Degree Of Risk Aversion Research Articles

Diversification, Industry Concentration, and Bank Margins: Empirical Evidence from an Emerging South Asian Economy

The study aims to empirically examine the determinants of bank margins from Pakistan, an emerging South Asian economy. To elucidate the importance of the Pakistani banking sector, secondary data has been used, which was extracted from the annual accounts of twenty-four Pakistani scheduled commercial banks (20 conventional, four full-fledged Islamic) over a sample period of 2006 to 2017. The factors identified in the dealership model and the subsequent empirical developments in the dealership model categorized as bank-specific, diversification, regulatory, and industry concentration are analyzed by applying the most-common linear dynamic panel-data estimator, the Generalized Method of Moments (GMM) estimator, developed by Arellano and Bond (1991). The findings reveal that, among the bank-specific variables, funding cost, credit risk, managerial efficiency, market share, and operating cost are significant predictors of bank margins. For diversification variables employed in the study, both variables including net non-interest income and asset diversity are as well significant predictors of bank margins. It is also found that the market concentration variable proxied by the Herfindahl-Hirschman Index (HHI) is significantly predicting bank margins. Subsequently, one of the regulatory variables, the opportunity cost of holding reserves, and one bank-specific variable, the degree of risk aversion, are insignificant in the model.

ECB'S non‐standard monetary policy and asset price volatility: Evidence from EU‐6 economies

AbstractIn this paper, we provide evidence that the effects of the different waves of asset purchase programmes implemented by the ECB from 2009 onwards have spilled over into a group of six Central and Eastern European economies belonging to the EU but not to the euro area, contributing to shield their financial markets from the negative shocks that hit international investors' degree of risk aversion in recent years. By means of a Dynamic Conditional Correlation Multivariate Generalized Autoregressive Conditional Heteroskedasticity Model, and resorting to three different proxies to describe the functioning, and measure the impact, of the ECB's programmes of asset purchase, we show that such non‐standard monetary measures have had a marked role in dampening volatility spikes in EU‐6 financial markets, likely reflecting the working of a “risk taking” and a “liquidity” channel of transmission. Results are in general robust to an extensive series of tests, including changes in the estimation methodology.

Risk-taking and fairness among cocaine-dependent patients in dual diagnoses: Schizophrenia and Anti-Social Personality Disorder

This study reports experimental results from a clinical sample of patients with a cocaine-related disorder and dual diagnosis: Schizophrenia and Anti-Social Personality Disorder. Both types of patients as well as a non-clinical group of students performed two incentivized decision-making tasks. In the first part of the experiment, they performed a lottery-choice task in order to elicit their degree of risk aversion. In the second part, they decided in two modified dictator games aimed at eliciting their aversion to advantageous and disadvantageous inequality. It is found that the Anti-Social Personality Disorder group exhibits no significant differences from the non-clinical sample in either task. However, compared with the students’ sample, subjects from the group with schizophrenia show more risk aversion and exhibit more aversion towards disadvantageous inequality.

Insider trading with different risk attitudes

This paper examines the impact of different risk attitudes on the financial decisions of two insiders trading in the stock market. We consider a static version of the Kyle (Econometrica 53:1315–1335, 1985) model with two insiders. Insider 1 is risk neutral while insider 2 is risk averse with negative exponential utility. First, we analytically prove the existence of a unique linear equilibrium. Second, we carry out a comparative static analysis with respect to the duopoly case of risk-neutral insiders (Tighe in Three essays on insider trading. Unpublished Ph.D dissertation, University of Illinois at Champaign-Urbana, 1989) and with respect to the duopoly case of risk-averse insiders (Holden and Subrahmanyam in Econ Lett 44:181–190, 1994) models. Our findings reveal that the market depth and the information revelation are higher in Tighe (1989) than in our model. However, compared to Holden and Subrahmanyam (1994), we find that the market depth depends crucially on the degree of risk aversion. Finally, we show that regardless of the degree of risk aversion, the stock price reveals more information in our model than the stock price in Holden and Subrahmanyam (1994).

Insider Trading With Different Risk Attitudes

This paper examines the impact of different risk attitudes on the financial decisions of two insiders trading in the stock market. We consider a static version of the Kyle (1985) model with two insiders. Insider 1 is risk neutral while insider 2 is risk averse with negative exponential utility. First, we analytically prove the existence of a unique linear equilibrium. Second, we carry out a comparative static analysis with respect to the duopoly case of risk-neutral insiders (Tighe (1989)) and with respect to the duopoly case of risk-averse insiders (Holden and Subrahmanyam (1994)) models. Our findings reveal that the market depth and the information revelation are higher in Tighe (1989) than in our model. However, compared to Holden and Subrahmanyam (1994), we find that the market depth depends crucially on the degree of risk aversion. Finally, we show that regardless of the degree of risk aversion, the stock price reveals more information in our model than the stock price in Holden and Subrahmanyam (1994).

Time-varying risk aversion and the profitability of momentum trades

We show that time-varying risk aversion serves as a significant predictor of stock market momentum in the U.S. and globally. Risk aversion is found to be a robust predictor of momentum returns even after controlling for various well established stock market predictors and absorbs the predictive power of market volatility. The findings imply that momentum strategies can be enhanced by conditioning trades on the degree of risk aversion in the marketplace.

Service facilities with risk‐averse customers: a simulation approach

AbstractIn this study, a one‐dimensional cellular automata model is used to represent a self‐organized queueing system with local interaction between captive and boundedly rational customers who repeatedly choose a facility for service. While previous work has focused on decision rules based on adaptive expectations, the present work expands this analysis by explicitly incorporating customers’ attitude toward risk to study the impact of risk aversion on the collective behavior and the average system sojourn time. The customers’ decision process is modeled using adaptive expectations and incorporating the uncertainty involved in these expectations. Customers update their expectations based on their own experience and that of their neighbors. Simulation analysis is used to compare the aggregated behavior for different degrees of customer risk aversion. Risk‐neutral customers base their decisions only on their expected sojourn time, while risk‐averse customers account for uncertainty by estimating an upper bound of the sojourn times. The results indicate that the more risk‐averse the customers, the longer the transient period, and the more slowly the system converges to an almost stable average sojourn time. Systems where customers have an intermediate level of risk aversion achieve the worst average sojourn times.

Further Reflections on Prospect Theory

A menu of paired lottery choices is structured so that the crossover point to the high-risk lottery can be used to infer the degree of risk aversion or preference. When payoffs are hypothetical and gains are transformed into losses by reflecting them around zero, more than half of the subjects exhibit a effect (risk aversion for gains and risk seeking for losses). With cash payoffs, however, this pattern is not observed; many subjects exhibit risk aversion for both gains and losses, and the frequency of reflection (about ten percent) is not much greater than the frequency of reverse reflection (risk seeking for gains and risk aversion for losses). Risk aversion is, however, less common in the loss domain.

Quality competition and coordination in a VMI supply chain with two risk-averse manufacturers

<p style='text-indent:20px;'>Quality competition and risk aversion have become more and more common in today's many industries, making it a challenge to supply chain management and coordination. This paper considers a vendor-managed inventory (VMI) supply chain comprising two risk-averse manufacturers who sell their competing products through a common retailer. Market demand shared by each manufacturer is dependent on the quality level of its own product as well as on the competitor's product quality. The Conditional Value-at-Risk (CVaR) criterion is employed to formulate the risk aversion of manufacturers. This study first develops basic models without coordination mechanism and analyzes the effect of the quality sensitivity, competition intensity, risk aversion degree and cost coefficient of quality improvement on equilibrium decisions and supply chain efficiency. Further, a combined contract composed of option and cost-sharing is proposed to investigate the supply chain coordination issue. The results reveal that the combined contract can coordinate the supply chain and achieve a win-win outcome only when the manufacturers are low in risk aversion, and the system-wide profit of the supply chain can be allocated arbitrarily only by the option price. Also, this research examines the effect of the quality sensitivity, competition intensity, risk aversion degree and cost coefficient of quality improvement on the feasible region of option price.

Measuring Interest Rate Risk Considering Key Factors Affecting the Net Interest Margin (NIM) Ratio of Commercial Banks in Bangladesh

This paper attempts to reveal how the commercial banks operating in Bangladesh have measured interest rate risk using Interest sensitivity analysis along with considering the impact of key factors affecting the profitability measured with Net interest margin of banks under Bank specific as well as macro-economic environment. Interest sensitivity (IS) GAP analysis has been deployed to measure the degree of interest rate risk followed by a panel data regression model considering a comparative analysis among fixed effect within group, random effect GLS and Pooled OLS method adopted to measure the causation between Net interest margin and Bank specific along with Macroeconomic factor to accomplish the objective of this paper. In IS GAP along with relative IS GAP analysis, two banks are found to be liability sensitive posing a risk of reducing the net interest margin (NIM) if interest rate has been increased and rest of the banks are found to be asset sensitive again postulating risk of reducing the NIM if market rate interest has been decreased considering the ten years’ data regarding rate sensitive assets (RSA) and rate sensitive liabilities (RSL) of four commercial banks selected using convenience sampling approach. Moreover, Panel Data regression model depicts how several key factors such as degree of risk aversion, credit risk and quality of management, Average operating cost, size of banks, implicit interest payments may significantly affect this NIM ratio measuring the profitability of banks in Bangladesh followed by several diagnostic tests such as model specification test using hausman & LM test, multicollinearity test, heteroscadisticy test and unit root test conducted to check the validity of models. Keywords: IS GAP, NIM ratio, Relative IS GAP, Fixed effect, Random effect, OLS method. DOI: 10.7176/EJBM/12-15-08 Publication date: May 31 st 2020

Optimal hedging under biased energy futures markets

Optimal futures hedging positions for those agents trying to maximize their expected utility will depend on their view about the evolution of the market and on how risk adverse they are. The most risk adverse agents will probably decide to full-cover their positions. But when a futures bias exists, hedgers with moderate or low degree of risk aversion can alter their strategy depending on the expected gains in futures markets. In our application to the UK natural gas market, we find a statistically significant time-varying negative futures bias that can be forecasted with confidence. As a result of this bias, most effective and best performing hedging strategies for moderate risk-averse agents are those involving short (long) hedging in winter (summer) with a hedging ratio above (below) the minimum variance hedge ratio. These findings are of great interest to practitioners in the UK natural gas markets and the methodology can be extrapolated to other energy markets.

A Dynamic Conditional Approach to Portfolio Weights Forecasting

We build the time series of optimal realized portfolio weights from high-frequency data and we suggest a novel Dynamic Conditional Weights (DCW) model for their dynamics. DCW is benchmarked against popular model-based and model-free specifications in terms of weights forecasts and portfolio allocations. Next to portfolio variance, certainty equivalent, and turnover, we introduce the break-even transaction costs as an additional measure that identifies the range of transaction costs for which one allocation is preferred to another. By comparing minimum-variance portfolios built on the components of the Dow Jones 30 Index, the proposed DCW overall attains the best allocations with respect to the measures considered, for any degree of risk-aversion, transaction costs, and exposure.

Analysis of Enterprise Sustainable Crowdsourcing Incentive Mechanism Based on Principal-Agent Model

The utilization of crowdsourcing to acquire distant knowledge is increasing. In the new product development process, sustainable crowdsourcing is an effective way to exploit both external and internal resources to boost enterprise innovation quality and the efficiency of the competitive edge of macro tasks in a relatively long cycle. The challenge of sustainable crowdsourcing is how to design a proper incentive mechanism to achieve the maximum initiator profit and, at the same time, satisfy the solver’s motivation so that they can continuously participate in the innovation process. In two situations, including a single motivation and multiple motivations of the solver, this paper analyzed the impact of a few factors on the initiator’s profit and the incentive coefficient for the solver based on the Principal–Agent Model. From the model and simulation results, the solver’s incentive coefficient is positively correlated to the solver’s work quality and negatively correlated to the uncertainty of the enterprise operation, the solver’s Effort Cost, the solver’s degree of risk aversion, etc. If the initiator is more sensitive to the benefits of the solver’s intrinsic motivation, the monetary incentive will be higher. The research results provide a theoretical basis to quantify the initiator’s expected profit and design a proper incentive plan for the solver. Finally, the conclusions offer practical guidance for enterprise to execute incentive plans for sustainable crowdsourcing from the perspective of the solver’s motivation.

Optimal Operation Strategies under a Carbon Cap-and-Trade Mechanism: A Capital-Constrained Supply Chain Incorporating Risk Aversion

Many small and medium enterprises (SMEs) with capital constraints often have no access or find it costly to obtain a loan from a bank; the retailer tends to borrow money from other enterprises in the supply chain by trade credit financing. We consider an emission-dependent supply chain with one emission-dependent manufacturer and one capital-constrained retailer in need of financing to explore the optimal operational and environmental strategies of a low-carbon supply chain under trade credit financing. We use a Stackelberg game model to depict the low-carbon supply chain. We analyse the optimal carbon-emission reduction effort, wholesale price, and order quantity in the equilibrium state. The impacts of key parameters, such as the retailer’s internal working capital, the manufacturer’s risk-aversion degree, and the carbon-trading price on the supply chain operation, are analysed. The results show that the retailer’s capital constraint causes the carbon-emission reduction effort, wholesale price, and order quantity to improve synchronously. The supply chain achieves a win-win outcome for both the manufacturer and the retailer when the capital-constrained retailer is funded via trade credit from the manufacturer. The in-depth development of financing is beneficial to the manufacturer but is a disadvantage for the retailer. When the initial carbon-emission quota is low, the manufacturer benefits from a relatively lower carbon-trading price. Otherwise, a higher carbon-trading price is better for the manufacturer. The “carbon-trading price trap” ensures that the retailer’s profit is minimal. We further investigate the scenario in which the manufacturer is risk averse and find that the retailer will purchase fewer products and that the manufacturer will gain less profit to decrease the carbon-emission reduction effort. The manufacturer’s risk aversion is unfavourable to both the economic and environmental outcomes of the whole supply chain. This research provides strategic support for a low-carbon supply chain to carry out operational decisions in the context of enterprise capital constraint. To examine the theoretical results, the data used in the existing literature are further used to simulate the corresponding conclusions. Our research enriches the existing supply chain finance literature and provides decision support for the supply chain core enterprise.

Risk aversion and the value of diagnostic tests

Diagnostic tests allow better informed medical decisions when there is uncertainty about a patient’s health status and, therefore, about the desirability to undertake treatment. This paper studies the relation between the expected value of diagnostic information and a patient's risk aversion. We show that the ex ante value of diagnostic information increases with risk aversion for diseases with low prevalence, but decreases with risk aversion for diseases with high prevalence. On the other hand, the ex post value of diagnostic information always increases with the patient's degree of risk aversion.

Risk investment decisions within the deterministic equivalent income model

Purpose The purpose of this paper is to establish a deterministic equivalent income model (DEIM) based on the risk cost (RC) and risk aversion of investors. The model fully considers both subjective and objective factors that affect risk investment and reasonably evaluates risk investment schemes to choose the correct investment scheme and gain greater investment returns. Design/methodology/approach The utility function is used to measure the extent to which an investor is satisfied by investment returns in various scenarios. Risk aversion expresses subjective attitude of investors to risk. RC represents risk loss in currency. This methodology is based on risk aversion function, utility function and RC theory to establish DEIM. Findings This study shows that investors with different risk preferences have different certainty equivalent returns (CER), so their choices of investment options change accordingly. Practical implications In this paper, the authors use DEIM to test an investment case and conclude that the CER and investment scheme both change with different risk preferences. At the same time, case analysis shows that DEIM is reasonable and stable when evaluating risk investment schemes. Originality/value In this study, the authors innovate by introducing both the RC and risk aversion degree into risk investment schemes evaluation and by deriving a utility function from the absolute risk aversion function to build a utility decision matrix and establish DEIM. The model combines the subjective and objective factors that influence risk investment decisions.

Adolescents' attitudes to risk and their employment sector choices in adulthood: Evidence from longitudinal data

AbstractI investigated the effects of adolescents' attitudes toward risk on their choice of employment sector in adulthood. I employed a joint model of employment sector choice and three-dimensional background characteristics to demonstrate that employment preference is an inverse function of the degree of relative risk aversion. Empirical data was obtained from longitudinal data, and a logit model was applied to estimate the effects of the three-dimensional background characteristics on the risk-taking attitudes and employment choices. I observed that individuals with a higher tendency to engage in risky experiences exhibit low risk aversion, and thus, tend to choose a riskier employment sector.

Evaluation of risk preferences and coping strategies to manage with various agricultural risks: evidence from India.

The present study proposes to analyse farmers' attitudes towards risk and examine the effect of specific socio-demographic and socio-economic characteristics on farmers' risk attitudes in irrigated and rain-fed regions of Odisha, India. A total of 400 randomly selected farmers participated in the experiment. The study applies the Modified Holt and Laury Lottery method for measuring risk attitudes. The majority of the farmers are having a risk-averse attitude and only a few farmers have a risk-taking attitude. One-sixth of the farmers are having risk-neutral decision behavior. The effect of Socio-demographic and socio-economic variables on farmers' risk attitude is also measured using an ordered probit model dealing with risky outcomes. The study reveals a negative relationship between household size and a risk-averse attitude. The study also reveals a negative relationship between off-farm income source and risk-averse attitude. The study also finds that there is an immediate need to improve extension facilities in the study area to train these farmers regarding the best risk management practices for deciding the choice of a particular crop such as growing short-duration crops as well as climate-resistant crop variety. Storage facilities need to be improved and there is an urgent need for improved irrigation systems to increase production particularly in Bolangir district. The result provides government agencies an outline to know how risky farming environment affects farmers' production decisions and designing policies such as crop insurance, weather-based crop insurance and other safety nets that effectively address farmer's problem. The main intention behind this experimental design is to make the policy makers aware of the high degree of risk aversion existing in a rural developing farm setting. Socio-demographic and socio-economic variables can be taken as a reference while implementing policies dealing with risky outcomes.

Life-cycle analysis (LCA) to restore community building portfolios by building back better I: Building portfolio LCA

In recent years, the United States and other countries have experienced catastrophic consequences of severe natural hazards, e.g. the 2005 Hurricane Katrina, the 2011 Christchurch Earthquake, and the 2011 Great East Japan Earthquake and Tsunami. These consequences motivate the question: How should a community’s damaged building portfolio be reconstructed efficiently to enhance its performance under future hazard events and meet the resilience goals of the community? The relatively recent notion of Building Back Better requires a quantitative methodology that can address each phase of building portfolio recovery following a severe hazard event and provide decision support to best enhance the performance of the portfolio under future hazards. This study extends notions of life-cycle analysis from individual buildings to building portfolios to support post-hazard reconstruction decisions at the community level. The building portfolio expected life-cycle cost and cumulative prospect value are adopted as decision metrics which reflect varying degrees of risk aversion on the part of community decision-makers. The applicability of these building portfolio life-cycle analyses and some key aspects in their implementation are explored using a moderate-sized community that is susceptible to extreme earthquake hazards.

The Investigation of a Wealth Distribution Model on Isolated Discrete Time Domains

A wealth distribution model on isolated discrete time domains, which allows the wealth to exchange at irregular time intervals, is used to describe the effect of agent’s trading behavior on wealth distribution. We assume that the agents have different degrees of risk aversion. The hyperbolic absolute risk aversion (HARA) utility function is employed to describe the degrees of risk aversion of agents, including decreasing relative risk aversion (DRRA), increasing relative risk aversion (IRRA), and constant relative risk aversion (CRRA). The effect of agent’s expectation on wealth distribution is taken into account in our wealth distribution model, in which the agents are allowed to adopt certain trading strategies to maximize their utility and improve their wealth status. The Euler equation and transversality condition for the model on isolated discrete time domains are given to prove the existence of the optimal solution of the model. The optimal solution of the wealth distribution model is obtained by using the method of solving the rational expectation model on isolated discrete time domains. A numerical example is given to highlight the advantages of the wealth distribution model.