Sustainable hub location under mixed uncertainty

This paper addresses a novel sustainable hub location problem (SHLP) in which two new environmental-based cost functions accounting for air and noise pollution of vehicles are incorporated. To cope with uncertain data incorporated in the model, a mixed possibilistic–stochastic programming approach is proposed to construct the crisp counterpart. A simulated annealing (SA) and an imperialist competitive algorithm (ICA) with a new solution representation are developed to solve real-sized instances whose performances are compared with a proposed lower bound. Finally, some computational experiments are provided to demonstrate the effectiveness of the proposed model and solution approaches.     

Modelling the implied volatility surface based on Shanghai 50ETF options

We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance.     

Short-time at-the-money skew and rough fractional volatility

The Black–Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time to maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power law. The volatility process of the model is driven by a fractional Brownian motion with Hurst parameter less than half. The fractional Brownian motion is correlated with a Brownian motion which drives the asset price process. We derive an asymptotic expansion of the implied volatility as the time to maturity tends to zero. For this purpose, we introduce a new approach to validate such an expansion, which enables us to treat more general models than in the literature. The local-stochastic volatility model is treated as well under an essentially minimal regularity condition in order to show such a standard model cannot be dynamically consistent to the power law.     

The veto mechanism in atomic differential information economies

We establish new characterizations of Walrasian expectations equilibria based on the veto mechanism in the framework of differential information economies with a complete finite measure space of agents. We show that it is enough to consider the veto power of a single coalition, consisting of the entire set of agents, to obtain the Aubin private core. Moreover, we investigate on the veto power of arbitrarily small and big coalitions, providing an extension to mixed markets of well known Schmeidler (1972) and Vind’s (1972) results in terms of Aubin private core allocations.     

Socio-economic and biophysical determinants of land degradation in Vietnam: An integrated causal analysis at the national level

Recognizing the socio-economic and biophysical causes of land degradation at the national level is important for cause-targeted strategies when designing policies for combating land degradation. This study aims to identify the biophysical and socio-economic factors that significantly affect land degradation across Vietnam and to interpret the causalities underlying the effects. The dependent variables considered in the study are spatial, the extent and intensity of degradation in three land-use zones (agriculture, forest and severely degraded abandonment). The hypothesized explanatory variables are common economic and demographic drivers and bio-physical factors such as soil, terrain constraints, and neighborhood land-use structures that are often neglected in many large-scale land degradation assessments. Instead of using a single inferential statistic technique, we used multi-linear regression and binary logistic regression in a complementary manner to increase the detectability and credibility of the degradation cause analyses. The results showed agricultural production growth had strong and consistent effects on land degradation extent and intensity. Population growth, especially in rural areas, had a strong effect on the extent of overall land degradation. The importance of a neighboring forest was revealed for its ability to reduce land degradation intensity in abandoned, unproductive lands. The concrete faceting of the causal analysis for each land-use zone as social–ecological stratum allowed us to combine the defined social–ecological contexts, contemporary theories, and hypotheses in the field to clarify the causal factors of a complex phenomenon like land degradation. The study demonstrates these contemporary inferential statistics can be complementarily used to sufficiently detect and understand land degradation causes at the national level. The results suggest implications for national land management policy: internalizing land degradation costs in the farming system evaluation for payment for ecosystem services policy, restricting forest conversion, and improving extension services and education in agrarian communities.     

The shared environmental responsibility principle: new developments applied to the case of marine ecosystems

Estuaries provide advantageous sites for both harbors and fish habitats. In many countries, harbor expansion in estuaries contributed to the decline of fish populations with impacts at the global scale. Restoring these habitats is important to prevent a global biodiversity crisis but is costly and potentially unaffordable for polluters under the Polluter Pays Principle. Such affordability issues prompt decision-makers to reduce environmental targets of restoration programs. Harbor infrastructures destroy fish habitats but generate benefits for society and contribute to the public interest, raising some questions on who is responsible for environmental degradations and who can afford environmental restoration costs? One way to allocate restoration costs is to analyze the amount of harbor services consumed by economic sectors. This paper addresses these questions by computing burden sharing scenarios with an input–output matrix. These scenarios are simulated under the shared responsibility principle to distribute restoration costs among stakeholders in the Seine estuary, France.     

The use–make framework and the derivation of functional forms in production theory

The use–make framework is employed to explain functional forms in production theory, including Cobb–Douglas and Leontief. Productivity and efficiency are interrelated by augmenting the framework with a linear program that determines the frontier output.     

Crime prediction by data-driven Green’s function method

We develop an algorithm that forecasts cascading events, by employing a Green’s function scheme on the basis of the self-exciting point process model. This method is applied to open data of 10 types of crimes happened in Chicago. It shows a good prediction accuracy superior to or comparable to the standard methods which are the expectation–maximization method and prospective hotspot maps method. We find a cascade influence of the crimes that has a long-time, logarithmic tail; this result is consistent with an earlier study on burglaries. This long-tail feature cannot be reproduced by the other standard methods. In addition, a merit of the Green’s function method is the low computational cost in the case of high density of events and/or large amount of the training data.     

Paired comparison models with age effects modeled as piecewise quadratic splines

We propose new models for analyzing pairwise comparison data, such as that relating to sports. We focus on changes in players’ strengths and the prediction of future results. Our models are based on the Thurstone-Mosteller and Bradley–Terry models, and make use of the time variation in the parameters. Furthermore, we apply our models to data from the Japanese traditional sport sumo, and analyze this data. The proposed models perform better than the standard Thurstone-Mosteller and Bradley–Terry models according to both the Akaike information criterion and the Brier score. We compare the proposed models in detail by focusing on individual sumo wrestlers.     

无穷范数松弛的低复杂度超奈奎斯特检测

超奈奎斯特(Faster-than-Nyquist,FTN)速率传输可以有效提高频谱效率，但这种非正交传输方式引入的严重码间串扰相应提高了接收端的处理难度。针对该问题，设计了一种基于循环成块传输的低复杂度检测算法。最优检测被建模为无约束的二元二次规划(Boolean Quadratic Program,BQP)问题，为了求解该NP-hard问题，采用无穷范数约束松弛原问题的非凸可行解集，并基于次梯度下降法提出松弛问题的有效优化算法。数值仿真结果表明，所提算法在误比特率(Bit Error Rate,BER)性能上优于频域均衡，且在可接受的性能损失范围内算法执行效率远高于理论最优的最大似然序列估计(Maximum Likelihood Sequence Estimation,MLSE)。