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We measure “good” and “bad” variance premia that capture risk compensations for the realized variation in positive and negative market returns, respectively. The two variance premium components jointly predict excess returns over the next one and two years with statistically significant positive (negative) coefficients on the good (bad) component. The R 2 s reach about 10% for aggregate equity and portfolio returns and 20% for corporate bond returns. To explain the new empirical evidence, we develop a model that highlights the differential impact of upside and downside risk on equity and variance risk premia. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2890 . This paper was accepted by Neng Wang, finance.

Purpose This study aims to examine the association between predictive accounting downside risk measures and changes in credit spreads. Building upon the earnings downside risk (EDR) measure developed in prior literature, this paper introduces cash flow downside risk (CFDR). Design/methodology/approach This study modifies an existing empirical framework (root lower partial moment) to calculate CFDR and applies it to a sample of firms between 2002 and 2013 for which credit default swap data are available. Findings After validating the measure, this study identifies a positive association between CFDR and changes in credit spreads. This paper further shows the association between CFDR and credit spread changes is stronger than that between EDR and credit spread changes. Financial stability moderates the relationship between CFDR and credit spreads. Originality/value This study proposes a novel measure of accounting downside risk, CFDR and demonstrates a negative association between this measure and future cash flow and a positive association between this measure and future credit spreads.

We add an independent unfair background risk to higher-order risk-taking models in the current literature and examine its interaction with the main risk under consideration. Parallel to the well-known concept of risk vulnerability, which is defined by Gollier and Pratt (Econometrica 64:1109–1123, 1996), an agent is said to have a type of higher-order risk vulnerability if adding an independent unfair background risk to wealth raises his level of this type of higher-order risk aversion. We derive necessary and sufficient conditions for all types of higher-order risk vulnerabilities and explain their behavioral implications. We find that as in the case of risk vulnerability, all familiar HARA utility functions have all types of higher-order risk vulnerabilities except for a type of third-order risk vulnerability corresponding to a downside risk aversion measure called the Schwarzian derivative.

This study evaluates the performance of U.S. data center Exchange-Traded Funds (ETFs) relative to major equity and technology benchmarks, using monthly returns from January 2000 through December 2024, with particular emphasis on the COVID-19 period and the subsequent post-vaccine era. Data center ETFs have not provided better risk-adjusted returns even though they are often advertised as access points to the digital economy. Digital infrastructure demand increased through the pandemic but did not improve the performance of these funds which stayed weak across both traditional and conditional multi-factor asset pricing models. These ETFs struggle with asset selection and market timing proficiency, which leads to relatively poor performance results during volatile market conditions. The downside risks linked to these funds tend to match or exceed the downside risks of broader indices like the S&P 1500 Information Technology Index. Although these investments are based on strong thematic narratives, they do not achieve returns that align with investor expectations.

In addition to risk aversion, decision-makers tend to be also downside risk averse. Besides the usual size for risk trade-off, this allows several other trade-offs to be considered. The decision to increase the level of self-protection generates five trade-offs each involving an unfavourable downside risk increase and an accompanying beneficial change. Five stochastic orders that correspond to these trade-offs are defined, characterised and used to prove comparative static theorems that provide information concerning the self-protection decision. The five stochastic orders are general in nature and can be applied in any decision model where downside risk aversion is assumed.

Downside risk increases have previously been characterized as changes preferred by all decision makers u(x) with u'\"(x) > 0. For risk averse decision makers, u'\"(x) > 0 also defines prudence. This paper finds that downside risk increases can also be characterized as changes preferred by all decision makers displaying decreasing absolute risk aversion (DARA) since those changes involve random variables that have equal means. Building on these findings, the paper proposes using \"more decreasingly absolute risk averse\" or \"more prudent\" as alternative definitions of increased downside risk aversion. These alternative definitions generate a transitive ordering, while the existing definition based on a transformation function with a positive third derivative does not. Other properties of the new definitions of increased downside risk aversion are also presented.

In this paper, we implement an integrated framework for constructing ESG-constrained, downside-risk-optimized equity portfolios in the European stock market. Extending traditional mean-variance approaches, we employ downside-oriented risk measures-conditional value at risk (CVaR) and semi-variance-to better capture investors’ asymmetric aversion to losses. ESG scores are introduced as binding constraints based on percentile thresholds, ensuring that portfolios comply with predefined sustainability standards. Semi-variance and CVaR objectives are formulated as convex programs to enable tractable optimization. Using data from Euro Stoxx 50 and Euronext 100 constituents, our empirical analysis reveals that: (i) integrating downside risk measures enhances tail-risk protection and may improve performance for loss-averse investors; but (ii) enforcing ESG constraints, particularly at stricter thresholds, leads to reduced diversification and a decline in risk-adjusted returns (e.g., Sharpe and Sortino ratios). These findings highlight the inherent trade-off between sustainability and financial efficiency, underscoring the importance of moderate ESG integration when balancing performance and ethical objectives.

The peer-to-peer (P2P) strategy as a new trading scheme has recently gained attention in local electricity markets. This is a practical framework to enhance the flexibility and reliability of energy hubs, specifically for industrial prosumers dealing with high energy costs. In this paper, a Norwegian industrial site with multi-energy hubs (MEHs) is considered, in which they are equipped with various energy sources, namely wind turbines (WT), photovoltaic (PV) systems, combined heat and power (CHP) units (convex and non-convex types), plug-in electric vehicles (EVs), and load-shifting flexibility. The objective is to evaluate the importance of P2P energy transaction with on-site flexibility resources for the industrial site. Regarding the substantial peak power charge in the case of grid power usage, this study analyzes the effects of P2P energy transaction under uncertain parameters. The uncertainties of electricity price, heat and power demands, and renewable generations (WT and PV) are challenges for industrial MEHs. Thus, a stochastically based optimization approach called downside risk constraint (DRC) is applied for risk assessment under the risk-averse and risk-neutral modes. According to the results, applying the DRC approach increased by 35% the operation cost (risk-averse mode) to achieve a zero-based risk level. However, the conservative behavior of the decision maker secures the system from financial losses despite a growth in the operation cost.

The field of international business is fundamentally concerned with the implications of managerial actions that affect multinational risk and performance outcomes. While portfolio diversification and real options theory are often used to describe the outcomes of multinational investment, existing work often confuses the actions and predictions proposed by these theories. This is concerning, as the two theories emphasize different causal mechanisms, managerial actions, and conceptions of risk and performance. Whereas portfolio theory argues that passive management affects symmetric outcomes, such as variance in returns by attaining a well-diversified portfolio, real options theory posits that managers actively shift subsidiary resources to affect asymmetric outcomes, such as upside potential or downside risk by monitoring and responding to environmental changes affecting the portfolio. This paper disentangles these two theories by focusing on unique predictions from real options theory – that geographic dispersion of MNE activities is associated with asymmetric outcomes, that this association is contingent on management being aware of real options logic, and that these effects are moderated by the degree of market uncertainty. Our findings confirm these predictions and suggest differences in the types of managerial strategies and actions required to effectively implement these distinct theories of the MNE.

Over the past decade, several studies have argued that customer satisfaction has high relevance for financial markets because it has a significant impact on stock returns. However, little attention has been given to understanding the impact of customer satisfaction on the risk of stock returns. The finance literature suggests that investors that judge performance only in terms of returns place more resources than warranted in risky opportunities, forgo profitable opportunities, and apply misguided performance evaluations. Accordingly, this study develops, tests, and finds empirical support for the hypotheses that positive changes (i.e., improvement) in customer satisfaction result in negative changes (i.e., reduction) in overall and downside systematic and idiosyncratic risk. Using a panel data sample of publicly traded U.S. firms and satisfaction data from the American Customer Satisfaction Index, the study demonstrates that investments in customer satisfaction insulate a firm's stock returns from market movements (overall and downside systematic risk) and lower the volatility of its stock returns (overall and downside idiosyncratic risk). The results are robust to alternative measures of risk, model specifications, and concerns related to sample composition criteria raised in some recent studies. Therefore, the results indicate that customer satisfaction is a metric that provides valuable information to financial markets. The robust impact of customer satisfaction on stock returns risk indicates that it would be useful for firms to disclose their customer satisfaction scores in their annual report to shareholders.