The composite iteration algorithm for finding efficient and financially fair risk-sharing rules

We consider the problem of finding an efficient and fair ex-ante rule for division of an uncertain monetary outcome among a finite number of von Neumann–Morgenstern agents. Efficiency is understood here, as usual, in the sense of Pareto efficiency subject to the feasibility constraint. Fairness is defined as financial fairness with respect to a predetermined pricing functional. We show that efficient and financially fair allocation rules are in one-to-one correspondence with positive eigenvectors of a nonlinear homogeneous and monotone mapping associated to the risk sharing problem. We establish relevant properties of this mapping. On the basis of this, we obtain a proof of existence and uniqueness of solutions via nonlinear Perron–Frobenius theory, as well as a proof of global convergence of the natural iterative algorithm. We argue that this algorithm is computationally attractive, and discuss its rate of convergence.     

The Effects of Productivity Shocks,Financial Shocks,and Monetary Policy on Exchange Rates: An Application of the Currency Crisis Model and Implications for Emerging Market Crises

What kind of shock affects exchange rate dynamics? How much of an effect does the monetary policy have on exchange rates? To answer these questions empirically based on the currency crisis model, I use panel data on 51 emerging countries from 1980 to 2011, identify shocks, and apply instrumental variable methods. I found that both productivity shocks and shocks to a country’s risk premium affect exchange rates and a 1 percentage point increase in the policy interest rate is associated with a 1 percentage point appreciation of domestic currency. I further apply this method to Asian and Latin-American crises.     

Semiparametric estimation of multi-asset portfolio tail risk

When correlations between assets turn positive, multi-asset portfolios can become riskier than single assets. This article presents the estimation of tail risk at very high quantiles using a semiparametric estimator which is particularly suitable for portfolios with a large number of assets. The estimator captures simultaneously the information contained in each individual asset return that composes the portfolio, and the interrelation between assets. Noticeably, the accuracy of the estimates does not deteriorate when the number of assets in the portfolio increases. The implementation is as easy for a large number of assets as it is for a small number. We estimate the probability distribution of large losses for the American stock market considering portfolios with ten, fifty and one hundred assets of stocks with different market capitalization. In either case, the approximation for the portfolio tail risk is very accurate. We compare our results with well known benchmark models.     

Cost-benefit analysis of airport security: Are airports too safe?

This paper assesses the risks and cost-effectiveness of measures designed to further protect airport terminals and associated facilities such as car parks from terrorist attack in the U.S., Europe, and the Asia-Pacific area. The analysis considers threat likelihood, the cost of security measures, hazard likelihood, risk reduction and expected losses to compare the costs and benefits of security measures to decide the optimal security measures to airports. Monte-Carlo simulation methods were used to propagate hazard likelihood, risk reduction and loss uncertainties in the calculation of net benefits that also allows probability of cost-effectiveness to be calculated. It is found that attack probabilities had to be much higher than currently observed to justify additional protective measures. Overall, then, it is questionable whether special efforts to further protect airports are sensible expenditures. Indeed, some relaxation of the measures already in place may well be justified.     

Risk regulation,community pressure and the use of management accounting in managing climate change risk: Australian evidence

This exploratory study is amongst the first to investigate how companies perceive the regulation of carbon emissions and the pressure exerted by the community in an environment characterised by risk and uncertainty. Semi-structured interviews were conducted among 39 executives who were directly involved in carbon emissions management in 18 large listed Australian companies. Consistent with Prospect Theory, we find that decision-makers are threat biased and are more likely to take immediate actions when climate change issues are framed as threats as opposed to opportunities. From the interview data, it is seen that managers use management accounting techniques as a risk management tool in mitigating risks associated climate change issues. Furthermore, this use of management accounting appears to be driven primarily by the protection of economic interests, regulatory pressure and reputational pressure. The study provides insights into how perceptions of climate change uncertainties and external pressure for disclosure of emissions information influence companies to use management accounting in managing climate change risk.     

REAL OPTIONS AND THE CROSS‐SECTION OF EXPECTED STOCK RETURNS

This paper surveys the theoretical literature investigating the effect of firms’ investment flexibility on the cross‐section of expected stock returns. Real options analysis derives firms’ value‐maximizing investment policies as functions of exogenous fundamental drivers of profitability and calculates firms’ market values as functions of the same variables. These functions yield the relationship between expected stock returns and firm fundamentals. Several plausible explanations for the value premium – the high average stock returns earned by firms with high book‐to‐market ratios – emerge from this literature.     

EXTREME VALUE THEORY IN FINANCE: A SURVEY

Extreme value theory is concerned with the study of the asymptotic distribution of extreme events, that is to say events which are rare in frequency and huge in magnitude with respect to the majority of observations. Statistical methods derived from it have been employed increasingly in finance, especially for risk measurement. This paper surveys some of those main applications, namely for testing different distributional assumptions for the data, for Value‐at‐Risk and Expected Shortfall calculations, for asset allocation under safety‐first type constraints, and for the study of contagion and dependence across markets under conditions of stress.     

Fair Value Measurements of Control Premiums

As the overview of the current state of research within this paper shows, the debate around fair value measurements is far from over. This paper analyzes fair value measurement requirements in a controversial scenario, namely when a control premium exists. The analyses of the paper show that, while measurement rules around control premiums could have a material impact on fair value measurements and the financial statements as a whole, significant fair value measurement issues remain unresolved. The conclusion is that fair value measurements should include or exclude control premiums consistently. It is argued that including control premiums for all fair value measurements is the most faithful representation of the underlying economic phenomenon. This paper contributes to the fair value measurement debate by comparing the merits of alternative fair value measurements for control premiums and highlights an area where researchers, investors, and other users should exercise caution when evaluating financial statements.     

Credibilistic risk aversion

In the probabilistic risk aversion approach, risks are presumed as random variables with known probability distributions. However, in some practical cases, for example, due to the absence of historical data, the inherent uncertain characteristic of risks or different subject judgements from the decision-makers, risks may be hard or not appropriate to be estimated with probability distributions. Therefore, the traditional probabilistic risk aversion theory is ineffective. Thus, in order to deal with these cases, we suggest measuring these kinds of risks as fuzzy variables, and accordingly to present an alternative risk aversion approach by employing credibility theory. In the present paper, first, the definition of credibilistic risk premium proposed by Georgescu and Kinnunen [Fuzzy Inf. Eng., 2013, 5, 399–416] is revised by taking the initial wealth into consideration, and then a general method to compute the credibilistic risk premium is provided. Secondly, regarding the risks represented with the commonly used LR fuzzy intervals, a simple calculation formula of the local credibilistic risk premium is put forward. Finally, in a global sense, several equivalent propositions for comparative risk aversion under the credibility measurement are provided. Illustrated examples are presented to show the applicability of the theoretical findings.     

How locus of control shapes intention to reuse mobile apps for making hotel reservations: Evidence from chinese consumers

This study unveils the cognitive mechanism that locus of control (LOC) dimensions (internal control, chance control, and control by powerful others) predict intention to reuse mobile apps for making hotel reservations. The predictions are assumed through the unified theory of acceptance and use of technology (UTAUT) anchors and perceived risk. Drawn from an online survey with 457 Chinese participants, results show direct positive predictions of intention to reuse from UTAUT anchors including performance expectancy, effort expectancy, social influence, and facilitating conditions. Perceived risk also negatively predicts intention. Effort expectancy mediates the links between internal/chance control and intention, whereas perceived risk mediates only the latter link. Facilitating conditions mediate the relationship between control by powerful others and intention. This study contributes to existing research by distinguishing the mechanisms that underpin LOC dimensions and technology re-adoption. Practitioners are recommended to improve booking apps by addressing the concerns of users with different LOC.