Level Of Risk Aversion Research Articles

Small stakes risk aversion in the laboratory: A reconsideration

Evidence of risk aversion in laboratory settings over small stakes leads to a priori implausible levels of risk aversion over large stakes under certain assumptions. One core assumption in statements of this calibration puzzle is that small-stakes risk aversion is observed over all levels of wealth, or over a “sufficiently large” range of wealth. Although this assumption is viewed as self-evident from the vast experimental literature showing risk aversion over laboratory stakes, it actually requires that lab wealth be varied for a given subject as one evaluates the risk attitudes of the subject. We consider evidence from a simple design that tests this assumption, and find that the assumption is strikingly rejected for a large sample of subjects from a population of college students. We conclude that the implausible predictions that flow from these assumptions do not apply to one specialized population widely used to study economic behavior in laboratory experiments.

Modeling Gas Markets with Endogenous Long-Term Contracts

Since its initial development, long-term contracts have been associated with the gas industry in all regions of the world. This was also the case in Europe where natural gas trade was, for a long time, dominated by bilateral long-term agreements between producers and midstreamers. These contracts fixed a minimum volume to be exchanged (take or pay) and indexed the gas price using a price formula that usually referred to oil product prices. These arrangements allowed market risk sharing between the producer (who takes the price risk) and the midstreamer (who takes the volume risk). They also offered risk hedging since oil is considered as a trusted commodity by investors. The fall of the European natural gas demand, combined with the increase of the oil price, favored the emergence of a gas volume bubble that caused significant losses for most of the European midstreamers bound by long-term agreements. As a result, the downstream part of the industry brought forward the idea of indexing contracts on gas spot prices. In this paper, we present an equilibrium model that endogenously captures the contracting behavior of both producer and midstreamer, who strive to hedge their profit-related risk. Players can choose between gas forward and oil-indexed contracts. Using the model, we show that (i) contracting can reduce the trade risk for both producer and midstreamer; (ii) oil-indexed contracts should be signed only when oil and gas spot prices are well correlated, otherwise, these contracts hold less interest for risk mitigation; (iii) contracts are best suited when the upstream cost structure is mainly driven by capital costs; and (iv) a high level of risk aversion from the midstreamer might deprive upstream investments and downstream consumer surplus. The online appendix is available at https://doi.org/10.1287/opre.2017.1599 .

A Robust Reliable Forward-reverse Supply Chain Network Design Model under Parameter and Disruption Uncertainties

Social responsibility is a key factor that could result in success and achieving great benefits for supply chains. Responsiveness and reliability are important social responsibility measures for consumers and all stakeholders that strategists and company managers should be concerned about them in long-term planning horizon. Although, presence of uncertainties as an intrinsic part of supply chains could adversely affect the best set plans by field experts. Accordingly, uncertainty of parameters and uncertainties caused by disruptions should be regarded in planning process of networks to prevent unpredictable negative consequences of such uncertainties for all echelons of supply chain. Based on enumerated matters, the aim of this paper is to design a reliable multi-echelon closed loop supply chain network model that maximizes social responsibility while minimizing fixed establishing and variable processing costs of network design. To cope with uncertainty of parameters, stochastic programming is applied and an effective reliable modelling method is employed to appropriately control unpleasant economic impacts of disruptions. Notably, an efficient robust programming method is applied to give the decision makers the capability to control level of risk-averseness of decisions while modelling uncertain parameters. Finally, the proposed model is solved and its outputs are analyzed on the basis of generated test problems which shows correct performance and applicability of extended model in real world problems.

Risk Aversion and Implicit Bias

This paper studies risk aversion as an influential construct in implicit bias testing, and one that has been previously overlooked in the literature. In it, I adapt a model of internal validity and apply it to the impact that risk preferences have on implicit bias. I then implement a laboratory experiment to gauge implicit bias as measured by the implicit association test (IAT). I structurally estimate subjects’ attitudes towards risk. In testing said model, I find that higher levels of risk aversion are associated with stronger implicit bias scores. This result is robust to a variety of econometric specifications and thus lends support to previous critiques of IAT validity.

Risk Perceptions in Diabetic Patients Who Have Experienced Adverse Events: Implications for Patient Involvement in Regulatory Decisions.

BackgroundIncreasingly, patients are expected to influence decisions previously reserved for regulatory agencies, pharmaceutical companies, and healthcare professionals. Individual patients have previously represented their patient population when rare, serious adverse events (AEs) were weighed as part of a benefit-risk assessment. However, the degree of heterogeneity of the patient population is critical for how accurately they can be represented by individuals.ObjectivesThis study aims to explore patients’ risk perception of rare, serious adverse effects of medicines with regard to blood glucose-lowering antidiabetics used by the individual patient.MethodsSemi-structured interviews were conducted with 18 patients with diabetes with self-perceived serious, but not necessarily rare, AEs (e.g. stroke or valve or bypass surgery). The interviews explored the patients’ history of disease, perceptions of the terms rare and serious, and overall levels of risk aversion. A thematic analysis of the interviews, including a consensus discussion, was carried out.ResultsInterestingly, respondents rarely made a clear distinction between medicines-induced AEs and complications related to disease progression. Concerns regarding AEs were apparently diverse but were systematically related to the personal experiences of the respondents. Respondents routinely ignored information about possible rare, serious AEs, unless it could be related to personal experience. In the absence of experience, concerns were focused on common and less serious AEs, thus disregarding rare and more serious events.ConclusionThe study suggests that experience of AEs, related to either medicines or disease, constitutes an important factor of patient risk perception. We therefore propose that serious adverse experiences should be added to the traditional panel of socioeconomic factors that are accounted for when patients are invited to give input on regulatory decisions.

Two-Stage Coordinated Operational Strategy for Distributed Energy Resources Considering Wind Power Curtailment Penalty Cost

The concept of virtual power plant (VPP) has been proposed to facilitate the integration of distributed renewable energy. VPP behaves similar to a single entity that aggregates a collection of distributed energy resources (DERs) such as distributed generators, storage devices, flexible loads, etc., so that the aggregated power outputs can be flexibly dispatched and traded in electricity markets. This paper presents an optimal scheduling model for VPP participating in day-ahead (DA) and real-time (RT) markets. In the DA market, VPP aims to maximize the expected profit and reduce the risk in relation to uncertainties. The risk is measured by a risk factor based on the mean-variance Markowitz theory. In the RT market, VPP aims to minimize the imbalance cost and wind power curtailment by adjusting the scheduling of DERs in its portfolio. In case studies, the benefits (e.g., surplus profit and reduced wind power curtailment) of aggregated VPP operation are assessed. Moreover, we have investigated how these benefits are affected by different risk-aversion levels and uncertainty levels. According to the simulation results, the aggregated VPP scheduling approach can effectively help the integration of wind power, mitigate the impact of uncertainties, and reduce the cost of risk-aversion.

An inexact two-stage stochastic risk-aversion model for integrated energy system management in Beijing-Tianjin-Hebei, China

An inexact two-stage stochastic risk-aversion model was developed in this study for supporting regional energy system planning and management. It can tackle uncertainties described in terms of probability distributions and permits the in-depth analysis of various policy scenarios when the promised policy targets are violated. Moreover, it can help local decision-makers evaluate trade-offs between energy system economy and stability associated with different robust criteria (risk-aversion levels). An actual case study in the Beijing-Tianjin-Hebei (BTH) region, China, was provided for demonstrating the applicability of the developed model. The results indicated that electricity generated by coal-burning (coal-fired power and coal-fired cogeneration) and gas-fired heating would be the main power forms for power and heat supply to get the maximum security. Furthermore, some policy implications can be concluded as follows: (a) more attention should be focused on increasing the local power generation capacity in the BTH region rather than importing electricity from other regions; (b) the introduction of risk aversion into the optimization model is conducive to the development of solar power, biomass power, and gas-fired cogeneration; and (c) renewable energy (e.g., biomass energy and geothermal energy) development in the BTH region still has a long way to go, because it is constrained by resource endowment and geographical location. Generally, the proposed model not only can help decision-makers identify the desired energy system management policies under risk considerations, but also could be viewed as a prime example for energy system planning and management at different regional levels (e.g., city, province, and multiprovince) and used as a reference for energy structure adjustment in other metropolitan groups such as the Yangtze River Delta and Pearl River Delta urban agglomerations.

Managerial Risk Aversion and Accounting Conservatism

This paper investigates the delegation of financial reporting policy to a manager as a shareholder commitment device to achieve an ex-ante preferred level of conservatism. It especially explores how managerial traits – specifically the level of risk aversion and overconfidence – facilitate efficient implementation of the preferred level of conservatism. The potential benefit of a conservative reporting policy has been demonstrated in the literature, but if firms have some freedom to set the level of conservatism and it is not perfectly observable, the enforcement of a commitment to conservative reporting could be a concern (firms may claim to be conservative while in fact being aggressive). Therefore, the delegation of the reporting policy and the design of an appropriate incentive scheme could be a possible commitment device. We present a model in which to obtain better funding terms, a firm has an ex-ante preference for a given level of conservatism. Hiring a more risk-averse manager lowers the cost of implementing a conservative reporting policy, but increases the agency cost linked to the productive effort. We show that, for a plausible range of parameter values, the optimal level of managerial risk aversion which minimizes the overall agency cost is increasing with respect to the level of conservatism the firm wants to induce. Similar results hold for the degree of overconfidence – in the opposite direction: the optimal level of overconfidence is decreasing with respect to the desired level of conservatism. These results suggest an alternative explanation for recent empirical evidence linking CEO and CFO characteristics to the level of conservatism: firms deliberately choose managers with specific personality traits for efficient implementation of shareholders’ ex-ante preferred level of conservatism.

Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

Abstract. A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost–loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

Asset pricing puzzles in an OLG economy with generalized preference

AbstractWe seek to explain a number of asset pricing anomalies – the equity premium puzzle, the risk‐free rate puzzle, and portfolio allocation puzzle – in a parsimonious overlapping generations (OLG) model with two key features: borrowing constraint and Epstein–Zin–Weil (1989) preference. The model goes a long way towards the resolution of these puzzles, and is able to simultaneously match asset pricing moments and individual portfolio decisions using reasonable values of parameters governing behavior. We find that the main driver of savings behavior, equity returns, and asset allocation is the relative difference between the two parameters: the level of relative risk aversion and the inverse of the elasticity of substitution.

Macroeconomic Uncertainty and Corporate Bond Returns

We examine the role of macroeconomic uncertainty in the cross-section of corporate bonds and find a significant uncertainty premium for both investment-grade (0.40% per month) and non-investment-grade (0.81% per month) bonds. The economic uncertainty premium declines as we progressively remove downgraded bonds, indicating that the premium represents an increase in required returns for bonds with higher credit and macroeconomic risk. The economic uncertainty premia vary across equities and bonds in a manner consistent with heterogeneous risk aversion levels of dominant players in equities (retail investors) versus bonds (institutional investors).

A normalized value for information purchases

Consider agents who are heterogeneous in their preferences and wealth levels. These agents may acquire information prior to choosing an investment that has a property of no-arbitrage, and each piece of information bears a corresponding cost. We associate a numeric index to each information purchase (information-cost pair). This index describes the normalized value of the information purchase: it is the risk-aversion level of the unique CARA agent who is indifferent between accepting and rejecting the purchase, and it is characterized by a “duality” principle that states that agents with a stronger preference for information should engage more often in information purchases. No agent more risk-averse than the index finds it profitable to acquire the information, whereas all agents less risk-averse than the index do. Given an empirically measured range of degrees of risk aversion in a competitive economy with no-arbitrage investments, our model therefore comes close to describing an inverse demand for information, by predicting what pieces of information are acquired by agents and which ones are not. Among several desirable properties, the normalized-value formula induces a complete ranking of information structures that extends Blackwell's classic ordering.

Yield curve forecast combinations based on bond portfolio performance

AbstractWe propose an economically motivated forecast combination strategy in which model weights are related to portfolio returns obtained by a given forecast model. An empirical application based on an optimal mean–variance bond portfolio problem is used to highlight the advantages of the proposed approach with respect to combination methods based on statistical measures of forecast accuracy. We compute average net excess returns, standard deviation, and the Sharpe ratio of bond portfolios obtained with nine alternative yield curve specifications, as well as with 12 different forecast combination strategies. Return‐based forecast combination schemes clearly outperformed approaches based on statistical measures of forecast accuracy in terms of economic criteria. Moreover, return‐based approaches that dynamically select only the model with highest weight each period and discard all other models delivered even better results, evidencing not only the advantages of trimming forecast combinations but also the ability of the proposed approach to detect best‐performing models. To analyze the robustness of our results, different levels of risk aversion and a different dataset are considered.

Pertinence of reactive, active, and robust adaptation strategies in forest management under climate change

Pertinence of alternative adaptation strategies to business as usual, namely reactive, active, and robust adaptation strategies, can be evaluated by incorporating the expected costs and benefits of adaptation, climate change uncertainty, and the risk attitudes of decision-makers. Forest management is used to coping with risky and uncertain projections and estimates. However, climate change adds a major challenge and necessitates adaptation in many ways. This paper highlights the dependency of the decisions on adaptation strategies to four aspects of forest management: (i) the costs of mitigating undesirable climate change impacts on forests, (ii) the value of ecosystem goods and services to be sustained, (iii) uncertainties about future climate trajectories, and (iv) the attitude of decision-makers towards risk (risk aversion level). We develop a framework to evaluate the pertinence of reactive, active, and robust adaptation strategies in forest management in response to climate change. Business as usual may still be retained if the value of the forest and cost of climate impacts are low. Otherwise, it is crucial to react and facilitate the resilience of affected forest resources or actively adapt in advance and improve forest resistance. Adaptation should be robust under any future climate conditions, if the value of the ecosystem, the impacts from climatic changes, and the uncertainty about climate scenarios are very high. The decision framework for adaptation should take into account multiple aspects of forest management under climate change towards an active and robust strategy.

Asymmetric volatility and conditional expected returns

PurposeThe risk-return relationship is one of the most widely investigated topics in finance, yet this relationship remains one of the most controversial topics. The purpose of this paper is to investigate the asymmetric volatility and the risk-return tradeoff at the sector level in the emerging stock market of Jordan.Design/methodology/approachData consist of daily prices for 22 sub-sectors spanning from August 1, 2006, to September 30, 2015, covering the periods of pre, during, and after the global financial crisis. The EGARCH-M model is used to document the patterns of asymmetric volatility of sub-sector returns and the risk-return tradeoff during the non-overlapping three sub-sample periods.FindingsThe major findings of this study are as follows. In the pre-crisis period, the results suggest some evidence of a positive relationship between risk and return. The results also reveal that good news has more effect than bad news during the same period. In the crisis period, there is a negative but insignificant risk-return relationship and negative shocks have more impact than positive ones. In the post-crisis period, the authors find positive but insignificant risk-return tradeoff with weak evidence of volatility asymmetry.Practical implicationsThe results have major implications for investors willing to engage their investment decisions in the Amman Stock Exchange (ASE) and for policymakers who seek to attract and retain regional and international investors. Since the empirical investigation is conducted at the sector level, the study may aid investors to target specific sub-sectors with positive and significant risk-return tradeoff. In addition, investors need to monitor the asymmetric patterns which make the level of risk-aversion more susceptible to coming news. For policymakers, the latest infrastructure reforms are crucial to achieving the potential for growth but the ASE market authority needs to undergo further reforms and provide various promotional incentives.Originality/valueAlthough there are numerous studies on asymmetric volatility and risk-return tradeoff, there is a lack of parallel studies at the sector level for both developed and emerging stock markets. Such assessment at the sector level is crucial for international investors after their choice of countries or markets for better choice of portfolio diversification and allocation of financial resources.

Competition, risk and learning in electricity markets: An agent-based simulation study

This paper studies the effects of learning and risk aversion on generation company (GenCo) bidding behavior in an oligopolistic electricity market. To this end, a flexible agent-based simulation model is developed in which GenCo agents bid prices in each period. Taking transmission grid constraints into account, the ISO solves a DC-OPF problem to determine locational prices and dispatch quantities. Our simulations show how, due to competition and learning, the change in the risk aversion level of even one GenCo can have a significant impact on all GenCo bids and profits. In particular, some level of risk aversion is observed to be beneficial to GenCos, whereas excessive risk aversion degrades profits by causing intense price competition. Our comprehensive study on the effects of Q-learning parameters finds the level of exploration to have a large impact on the outcome. The results of this paper can help GenCos develop bidding strategies that consider their rivals’ as well as their own learning behavior and risk aversion levels. Likewise, the results can help regulators in designing market rules that take realistic GenCo behavior into account.

Portfolio choice with high frequency data: CRRA preferences and the liquidity effect

This paper suggests a new approach for portfolio choice. In this framework, the investor, with CRRA preferences, has two objectives: the maximization of the expected utility and the minimization of the portfolio expected illiquidity. The CRRA utility is measured using the portfolio realized volatility, realized skewness and realized kurtosis, while the portfolio illiquidity is measured using the well-known Amihud illiquidity ratio. Therefore, the investor is able to make her choices directly in the expected utility/liquidity (EU/L) bi-dimensional space. We conduct an empirical analysis in a set of fourteen stocks of the CAC 40 stock market index, using high frequency data for the time span from January 1999 to December 2005 (seven years). The robustness of the proposed model is checked according to the out-of-sample performance of different EU/L portfolios relative to the minimum variance and equally weighted portfolios. For different risk aversion levels, the EU/L portfolios are quite competitive and in several cases consistently outperform those benchmarks, in terms of utility, liquidity and certainty equivalent.

Robust bi-level optimization for green opportunistic supply chain network design problem against uncertainty and environmental risk

The main objective of this research is to introduce the concept of Green Opportunistic Supply Chain (GrOSC) and to design it in a lean and agile manufacturing setting under uncertain and risky environment. The model considers the uncertainties of the market-related information, i.e. the demand and transportation and shortage costs, under Vendor Managed Inventory (VMI) strategy. Addressing the retailer’s risk aversion level through Conditional Value at Risk (CVaR) to deal with these uncertainties leads to a bi-level programming problem. The Karush-Kuhn-Tucker (KKT) conditions are adopted to transform the model into a single-level mixed integer linear programming problem. Since, the realization of the uncertain parameters is the only information available, a data-driven approach is employed to avoid distributional assumptions. The effectiveness of the model is finally demonstrated through a numerical example.

Audit Partners Gender, Auditor Quality and Clients Value Relevance

Several corporate scandals around the world have aggravated the investors’ need for reliable and relevant accounting information. In fact, the study is inspired by prior research which suggests women audit partner or auditor possess a higher level of preparation, risk aversion and ethical behaviour in audit process. Thus, we investigated the possible effect of women audit partner on the client value relevance of accounting information on 2,478 firm-year observations from year 2012 to 2014 for Malaysian listed firms. This article uses time series cross-sectional ordinary least squares (OLS) regressions upon a large sample of the Malaysian listed firms. Basically, the regression results indicate that the signing women audit partner from Big-4 audit firms improves the reliability and value relevance of earnings. Furthermore, our additional analysis shows that firms that engaged the women audit partner from Big-4 audit firms report high relevant equity book values. This study provides a valuable contribution on the positive effect of signing women audit partner from Big-4 audit firms on client value relevance of accounting information to researchers, regulators, investors and all other interested parties in financial information.

To Stay or Go? Consumer Bank Switching Behaviour after Government Interventions

We analyse whether and how individual savings and current accounts holders respond to government interventions at banks. We are the first to employ a difference-in-difference analysis, distinguish between a nationalisation and a capital injection, and separate between the two banking products. We find that the aggregate switching behaviour of consumers at intervened banks is similar before and after the troubles and intervention. This holds for both type of interventions, both type of products, and for switching from and to the intervened bank. However, we show heterogeneity in consumer responses to government interventions, depending on the type of intervention and banking product. For example, compared to consumers who trust the government, consumers with no or little trust are more likely to switch away from a bank after a nationalisation, relative to customers of the control bank. This holds for switching with the savings and current account. This highlights that trust in the government is an important prerequisite for a successful nationalisation. Second, responses depend on consumers’ level of risk aversion. Risk averse current account holders at a nationalised bank are more likely to switch away than customers of the control bank. This result indicates that interventions can make consumers more aware of the troubles the intervened bank faces, and result in an outflow of consumers if a large share is risk averse.