How much is the gap?—Efficient jump risk-adjusted valuation of leveraged certificates

This paper develops a novel and highly efficient numerical algorithm for the gap risk-adjusted valuation of leveraged certificates. The existing literature relies on Monte Carlo simulations, which are not fast enough to be used in a market-making environment. This is because issuers need to compute thousands of price updates per second. By valuing leveraged certificates as multi-window barrier options, we explicitly model random jumps that occur at known times, such as between the exchange closing and re-opening. Our algorithm combines the one-day transition probability with Simpson’s numerical integration rule. This yields a backward induction scheme which requires a significantly coarser spatial and time grid than finite-difference methods. We confirm its robustness and accuracy through Monte Carlo simulations.     

Risk sentiment and firms’ liquidity in the French market

This paper investigates the impact of risk sentiment on market liquidity by using panel data. We use six risk word lists; uncertain, weak model, negative, legal, opportunity, and environmental & social responsibility word lists to measure the risk sentiment. Concerning the liquidity proxies, we use three measures, quoted spread, effective spread, and adverse selection component. The results indicate that an intensive risk tone and uncertain information in annual reports lead to decreased liquidity. In addition we find that risk sentiment variable impacts the liquidity but not vice versa.     

A study on risk retention regulation in asset securitization process

We study the impacts of the recently proposed risk retention regulation for asset securitization, i.e. the issuer has to retain a certain proportion of securitized assets. We also consider the frequently discussed measure to require the issuer disclose certain information of the securitized assets. In a dynamic model with asymmetric information between a risk-averse originating bank and a continuum of risk-averse investors, we find that it is impossible for a flat-rate retention requirement to be optimal for all asset types. Although both risk retention and information disclosure regulations are effective in reducing investors’ informational loss, neither can unconditionally enhance social welfare upon the unregulated case. For both measures, there are associated regulatory cost: risk retention regulation aggravates adverse selection problem because it undermines the channel of informational revelation by the choice of securitization intensity, and information disclosure requirement incurs a signalling cost by distorting banks’ securitization intensity in sending signals. Under an appropriate set of conditions we find that information disclosure requirement complements risk retention regulation when investors are sufficiently risk averse.     

Does risk sharing increase with risk aversion and risk when commitment is limited?

I consider a risk-sharing game with limited commitment, and study how the discount factor above which perfect risk sharing is self-enforcing in the long run depends on agents׳ risk aversion and the riskiness of their endowment. When agents face no aggregate risk, a mean-preserving spread may destroy the sustainability of perfect risk sharing if each agent׳s endowment may take more than three values. With aggregate risk the same can happen with only two possible endowment realizations. With respect to risk aversion the intuitive comparative statics result holds without aggregate risk, but it holds only under strong assumptions in the presence of aggregate risk. In simple settings with two endowment values I also show that the threshold discount factor co-moves with popular measures of risk sharing.     

人口老龄化背景下的中国养老保险风险分析

伴随着我国人口老龄化的不断加速,社会保障尤其是养老保险领域的压力也随之加大,我国当前的养老保险体系也存在着一些现实问题与不足之处。而这都将导致在养老保险体系中固有的筹资、基金投资运营风险上升,同时也将出现制度与政策等新的风险。文章认为,需加强风险管理,不断完善养老保险制度,才能积极应对风险与收益的平衡。     

Impossibilities for strategy-proof committee selection mechanisms with vetoers

When a group of voters selects a committee out of a set of candidates, it is common and often desirable to endow these voters with some veto power. I present impossibility results showing that even limited veto power makes many mechanisms of interest manipulable. This applies in particular (i) to mechanisms the range of which contains a degenerate lottery in which a committee is chosen for sure and (ii) to mechanisms that are constructed from extensive game forms with a finite number of strategies. These impossibilities hold on a large set of domains including the domain of additive preferences, and even when probabilistic mechanisms are allowed and voters can report cardinal preferences.     

Tales from tails: On the empirical distributions of forecasting errors and their implication to risk

When evaluating the performances of time series extrapolation methods, both researchers and practitioners typically focus on the average or median performance according to some specific error metric, such as the absolute error or the absolute percentage error. However, from a risk-assessment point of view, it is far more important to evaluate the distributions of such errors, and especially their tails. For instance, a lack of normality and symmetry in error distributions can have significant implications for decision making, such as in stock control. Moreover, frequently these distributions can only be constructed empirically, as they may be the result of a computationally-intensive non-parametric approach, such as an artificial neural network. This study proposes an approach for evaluating the empirical distributions of forecasting methods and uses it to assess eleven popular time series extrapolation approaches across two different datasets (M3 and ForeDeCk). The results highlight some very interesting tales from the tails.     

Thinking critically about critical thinking: Assessing critical thinking of business students using multiple measures

Critical thinking is a skill that potential employers expect all graduates to possess. Hence, most business management programs consider critical thinking as an important student learning goal. Unfortunately, there is ambiguity about how to best assess critical thinking, both as a skill and a learning outcome. The authors empirically demonstrate how they measure the critical thinking ability of their students in different settings, and how their critical thinking ability improves as they progress through the business program.     

A strategic planning model for the railway system accident rescue problem

The present study examines the location of emergency rescue problems for urban ambulance and railway emergency systems. The proposed model considers probabilistic rescue demand, independent busy fractions of ambulances, and the corresponding risk levels in railway segments. We formulate the proposed model using fuzzy multi-objective programming and solve it using a generic algorithm and a non-dominated sorting genetic algorithm-II. Computation results are analyzed by applying the model to a real-world Taiwan railway system. Analytical results demonstrate that a proper adjustment of the rescue resource location improves rescue effectiveness for railway rescue and urban medical service demand.     

Are impatient farmers more risk-averse? Evidence from a lab-in-the-field experiment in rural Uganda

Based on data from a field-experiment in rural Uganda, we show that impatient farmers are more risk-averse than patient farmers. We relied on a simplified version of the Convex Time Budget (CTB) method to elicit farmers’ time preferences and on an independent method for eliciting their risk-preferences. We report two important findings. First, we show that our simplified CTB method applied to farmers from Uganda replicates the key findings of Andreoni and Sprenger’s lab experiments that involved student subjects. Second, we establish the existence of a negative correlation between risk tolerance and impatience, based on two independent measures.