Degree Of Risk Aversion Research Articles

Can Investment Views Explain Why People Insure Their Cell Phones But Not Their Homes?—A New Perspective on the Catastrophe Insurance Puzzle

The consistently missing demand for catastrophe insurance and for coverage of other low-probability–high-consequence risks is often referred to as the catastrophe insurance puzzle. People show reluctance to insure low-probability–high-consequence events, even with some disastrous consequences, yet insure against small high-probability–low-consequence events. There has been no convincing explanation of this puzzle to this date. This article points out that the underlying rationale may be that individuals interpret insurance contracts with low payout probability as an investment with negative expected net present value. While premium payments start with the conclusion of the contract, usually there is only one loss payment in the near or far future. Using a simple annuity model with fixed annual premiums and expected indemnity payouts, it is found that even an individual characterized by the degree of risk aversion found in the literature is unlikely to purchase insurance with these characteristics. To alleviate this unfavorable insurance purchase syndrome, combining a low-probability with a high-probability loss insurance contract may be a way to incentivize individuals to purchase catastrophe risk coverage.

Optimal product and after-sales service decisions considering risk attitudes under price-dependent uncertain demand

In this paper, we investigate a service-oriented manufacturer that provides fashionable products with after-sales services to customers. Before the selling season, the manufacturer invests in service capacity in advance and then decides on the production quantity and selling price based on updated demand information. Interestingly, it is found that the manufacturer’s production and pricing decisions will not be affected by the unit production cost when the market base exceeds a threshold. We investigate and compare the manufacturer’s decisions in two cases: imperfect and perfect demand information updates. The selling price in the imperfect demand updates case is always set lower than that in the perfect demand updates case when the service capacity is sufficient but may not be under insufficient service capacity. The possibility that the prepared service capacity limits the production quantity may decrease with the unit production cost in the imperfect demand updates case. In contrast, this possibility is invariant with the unit production cost in the case of perfect demand updates. The effects of risk aversion are also investigated. It is found that under the conditional value-at-risk (CVaR) criterion, the manufacturer with a higher risk-averse degree establishes a lower service capacity and sets a lower selling price.

Blockchain Adoption for Generic Drugs in the Medicine Supply Chain with Consumers' Risk-Aversion: A Game-Theoretic Model Within Chinese Legal Framework.

Blockchain is expected to mitigate consumers' risk-aversion and quality uncertainty about generic drugs in medicine supply chains. This study investigates the effect of blockchain adoption for disclosing the quality information of generic drugs that compete with original drugs in the market and proposes legal measures accordingly. We employ a game-theoretic model to analyze a medicine supply chain including a generic drug manufacturer, an original drug manufacturer, and a retailer. We examine when should the supply chain members adopt blockchain for generic drugs and how blockchain affects the medicine supply chain. Our results show that the quality information of generic drugs determines how blockchain adoption affects the price and sales quantity of generic and original drugs. Moreover, we observe that the generic drugs manufacturer and the retailer decide to adopt blockchain only if consumers' risk-aversion degree is sufficiently low. Also, a low risk-aversion degree can lead to higher whole supply chain's profitability with blockchain adoption, and generate a win-win-win situation of blockchain adoption for the consumers, the generic drug manufacturer, and the retailer. To mitigate consumers' risk aversion, the law should safeguard consumer rights. Blockchain adoption can benefit the medicine supply chain and consumers under certain conditions. However, it also requires the coordination of supply chain members' benefits and the disclosure of quality information.

Risk-Averse Ride-Hailing Platform Operations With Safety Risk-Averse Consumers Under Pandemics: Roles of Blockchain Technology and Government Sponsors

Today, ride-hailing platform operations are popular. Facing pandemics (e.g., COVID-19) some customers feel unsafe for the ride-hailing service and possess a “safety risk-averse” (SRA) attitude. The proportion of this type of SRA customers is unfortunately unknown, which makes it difficult for the ride-hailing platform to decide its optimal service price. In this article, understanding that blockchain technology (BT) based systems can help improve market estimation for the proportion of SRA customers, we conduct a theoretical study to explore the impacts that the BT-based system can bring to the platform, customers, and drivers. We consider the case in which the platform is risk-averse (in profit) and serves a market with both SRA and non-SRA customers. We analytically prove that using BT, the optimal service price will be increased and BT is especially helpful for the case with a more risk-averse ride-hailing platform. However, whether it is more or less significant for the more risk-averse SRA customers depends on their degree of risk aversion. We uncover that when the use of BT is beneficial to the customers, it will also be beneficial to the drivers, and vice versa. We derive in closed-form the analytical conditions under which the use of BT can be beneficial to the ride-hailing platform, customers, and drivers (i.e., achieving “all-win”). When all-win cannot be achieved automatically, we explore how governments can provide sponsors to help. We further extend the analysis to consider the general case in which BT incurs both a fixed cost as well as a cost increasing in demand. We prove that the main conclusion remains robust. In addition, we reveal that the required amount of government sponsor to achieve all-win is the same between the two different costing models explored in this article.

A Capacity Adequacy Mechanism Based on Optional Option and Its Impact on Generation Mix Equilibrium

Due to the missing money problem, it is a challenging task to maintain generation capacity adequacy with increasing shares of zero-marginal-cost renewable energy resources. Multiple capacity adequacy mechanisms (CAMs), such as scarcity pricing, capacity payment, capacity market, and reliability option, have been proposed and implemented, each having its own pros and cons. Here, we propose a hybrid CAM called optional option. The hybrid CAM allows scarcity pricing and reliability option to co-exist. Market participants, with diverse degrees of risk aversion and diverse forecasts of future duration of scarcity, can self-select the CAM best suited to themselves. We also present a method to efficiently derive the generation mix equilibrium under the CAM, by using the theory that the profits of all generator types approach zero in the long-term equilibrium. Simulation results show that the proposed CAM enables Pareto improvement by letting market participants be better off than being restricted to only one CAM. The results also show the effectiveness of the algorithm to calculate the generation mix equilibrium.

A multi-agent incomplete equilibrium model and its applications to reinsurance pricing and life-cycle investment

This paper develops an incomplete equilibrium model with multi-agents' different risk attitudes and heterogeneous income/payout profiles. Particularly, we apply its concrete and computationally tractable model to reinsurance derivatives pricing and life-cycle investment, which are important for insurance and asset management companies in practice. In numerical experiments, we explicitly obtain endogenously determined expected returns of the risky asset in equilibrium, agents' specific reinsurance prices with their stochastic discount factors (SDF) and optimal life-cycle trading strategies. Moreover, we investigate how each agent's degree of risk aversion and income/payout profile, and correlations between an insurance or economic factor and the risky asset price affect reinsurance claims pricing and optimal portfolios in life-cycle investment.

Hedging goals

Goal-based investing is concerned with reaching a monetary investment goal by a given finite deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in Browne (Adv Appl Probab 31(2):551–577, 1999) by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. Föllmer and Leukert in Finance Stoch 3:251–273, 1999) and minimizing the expected shortfall (efficient hedging, cf. Föllmer and Leukert in Finance Stoch 4:117–146, 2000) yield, in fact, the same optimal investment policy. We furthermore present an innovative and model-free approach to goal-based investing using methods of reinforcement learning. To the best of our knowledge, we offer the first algorithmic approach to goal-based investing that can find optimal solutions in the presence of transaction costs.

Production Diversification as a Tool for Agricultural Risk Management: The Case of Northern Kazakhstan

This paper addresses the impacts of degree of risk aversion on optimal farm plans in Kazakh agriculture. The results obtained during the field research in the region of Northern Kazakhstan are presented. Calculations were carried out using data from 145 peasant farms in the region for 2017-2022 based on a risk model. It has been found that the choice of a portfolio is influenced not only by considerations of profitability and riskiness of crops, but also by grain production traditions deeply rooted among the farmers of the region, and the skills and knowledge associated with them, as well as the existing infrastructure. These circumstances constrain the wider spread of oilseed crops in the region. It seems that the size of the farm does not significantly affect the choice of portfolio, while the degree of risk aversion by the farmer affects the optimal farming plan. The potential benefits of the farming diversification are an empirical issue, and it should be addressed on a case-by-case basis. The question is to choose the utility function and its parameters that most accurately reflect the preferences of a particular farmer, the authors conclude.

On the Combination of Naive and Mean-Variance Portfolio Strategies

We study how to best combine the sample mean-variance portfolio with the naive equally weighted portfolio to optimize out-of-sample performance. We show that the seemingly natural convexity constraint—the two combination coefficients must sum to one—is undesirable because it severely constrains the allocation to the risk-free asset relative to the unconstrained portfolio combination. However, we demonstrate that relaxing the convexity constraint inflates estimation errors in combination coefficients, which we alleviate using a shrinkage estimator of the unconstrained combination scheme. Empirically, the constrained combination outperforms the unconstrained one in a range of generally small degrees of risk aversion, but severely deteriorates otherwise. In contrast, the shrinkage unconstrained combination enjoys the best of both strategies and performs consistently well for all levels of risk aversion.

Religiosity, financial distress and R&D accounting treatment in US context

PurposePrior research shows that religiosity affects the degree of managers' risk aversion. As a result, religious firms are less likely to invest in R&D activities. Moreover, US GAAP treats these investments as expenses. For this reason, religious firms have fewer expenses in their earnings and are less likely to be in financial distress.Design/methodology/approachData are collected from Worldscope and the Churches and Church Membership files of the American Religion Data Archive website from 1985 to 2018. With 18,199 observations in US context, the authors used the marginal effect to test the mediating effect of R&D accounting treatment.FindingsThe authors find that the marginal effect of religiosity on financial distress with US GAAP is higher than the marginal effect of religiosity on financial distress with capitalization of R&D costs, which means that accounting treatment can explain the relation between religiosity and financial distress in the US context.Research limitations/implicationsThe authors used linear interpolation and linear extrapolation data to be able to conduct this research over a period of 1985–2018. For future researches, the authors propose to test other factors which can explain the relationship between religiosity and financial distress based on the ethics element.Practical implicationsThese results should be of interest to regulators because treating R&D activities as expenses can destroy the accounting performance of firms that prefer investing in risky projects. This favoritism prevents the comparison between two firms in the same industry with different risk-taking behaviors. This problem is more prevalent if the authors have two firms with different ratios of religiosity. This paper suffers from a major limitation related to data availability.Originality/valueThis may be the first study that investigates why religious firms are less likely to be in financial distress. This paper notes that religious firms are less likely to be in financial distress because their conservative behavior towards R&D activities coincides with the conservative R&D accounting treatment. In fact, the mismatch between expenses and revenues from R&D activities can cause financial distress.

Optimal contracting with asymmetric risk aversion information and fairness concerns

PurposeThis study considers a contracting problem between a fairness concerned entrepreneur (EN) and a fair-neutral venture capitalist (VC) to explore the effects of asymmetry, agency conflicts and fairness concerns.Design/methodology/approachThe authors construct the model by assuming the EN's risk aversion degree is private information, which is more realistic but ignored in most studies. Under the principal–agent framework, the authors solve the VC's optimal contracting models by identifying the ranges of feasible solution, where the optimal solutions of these models are explicit and nicely reconcile the “private equity” puzzle. Moreover, validity of the optimal solutions is verified by numerical simulations.FindingsIn accordance with empirical evidence, information asymmetry lowers the optimal equity share that the VC provides to EN but raises EN's profit due to lower effort disutility and information rent. Moreover, the authors find that the fairness concerns is beneficial for the EN, where it not only increases the EN's optimal equity share, but also enhances the certainty equivalence of the EN's utility regarding its profit. Relative to the benchmark model where the EN's risk aversion degree is common knowledge, the EN's efforts recommended by the optimal contract is less sensitive to the EN's fairness concerns degree when the EN does not actually announce its risk aversion degree.Originality/valueFirst, the authors incorporate asymmetry to study a two-period contracting problem and explore how it affects the equity shares allocated to the contractual parties. Second, the authors incorporate fairness concerns and analyze its effect regarding the decision-makings and profits.

Predicting cryptocurrency returns for real-world investments: A daily updated and accessible predictor

This paper uses a daily updated and accessible Crypto Fear and Greed Index (FG) to predict cryptocurrency returns. Investors can easily use return predictions from FG for real-world cryptocurrency investments. Empirical results show that FG has significant in-sample and out-of-sample predictive power at forecast horizons ranging from one day to one week. The predictive power of FG exists for individual cryptocurrencies and different market indices. From an investment perspective, we use different evaluation indicators and demonstrate that FG can bring substantial economic benefits to investors with different degrees of risk aversion.

Market uncertainty, persistent arbitrage-free violation, and price discovery in RMB market

This paper applies a fractionally cointegrated vector autoregressive model to examine time-varying price discovery between Chinese renminbi onshore and offshore exchange rates. We study the impact of the equity market and economic policy uncertainty level on price discovery and the arbitrage opportunities between the onshore and offshore markets. The results show that the less regulated offshore rates dominate in price discovery, and a higher market uncertainty level strengthens the leading role of offshore rates in price discovery. However, a higher market uncertainty would increase the bid–ask spread and investors’ risk aversion degree and then impede the whole price discovery. Finally, higher uncertainty would induce persistent arbitrage opportunities in renminbi onshore and offshore markets.

Risk-averse two-stage stochastic programming-based closed-loop supply chain network design under uncertain demand

In recent years, there has been a growing awareness and acceptance of the concept of green environmental protection among the public, primarily due to the worsening environmental issues and increased emphasis by governments on corporate social responsibility regulations. As a result, the management of closed-loop supply chains has gained significant attention from both businesses and researchers. Most stochastic programming models addressing closed-loop supply chain (CLSC) under uncertainty are typically designed to be risk-neutral. In this paper, a risk-averse two-stage stochastic programming (RATSSP) model for the closed-loop supply chain network design (CLSCND) problem considering facility capacity level decisions under uncertain demand. It is aiming to trade off the expected total profit and the profit risk, based on a given degree of responsive risk aversion. Due to the NP-hard nature of the CLSCND problem, this paper applies simplified swarm optimization (SSO), genetic algorithm (GA), and particle swarm optimization (PSO) algorithms to solve the problem. To improve the efficiency and quality of the obtained solutions, we propose a parallel computation meta-heuristic algorithm, parallel simplified swarm optimization (PSSO), along with parallel versions of PSO and GA. Computational results show the effectiveness of our proposed model, with PSSO demonstrating the best robustness and solution quality among the considered algorithms.

Mutual optimism and risk preferences in litigation

Why do some legal disputes fail to settle? From a bird’s eye view, the literature offers two categories of reasons. One consists of arguments based on informational disparities. The other consists of psychological arguments. This paper explores the psychological theory. It presents a model of litigation driven by risk preferences and examines the model’s implications for trials and settlements. The model suggests a foundation in Prospect Theory for the Mutual Optimism model of litigation. The model’s implications for plaintiff win rates, settlement patterns, and informational asymmetry with respect to the degree of risk aversion are examined.

Pricing decisions of risk averse logistic companies with carbon cap and trade under Stackelberg game.

With the implementation of the double carbon plan, this paper considers the delivery fees of two risk averse logistics companies under carbon cap and trade mechanism. We establish logistics company Stackelberg (MS) model and retailer Stackelberg (RS) model under mean variance (MV) framework, respectively. We obtain the optimal delivery fees and retail prices. We find out that the higher degree of risk aversion can lead to a lower delivery fee. We also show that a higher carbon trading price or a higher cross price sensitivity will increase delivery fees. Moreover, we indicate that the performances of logistics companies under MS scenario are higher than that RS scenario. In addition, we suggest that under the carbon cap and trade rules, in order to obtain higher profits, logistics companies should use fuel vehicle for transportation under certain conditions, and use electric vehicle in other cases.

Experimental Study on the Risk Preference Characteristics of Members in Supply Chain Emergencies

Since risk preference affects the behavior of decision makers, the study of its characteristics and impact on decision-making contributes to good planning for emergency coordination. The consistency of a member’s risk preferences in the conventional risk field and emergencies of a supply chain was analyzed by applying the prospect theory and adapting the domain-specific risk-taking (DOSPERT) scale. The influence of time pressure on the risk preferences and decision-making behaviors of members was studied in the emergency field and its sub-emergencies of a supply chain. The conclusions were drawn based on the empirical study. First, the risk preference could be measured in terms of conventional risk and emergencies. Second, the members tended to be risk averse with no time pressure, and the degree of risk aversion was weakened with time pressure, which had the greatest effect in the natural disaster event. Third, even though the change in risk preference had a consistency regarding the four types of sub-events of supply chain emergencies, it was inconsistent regarding the conventional risks and emergencies. With the evolution trend of risk preference demonstrated and the relationship between preference and time pressure revealed, this study may provide a decision-making reference for the formulation of a supply chain emergency coordination scheme.

A Robust Stochastic Programming Model for the Well Location Problem: The Case of The Brazilian Northeast Region

Slow-onset disasters, such as drought, are usually more destructive in the long term since they affect the productive capacity of a community, thereby preventing it from recovering using its resources. This requires the leaders and planners of drought areas to establish the best strategies for effective drought management. In this direction, the present work develops a robust stochastic programming approach for the problem of locating artesian wells for the relief of drought-affected populations under uncertainty. Our model considers different demand scenarios and proposes a novel perspective which considers both social and hydrogeological aspects for the location choice, aiming to maximize the affected area’s satisfaction through its prioritization using a composite drought risk index as well as to maximize the probability of success in water prospecting. We present a case study of our robust stochastic optimization approach for the Brazilian Semiarid Region using demand points from the database of Operação Carro-Pipa. Our findings show that a robust solution has a better expected value for the objective function considering all scenarios, so it can help decision makers to plan facility location and demand allocation under demand uncertainty, pointing out the best solution according to their degree of risk aversion.

How Do Personality Traits of Young Adults Affect Their Attitudes to Risk and Investment Decisions?

This paper examines the relationship between the Big five personality traits, socio-economic characteristics, and the investment decisions of individuals, with a focus on the decision-making of young adults. The empirical analysis was carried out using data obtained from a survey which identified the young adults’ personality traits, degree of risk aversion and preferred investment strategy. The estimation results show that individuals who are more agreeable have a higher degree of risk aversion. However, men and individuals with higher income are less risk averse, while older individuals in our sample tend to have a higher degree of risk aversion. The estimation results also show that certain personality traits and socio-demographic characteristics significantly affect the choice of individuals’ choice of preferred investment strategy. More extroverted individuals in our sample were identified as more likely to diversify their investment portfolio. However, we find that individuals more open to new experiences are more conservative in their investment decisions and diversify their investment with a lower probability. Considering individual socio-economic characteristics, men are more likely to diversity their investment portfolio and choose a less conservative investment strategy than women. Furthermore, marital and employment status were found to be significantly related to a preference towards a conservative investment strategy.

Pricing and contract preference in maritime supply chains with downstream competition impact of risk-aversion and contract unobservability

The maritime market has been facing increasingly fierce competition. Most of the existing literature in maritime supply chain assumes that the details of the contracts between ports and carriers are common knowledge among all competing carriers. In reality, it is usually difficult for carriers to be fully aware of each other's contracts with ports. In view of this, we consider two representative contracts, namely wholesale price contact and two-tariff contract, construct a maritime supply chain with one port and two carriers, and analyze how risk-aversion behavior and contract unobservability impact the pricing and contract preference. We use passive beliefs as an equilibrium refinement criterion to solve the model. Our findings indicate that the carrier prefers the wholesale price contract, regardless of whether the contract is observable or not. The port tends to select the two-part tariff contract when the contract is observable. When faced with an unobservable contract, contract preference of the port depends on the competition intensity and degree of risk-aversion. Additionally, under the wholesale price contract, the port can benefit from the decrease of its risk-aversion coefficient and the increase of the carrier's risk-aversion coefficient, while the carrier is exactly the opposite. Meanwhile, the utility of the port can be increased or reduced by the increase in carrier's risk-aversion coefficient under the two-part tariff contract.