Due to the complexity of economic system and the interactive effects between all kinds of economic variables and foreign trade, it is not easy to predict foreign trade volume. However, the difficulty in predicting foreign trade volume is usually attributed to the limitation of many conventional forecasting models. To improve the prediction performance, the study proposes a novel kernel-based en...

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to ...

One of the most challenging problems in econometrics is the prediction of turning points in financial time series. We compare ARMAand Vector-Autoregressive (VAR-) models by examining their abilities to predict turning points in monthly time series. An approach proposed by Wecker[1] and enhanced by Kling[2] forms the basis to explicitly incorporate uncertainty in the forecasts by producing proba...

Evolutionary processes are routinely modelled using 'ideal' Wright-Fisher populations of constant size N in which each individual has an equal expectation of reproductive success. In a hypothetical ideal population, variance in reproductive success (V(k)) is binomial and effective population size (N(e)) = N. However, in any actual implementation of the Wright-Fisher model (e.g., in a computer),...

Cointegration has different theoretical implications for forecasting. Several empirical studies have compared the out of sample forecasting performance of cointegrted VECMs against unrestricted VARs in levels and in differences. The results of these studies have been generally mixed and inconclusive. This paper provides a comprehensive review over the subject, and also examines the effects...

This thesis presents work concerning the analysis of behaviour specific facial motion and its automatic synthesis. Psychology research has shown that facial motion provides important cues to the human visual system for recognition of emotion, identity and gender. Similarly, in Computer Vision facial motion information has been used in face and facial expression recognition. However, the fact th...

Technologies such as aerial photogrammetry allow production of 3D topographic data including complex environments such as urban areas. Therefore, it is possible to create High Resolution (HR) Digital Elevation Models (DEM) incorporating thin above ground elements influencing overland flow paths. Even though this category of big data has a high level of accuracy, there are still errors in measur...

In financial market risk measurement, Value-at-Risk (VaR) techniques have proven to be a very useful and popular tool. Unfortunately, most VaR estimation models suffer from major drawbacks: the lognormal (Gaussian) modeling of the returns does not take into account the observed fat tail distribution and the non-stationarity of the financial instruments severely limits the efficiency of the VaR ...

Vector Autoregression Models (VAR) are widely used by researchers to capture the linear interdependencies among multiple time series. We propose a novel method called Clustered VAR (CVAR) to identify components of the data generated by a mixture of K VAR processes. By applying a CVAR model to a consumer-level time series dataset on shopping behavior at a retailer, we segment consumers based on ...