talent development as creating a “talent portfolio” composed of four “B”s: brain train, brain gain, brain circulation, and brain linkage. TPT attends to how a talent portfolio, like a financial one, is diversified to minimize risk, and how diversification can be maintained via rebalancing. As such, TPT provides a framework that captures the overall picture of a country’s talent strategy and offers a lens through which to understand how a country changes or “rebalances” its talent portfolio over time. It also provides a tool for examining cross-national variation in talent development strategy. We illustrate the utility of TPT with the cases of Japan and Singapore. While human resource development was crucial to the economic rise of both countries, TPT demonstrates that Japan’s and Singapore’s approaches to constructing and rebalancing their talent portfolios took different routes with diverging outcomes. We conclude with discussions of theoretical and policy implications of this new approach for the study and implementation of talent development.

Harry Markowitz, the Cowles Commission, and portfolio theory

Harry Markowitz, the Cowles Commission, and portfolio theory

Risk spillovers between Chinese new energy futures and carbon-intensive assets: Asymmetric effect, time–frequency dynamics, and portfolio strategies

This study investigates the asymmetric time–frequency risk spillovers between Chinese new energy futures and carbon-intensive assets by using a time-varying parameter vector autoregressive connectedness approach. The results reveal that, in both the return and volatility spillover cases, industrial silicon futures and lithium carbonate futures generally are the net receivers of risk spillovers as regards the relationships with carbon-intensive sectoral stocks and fossil energy futures. In addition, there exists an asymmetric spillover effect, where spillovers based on bad news are higher than those based on good news. Meanwhile, return and volatility spillovers are extremely intensive in the short term as compared to the medium the long term. Finally, this study develops portfolio strategies by constructing bivariate and multivariate portfolios comprised of new energy futures and carbon-intensive assets. The bivariate portfolio analysis indicates that industrial silicon futures and lithium carbonate futures can well hedge against carbon-intensive sectoral stocks. The multivariate portfolio analysis shows that allocating the smallest share of petrochemical stocks and steel stocks can mitigate investment risks. These findings have important implications for investors and policymakers.

Financial Portfolio Analysis of Single Households: Monthly Saving and Financial Assets

The purpose of this study was to analyze the financial portfolios of single-person households. For the analysis, data from the Korean Labor Panel Survey (2021) was utilized, comprising 2,905 single-person households. The major findings are as follows: First, the proportion of households with monthly savings was 32.0%, while the proportion of households holding financial assets was 72.1%. Second, regarding the composition of monthly savings, single-person households predominantly held savings accounts (93.3%), followed by insurance (4.7%), with cumulative funds at a mere 0.8%. The composition of financial assets showed that the majority were in bank deposits (78.5%), followed by risk management assets (18.0%), and investment assets (2.4%). Third, multivariate analysis results revealed that younger age, higher education level, and better financial factors were associated with a higher probability of having monthly savings. The results for financial assets were largely similar, with females showing a higher likelihood of asset possession compared to males. Fourth, the proportions of both bank savings in total savings and insurance generally had opposing effects. Fifth, age group had the greatest influence on the proportions of safety and insurance assets, followed by income group. Middle-aged households had lower proportions of safety assets but higher proportions of insurance assets compared to young households, while the opposite trend was observed for elderly households. Middle-income households had higher proportions of insurance assets compared to low-income households, whereas high-income households had higher proportions of investment assets. Lastly, cluster analysis categorized single-person households' financial portfolios into five groups: Group 1 (32.2%): "Old-Sustain" characterized by insufficient current income but economically stable retirement. Group 2 (29.4%): "Financially Active" engaging in various financial activities due to relatively high education and employment rates. Group 3 (28.0%): "Financially Inactive" classified as elderly groups with minimal financial activities. Group 4 (9.1%): "Risk Financial Structure" consisting of relatively young individuals focused on risk management assets but facing issues in financial asset management due to high-risk assets and financial loans. Group 5 (1.3%): "Stable-Insurance Oriented" with high financial assets and income concentrated in insurance for both savings and financial assets.

Employing behavioural portfolio theory for sustainable investment: Examining drawdown risks and ESG factors

ABSTRACT This study uses behavioural portfolio theory (BPT) within the Markowitz Portfolio Theory framework to enhance portfolio management by focusing on sustainability and risk mitigation during market downturns. It selects portfolios to hedge against market lows using Conditional Drawdown at Risk (CDaR) and Expected Regret of Drawdown (ERoD). These measures help choose securities that perform well during a market decline. This study applies drawdown-based risk metrics to assist institutional investors and fiduciaries in making informed investment and fund management decisions. By merging BPT with Markowitz’s mean–variance framework, selected investments are maintained above a safety threshold, contributing to the portfolio’s overall quality and sustainability. Additionally, by incorporating an Environmental, Social, and Governance (ESG) preference function, the findings suggest that BPT built portfolios meet traditional performance standards and align with socially responsible investment principles, thereby offering higher utility and alignment with investor values focused on sustainable investing.

An Entropic Analysis of Efficiency in the West Texas Intermediate Crude Oil Futures Market

For the last 50 years or so, the efficient market hypothesis (EMH) has been the central pillar of economic thought and the building block of portfolio theory. However, the validity of the EMH still remains controversial, and the methods of testing for market efficiency have been criticised. This study utilises entropy analysis combined with generalised autoregressive conditional heteroscedasticity (GARCH) regressions to provide extensive empirical evidence on informational efficiency. This study develops an innovative method for studying market efficiency by investigating the complexity of information saturated in the market. To this end, we have used daily West Texas Intermediate (WTI) crude oil futures contracts from June 1983 to February 2016, giving a total data set of 282,427 observations. The results of the Jensen–Shannon informational criteria indicate that the informational efficiency measure has never reached the maximum value of 1 which indicates weak-form efficiency. Our study has further found that the informational efficiency measure tends to decrease consistently during recessionary periods and to increase in subsequent periods. We have also found that the entropy measure tends to increase over time, supporting the adaptive market hypothesis over the EMH.

Quick Introduction into the General Framework of Portfolio Theory

This survey offers a succinct overview of the General Framework of Portfolio Theory (GFPT), consolidating Markowitz portfolio theory, the growth optimal portfolio theory, and the theory of risk measures. Central to this framework is the use of convex analysis and duality, reflecting the concavity of reward functions and the convexity of risk measures due to diversification effects. Furthermore, practical considerations, such as managing multiple risks in bank balance sheets, have expanded the theory to encompass vector risk analysis. The goal of this survey is to provide readers with a concise tour of the GFPT’s key concepts and practical applications without delving into excessive technicalities. Instead, it directs interested readers to the comprehensive monograph of Maier-Paape, Júdice, Platen, and Zhu (2023) for detailed proofs and further exploration.

A Study on the Risks of Real Estate Investment

This paper examines the risks associated with real estate investment, leveraging Modern Portfolio Theory (MPT) introduced by Harry Markowitz and later applied to real estate by Nigel Dubben and Sarah Sayce. MPT emphasizes balancing expected returns and risk through diversification, crucial in real estate due to its low correlation with other assets and its inflation-hedging properties. Despite global economic integration increasing systemic risks, real estate remains a key asset class for risk management. The literature review highlights traditional strategies focusing on diversifying by property type and geographic location. Studies show mixed results: some suggest property type diversification yields higher returns, while others find geographic diversification more effective for risk mitigation. Chinese market studies reveal that real estate investments can provide predictable returns and act as a hedge during economic downturns. Research on Beijing and Shanghai supports the effectiveness of geographic diversification within China. Applying MPT to real estate, the paper demonstrates through case studies how investment combinations can balance risk and returns. It discusses the Efficient Frontier, CAPM, and Arbitrage Pricing Theory to illustrate the relationship between risk and return in real estate portfolios. The analysis concludes that diversification strategies, though complex, are essential for optimizing performance and mitigating risks in real estate investments.

Portfolio theory in investment decision making: Evidence from NVIDIA and Costco

Portfolio theory in investment decision making: Evidence from NVIDIA and Costco

Contagion effect between fuel fossil energies and agricultural commodity markets and portfolio management implications

This study investigates the dynamic spillover effects between fossil fuels (Brent oil and natural gas) and major agricultural markets (maize, soybeans, and wheat) using a time-varying parameter vector autoregression (TVP-VAR) model. Additionally, we quantify the cumulative return of the investment portfolio, optimal weights, time-varying risk coverage, and hedging effectiveness of bivariate commodity portfolios using the Minimum Variance Portfolio (MVP), Minimum Correlation Portfolio (MCP), Minimum Connectedness Portfolio (MCoP) under bearish, tranquil, and bullish market conditions. The results show that maize and natural gas are the main net receivers of spillovers, whereas wheat and Brent oil are the main net transmitters of shocks to the network, respectively. Our findings of optimal weights in multivariate portfolio suggest more weights for agri-commodities against fossil fuels in all three modes of market. In addition, the optimal weights of bivariate portfolio analysis show that the most optimal portfolio which has the highest HE value is related to natural gas pairs with agri-commodities. Moreover, depending on the status of the market; in an average and bearish modes, the highest optimal weight is related to maize/natural gas. However, in the bullish market, the highest optimal weights are related to natural gas/Brent oil pair. Furthermore, the results of optimal bivariate hedge ratios show that natural gas/wheat (wheat/maize and vice versa) portfolio is the cheapest (the most expensive) investment strategy in all modes of market and based on MVP and MCoP approaches.