A Test of International CAPM

We propose and implement a Wald test of the international capital asset pricing model. Ex post asset returns are regressed on asset supplies. CAPM requires that the matrix of coefficients from a regression of n rates of return on n asset supply shares be proportional to the covariance matrix of the residuals from those regressions. We test this restriction in the context of a model that aggregates all outside financial assets for each of ten countries. We do not find strong support for the restrictions of CAPM.

Tests of International CAPM with Time-Varying Covariances

We perform maximum likelihood estimation of a model of international asset pricing based on CAPM. We test the restrictions imposed by CAPM against a more general asset pricing model. The "betas" in our CAPM vary over time from two sources -- the supplies of the assets (government obligations of France, Germany, Italy, Japan, the U.K. and the U.S.) change over time, and so do the conditional covariances of returns on these assets. We let the covariances change over time as a function of macroeconomic data. We also estimate the model when the covariances follow a multivariate ARCH process. When the covariance of forecast errors are time-varying, we can identify a modified CAFM model with measurement error -- which we also estimate. We find that the model in which the CAPM restrictions are imposed (which involve cross-equation constraints between coefficients and the variances of the residuals) perform much better when variances are not constant over time. Nonetheless, the CAPM model is rejected in favor of the less restricted model of asset pricing.

Financial implications of the U.S. external deficit

Debts, External ; Dollar, American ; Deficit financing ; Investments, Foreign - United States

Conditional Mean-Variance Efficiency of the U.S. Stock Market

We apply the method of constrained asset share estimation (CASE) to test the mean-variance efficiency (MVE) of the stock market. This method allows conditional expected returns to vary in unrestricted ways, given investor preferences. We also allow conditional variances to follow an ARCH process. The data estimate reasonably the coefficient of relative risk aversion, though are unable to reject investor risk neutrality. We reject the restrictions implied by MVE, although changing conditional variances improve statistically upon measured market efficiency. We find that unrestricted asset-share and ARCH models help forecast excess returns. Once MVE is imposed, however, this forecasting ability disappears.

The impact of alternative routeing and packaging scenarios on carbon and sulphate emissions in international wine distribution.

There is a large body of research related to carbon footprint reduction in supply chains and logistics from a wide range of sectors; however the decarbonisation of freight transport is mostly explored from a single mode perspective and at a domestic/regional level. This paper takes into account a range of alternative transport modes, routes and methods with particular reference to UK wine imports from two regions: northern Italy and Southeast Australia. The research examines supply chain structures, costs and the environmental impact of international wine distribution to the UK. A number of options are evaluated to calculate the carbon footprint and sulphate emissions of alternative route, mode, method of carriage, and packaging combinations. The estimation of CO2e emissions incor- porates three main elements - cargo mass, distance and method of carriage; sulphate emis- sions are derived from actual ship routes, engine power and operational speeds. The bottling of wine either at source or close to destination is also taken into consideration. The key findings are: there are major differences between the environmental footprint of different routeing and packaging scenarios; the international shipping leg almost always has a much larger footprint than inland transport within the UK except in the hypothetical case of the rail shipments from Italy using flexitanks. With reference to sulphate, the low- est cost scenario among the sea maximizing options is also the sulphate minimising solution

A disaster response model driven by spatial-temporal forecasts

In this research, we propose a disaster response model combining preparedness and responsiveness strategies. The selective response depends on the level of accuracy that our forecasting models can achieve. In order to decide the right geographical space and time window of response, forecasts are prepared and assessed through a spatial–temporal aggregation framework, until we find the optimum level of aggregation. The research considers major earthquake data for the period 1985–2014. Building on the produced forecasts, we develop accordingly a disaster response model. The model is dynamic in nature, as it is updated every time a new event is added in the database. Any forecasting model can be optimized though the proposed spatial–temporal forecasting framework, and as such our results can be easily generalized. This is true for other forecasting methods and in other disaster response contexts

Risk interaction identification in international supply chain logistics: developing a holistic model

International supply chains can be severely disrupted by failures in international logistics processes. Therefore, an understanding of international logistics risks, or causes of failure, how these may interact with each other and how they can be mitigated are imperatives for the smooth operation of international supply chains. The purpose of this paper is to specifically investigate the interactions between international logistics risks within the prevailing structures of international supply chains and highlights how these risks may be inter-connected and amplified. A new dynamic supply chain logistics risk analysis model is proposed which is novel as it provides a holistic understanding of the risk event interactivity