Narrow Results

This paper investigates the impact of emergency order in a price-dependent newsvendor setting. To this end, we compare two ways handling the excess demand: the excess demand is lost and a penalty cost is incurred, or the excess demand can be satisfied by an emergency order. Which way is better depends on the emergency purchase cost $e$ in emergency-order way and the price $p$ plus penalty cost $g$ in lost-sales way. For a risk-neutral newsvendor, our results indicate that, when $e$ is not larger than $p+g$, the emergency order way can lead to smaller order quantity and higher expected profit. We continue to discuss the impact of newsvendor’s risk aversion and demand uncertainty on the optimal decisions of the two ways. Theoretical analysis and numerical examples indicate that when the emergency purchase cost is not high, the differentials of the optimal order quantities and expected profits will be larger as the degree of risk aversion/demand uncertainty increases. What is more, we prove that there exists a threshold value of the emergency purchase cost so that the two ways handling excess demand can obtain the same expected profit, and this threshold value increases as the degree of risk aversion decreases.

In this paper, we consider a newsvendor system with strategic customers, who are boundedly rational and risk averse in terms of buying during the selling season or waiting for a clearance sale with price discounts. The newsvendor’s decision is to determine the optimal stock quantity. An optimization problem is formulated with the incorporation of competition among strategic customers with private product value information. We embed risk aversion within the quantal response equilibrium to characterize the strategic customer behavior. The influences of the decision biases of strategic customers on the newsvendor’s decision and profit are discussed. We find that the risk aversion considered alone always benefits the newsvendor. However, the bounded rationality considered alone benefits the newsvendor conditionally. Combining the two behavioral factor influences, the decision biases cause the newsvendor to order more and be better off when the critical fractile is high but to order less and be worse off when the critical fractile is low.

In this paper, we consider a closed-loop supply chain (CLSC) consisting of two suppliers, one manufacturer, one risk-averse retailer and one fair-caring third-party in the presence of supply disruption. We focus on establishing a dynamic Stackelberg game model with bounded rational expectation and analyzing the game evolution process. The effects of key parameters on the Nash equilibrium solutions and their stability are investigated, as well as the complex dynamical behaviors of the CLSC system are explored by using the stability region, bifurcation graph, the largest Lyapunov exponent (LLE), strange attractors, etc. Moreover, the performance of channel members under different values of parameters is researched by utilizing the (average) expected profits or utilities index. The analysis results reveal that the excessive fast adjustment speed of the manufacturer will lead to the system losing stability and falling into chaos. Also, the retailer’s risk aversion and the third party’s fairness concerns have a destabilization effect on the Nash equilibrium point, while the possibility of supply disruption has different effects on the scope of the adjustment speed of decision variables of the manufacturer. Furthermore, in most cases, an over the top adjustment speed of the manufacturer is disadvantageous to all the channel members for more expected profits, but the third-party can achieve a better performance when the system is in periodic state. Finally, the time-delay feedback control method is proposed to eliminate the system chaos.

Cooperative game theory is very useful to risk aversion problems in economics and management systems. The existing methods only focus on the situation payoffs take the form of numerical values, ones take the form of linguistic labels are seldom discussed. The aim of this study is to propose the consistent imputation for cooperative games under a linguistic environment. To support risk aversion, a 2-tuple linguistic representation is employed to obtain the valid results and avoid the loss of linguistic information. This paper firstly defines some concepts for linguistic cooperative games, such as linguistic imputation, carrier, core and null player. A set of their desirable properties are also discussed. The linguistic Shapley value is then presented based on three axioms. Moreover, the existence and uniqueness of the linguistic Shapley value are discussed in detail. To adjust the linguistic imputation in accordance with the cardinality of a given original linguistic label set, an adjustment algorithm for generating consistent imputation is proposed. Finally, we give the application of linguistic imputation in solving risk aversion problems to illustrate the validity of the consistent imputation generation (CIG) method.

Complex systems are subject to failure with increased use and degradation. The risk process is the stochastic dynamic process of system failures and their severities. This paper considers aggregate risk measures for the risk process of complex systems in the context of stochastic ordering. The aggregation follows from the accumulation of losses from a series of failure events. The emphasis is on second-order risk measures which account for risk aversion as defined by concave utilities. A second-order measure termed the adjusted risk priority number (ARPN) is presented. The measure is constructed from well-known statistics: rate of failures, average severity of failures, and the Gini Index for severity of failures. The ARPN is contrasted with the traditional risk priority number (RPN) defined by the rate and average severity. The computation and use of the measures is illustrated with a spectrum of failure data from commercial aircraft in the USA.

This paper discusses and analyzes risk measure properties in order to understand how a risk measure has to be used to optimize the investor's portfolio choices. In particular, we distinguish between two admissible classes of risk measures proposed in the portfolio literature: safety-risk measures and dispersion measures. We study and describe how the risk could depend on other distributional parameters. Then, we examine and discuss the differences between statistical parametric models and linear fund separation ones. Finally, we propose an empirical comparison among three different portfolio choice models which depend on the mean, on a risk measure, and on a skewness parameter. Thus, we assess and value the impact on the investor's preferences of three different risk measures even considering some derivative assets among the possible choices.

A canonical problem in real option pricing, as described in the classic text of Dixit and Pindyck [2], is to determine the optimal time to invest at a fixed cost, to receive in return a stochastic cashflow. In this paper we are interested in this problem in an incomplete market where the cashflow is not spanned by the traded assets. We follow the formulation in Miao and Wang [21]; our contribution is to show that significant progress can be made in solving the Hamilton-Jacobi-Bellman equation and that the optimal exercise threshold can be characterized quite precisely.

This paper examines the properties that a risk measure should satisfy in order to characterize an investor's preferences. In particular, we propose some intuitive and realistic examples that describe several desirable features of an ideal risk measure. This analysis is the first step in understanding how to classify an investor's risk. Risk is an asymmetric, relative, heteroskedastic, multidimensional concept that has to take into account asymptotic behavior of returns, inter-temporal dependence, risk-time aggregation, and the impact of several economic phenomena that could influence an investor's preferences. In order to consider the financial impact of the several aspects of risk, we propose and analyze the relationship between distributional modeling and risk measures. Similar to the notion of ideal probability metric to a given approximation problem, we are in the search for an ideal risk measure or ideal performance ratio for a portfolio selection problem. We then emphasize the parallels between risk measures and probability metrics, underlying the computational advantage and disadvantage of different approaches.

This paper points out the importance of Stochastic Dominance (SD) efficient sets being convex. We review classic convexity and efficient set characterization results on SD efficiency of a given portfolio relative to a diversified set of assets and generalize them in the following aspects. First, we propose a linear programming SSD test that is more efficient than that of Post (2003). Secondly, we expand the SSD efficiency criteria developed by Dybvig and Ross (1982) onto the Third Order Stochastic Dominance and further to Decreasing Absolute and Increasing Relative Risk Aversion Stochastic Dominance. The efficient sets for those are finite unions of convex sets.

This paper demonstrates the simple incorporation of any shape of risk aversion into an asset allocation framework. Indeed, the relevant literature about risk aversion shows mixed evidence regarding the shape of this important but subjective variable. Our setting builds on, and can be compared with, the well-known constant relative risk aversion (CRRA) framework and mostly preserves the tractability of the affine-CRRA framework. Our numerical analysis exhibits some link between measures of risk aversions and empirical studies of asset allocation.

This paper proposes an equilibrium model for evaluating equity with optimal dividend policy in a jump-diffusion market. In this model, a representative investor having power utility over an aggregate consumption process evaluates the equity as the expected value of the discounted dividends with his stochastic discount factor, while a firm paying the dividends from its own cash reserves manages to maximize the equity price. This situation is formulated as a singular stochastic control problem of jump-diffusion processes. We solve this problem and give the equilibrium equity price and the optimal dividend policy. Numerical examples show that the aggregate consumption process and the investor’s risk aversion have a significant impact on the equity price and the dividend policy. This model provides a structural explanation of equity risk premiums that is consistent with the standard theory of asset pricing.

Real option valuation has traditionally been concerned with investment under project value uncertainty while assuming that the agent has perfect confidence in a specific model. However, agents do not generally have perfect confidence in their model and this ambiguity may affect their decisions. In addition, the value of real investments is not typically fully spanned by tradable assets because markets are incomplete as is typically the case in energy and commodities. In this paper, we account for the agent’s aversion to model ambiguity and address market incompleteness through the notion of robust indifference prices. We derive analytical results for the perpetual option to invest and the linear complementarity problem that the finite-time version of this problem satisfies. Ambiguity aversion has a number of effects on decision making some of which cannot be explained by altering the agent’s risk aversion. For example, ambiguity averse agents are found to exercise real options both earlier and later than their ambiguity neutral counterparts, depending on whether ambiguity stems from uncertainty in the dynamics of the project value or the dynamics of a hedging asset.

We propose a new nonparametric technique to estimate the call function based on the superhedging principle. This approach requires minimal assumptions on absence of arbitrage and other market imperfections. The estimates so obtained are then combined with SNP estimates of the actual density of market returns. This permits to investigate the time behavior of the relative distance between the two densities obtained. Our empirical findings suggest that the more the two densities differ, the shorter is time to maturity, suggesting a major role of uncertainty over shorter than longer horizons.

I study the allocation problem of investors who hold their portfolio until reaching a target wealth. The strategy suppresses final wealth uncertainty but creates a time horizon risk. I begin with a classical mean variance model transposed in the duration domain, then study a dynamic portfolio choice problem with Generalized Expected Discounted Utility preferences. Using long-term US return data, I show in the mean variance model that a large amount of time horizon risk can be diversified away by investing a significant share of equities. In the dynamic model, more impatient investors are also more averse to timing risk and invest less in equities. The optimal equity share is downward trending as accumulated wealth approaches its target.

This study examines the association between gender and financial activities among middle- and old-aged adults in Taiwan. We conduct a survey of 221 respondents who attended a seminar on financial activities of older adults held by the Trust Association of Taiwan and participated in subsequent surveys on the community during 2017 and 2018. We found that females are more likely to participate in a greater number of financial activities compared with their male counterparts. In particular, we found evidence to support the positive association between female adults and riskier financial activities, such as stocks and mutual funds. Our findings support the information process hypothesis in which gender is an important factor for determining an individual’s participation in financial activities.

We propose a new noncooperative approach to implement a cooperative bargaining solution. This approach relies on a mechanism which specifies what happens when, at the end of the bargaining phase, players’ propositions are still not compatible. The mechanism uses a random lottery and the history of proposals. At equilibrium, under the threat of this mechanism, provided that the use of it carries a small cost, players reach consensus after a finite number of proposals. No discounting is needed. The equilibrium strategies implement the full Raiffa bargaining process and players agree on a solution arbitrarily close to the Raiffa solution.

The behaviour of traders in a stock market is influenced by their attitude toward the risk of the security. In this research the internal model of the risk-averse and the risk-loving trader is proposed in the context of the artificial market. This model is based on the ideas of the expected utility hypothesis. It is important to model the difference in subjective value of the same stock because this difference enables market activities. The feature of the proposed model is that this model realizes the dynamic aspect of trader's preference in the risk and the return.

We examine the effect of stock options on managerial incentives to invest. Our chief innovation is a model wherein firm value and executive decisions are endogenous. Numerical solutions to our model show that managerial incentives to invest are multi-dimensional and highly sensitive to option strike prices, the manager's wealth, degree of diversification, risk aversion, and career concerns. We show that under- and over-investment problems can be large and economically significant, with hurdle rates ranging from more than 20 percentage points below to more than 35 percentage points above shareholders' required rate of return. Finally, firm value is not a strictly increasing function of a manager's incentive compensation or conventional pay–performance sensitivity metrics. Stronger managerial incentives to invest can benefit or harm a firm.

I define the rate of inequity aversion, distinguishing between the pure rate and the consumption rate. I measure the rate of aversion to inequality in consumption as expressed in the development aid given by rich countries to poor ones between 1965 and 2005. There is an ambiguous relationship between the pure rate of inequity aversion and the consumption rate, driven by the rate of risk aversion. However, for a reasonable choice of the rate of risk aversion, rich countries are shown to be inequity averse, and increasingly so over time. The social cost of carbon is very sensitive to equity weighting and assumptions about the rate of risk and inequity aversion. Estimates of the consumption rate of inequity aversion for recent data suggest that the equity-weighted social cost of carbon is less than 50% larger than the unweighted estimate.

We propose a single evolutionary explanation for the origin of several behaviors that have been observed in organisms ranging from ants to human subjects, including risk-sensitive foraging, risk aversion, loss aversion, probability matching, randomization, and diversification. Given an initial population of individuals, each assigned a purely arbitrary behavior with respect to a binary choice problem, and assuming that offspring behave identically to their parents, only those behaviors linked to reproductive success will survive, and less reproductively successful behaviors will disappear at exponential rates. When the uncertainty in reproductive success is systematic, natural selection yields behaviors that may be individually sub-optimal but are optimal from the population perspective; when reproductive uncertainty is idiosyncratic, the individual and population perspectives coincide. This framework generates a surprisingly rich set of behaviors, and the simplicity and generality of our model suggest that these derived behaviors are primitive and nearly universal within and across species.