Bayesian time series analysis of periodic behaviour and spectral structure

Analysis, model selection and forecasting in univariate time series models can be routinely carried out for models in which the model order is relatively small. Under an ARMA assumption, classical estimation, model selection and forecasting can be routinely implemented with the Box–Jenkins time domain representation. However, this approach becomes at best prohibitive and at worst impossible when the model order is high. In particular, the standard assumption of stationarity imposes constraints on the parameter space that are increasingly complex. One solution within the pure AR domain is the latent root factorization in which the characteristic polynomial of the AR model is factorized in the complex domain, and where inference questions of interest and their solution are expressed in terms of the implied (reciprocal) complex roots; by allowing for unit roots, this factorization can identify any sustained periodic components. In this paper, as an alternative to identifying periodic behaviour, we concentrate on frequency domain inference and parameterize the spectrum in terms of the reciprocal roots, and, in addition, incorporate Gegenbauer components. We discuss a Bayesian solution to the various inference problems associated with model selection involving a Markov chain Monte Carlo (MCMC) analysis. One key development presented is a new approach to forecasting that utilizes a Metropolis step to obtain predictions in the time domain even though inference is being carried out in the frequency domain. This approach provides a more complete Bayesian solution to forecasting for ARMA models than the traditional approach that truncates the infinite AR representation, and extends naturally to Gegenbauer ARMA and fractionally differenced models.     

半导体照明产品检测实验室建设及展望

基于半导体照明灯具的特点,结合目前半导体照明产品检测的实际情况,从光、色、电、寿命及安全性等方面介绍了半导体照明产品检测实验室的建设方案,包括系统的功能、组成、基本的检测原理和方法等。     

LOD技术在三维地形图实时可视化中的应用研究

随着计算机科学、计算机图形学和现代测绘科学的迅速发展,三维数字地形图的研究与实现越来越成为人们研究和关注的热点,要实现三维地形图的实时可视化,应用LOD技术的研究又是非常必要的,如何针对大数据量三维地形图建立不同细节层次的模型和优化其算法又成为要研究关键技术。本文重点对LOD技术的原理、分类和应用进行比较与探讨。     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.     

On break-even correlation: the way to price structured credit derivatives by replication

We consider the pricing of European-style structured credit pay-off under the Gaussian Copula Model (GCM). When no sudden jump-to-default events occur, the perfect replication of these pay-offs under the GCM is obtained if and only if the underlying single-name credit spreads follow a particular family of dynamics and if the pricing parameters are given by so-called ‘break-even’ correlations. We exhibit a class of Merton-style models that are consistent with this result. We calculate break-even correlations explicitly to price nth-to-default baskets under the GCM. Finally, we illustrate the usefulness of this concept as a relative-value tool.     

风险价值及压力测试在采购策略中的应用

首先分析了供应链采购风险管理的重要性,然后分别介绍了VaR和压力测试这两种风险测度方法,并在此基础上建立了采购风险度量模型,为制定科学的采购策略提供了量化的决策依据。     

土地供给市场化后的出让总收入及预测模型设计

国有土地出让招拍挂制度的实施开启了我国土地供给的市场化,更公平、透明地揭示了土地的市场价值,同时为地方政府带来了一定的城市发展建设资金。然而,现行财税制度却加剧了地方财政对土地出让收入的依赖,由此滋生的种种问题导致土地出让收入成为舆论焦点。本文采用格兰杰因果分析、脉冲检验、自回归滞后分布模型等方法,通过实证研究寻找宏观经济变量与土地出让总收入的相互影响及数量关系,并据此推导建立土地出让收入模型,预测土地出让收入的数量及变化趋势,为各界真正了解土地财政以及政府把握土地供给与经济发展之间的关系提供一个理论途径。     

General equilibrium impact of an energy-saving policy in the public sector

We analyse a disregarded environmental policy instrument: a switch in government expenditure away from energy (or other natural resources) and toward a composite good which includes energy-saving expenditure. We first develop two variants of an analytical general equilibrium model. A composite good is produced with constant returns to scale, and energy is imported or produced domestically with diminishing returns, yielding a differential rent to its owners. The government purchases energy and composite goods from private firms. Such a policy unambiguously increases employment. It also raises private consumption and welfare under two conditions: (i) it is not too costly and (ii) the initial share of the resource is smaller in public spending than in private consumption, or the difference is small enough. We then run numerically a model featuring both importation and domestic production of energy (oil, gas and electricity), for the OECD as a whole. Simulations show that employment, welfare and private consumption rise. We provide magnitudes for different parameter values. Earlier versions of this paper have benefited from conference participants at the European Council for an Energy-Efficient Economy, International Society for Ecological Economics World Congress, CIRED seminar and EUREQua environmental economics seminar. We especially thank Michèle Sadoun and two anonymous referees. The usual disclaimer applies.     

Enhancing mental models,analogical transfer,and performance in strategic decision making

Recent research suggests that managers often make strategic decisions in novel situations by utilizing past experiences to reason by analogy. However, there is substantial evidence that decision makers often fail to identify and apply knowledge about one situation to a similarly structured situation. Two experimental studies investigated the mechanisms impacting knowledge transfer from one managerial situation (the source) to an analogous situation. The results show that exposure to variation in the source situation improves transfer performance. Variation decreases performance in the short term but improves learning and increases analogical transfer. Higher performance on and systematic search of the source situation also increase transfer performance. These results yield important implications for enhancing analogical transfer in strategic decision making and for future research on reasoning by analogy. Copyright © 2012 John Wiley & Sons, Ltd.     

An Evaluation of Contingent Claims Using the CKLS Interest Rate Model: An Analysis of Australia, Japan, and the United Kingdom

In this paper we apply a new efficient numerical method for valuing default free bonds and contingent claims within the CKLS interest rate model. Using historical parameter estimates of the CKLS model for Australia, Japan, and the United Kingdom we compare implied bond and contingent claim prices. Our results indicate that default free bond prices and contingent claim prices are sensitive to the underlying interest rate model used.