The objective and subjective classification of unvoiced stop consonants in varying vowel contexts were studied. The objective classification was based on auditory feature vectors obtained by warped linear prediction (WLP) and vector autoregressive (VAR) models for parameter trajectories. In the case of known vowel the unvoiced consonants were classified 98-100% correctly based on the auditory s...

The mean-variance framework for portfolio selection should be revised when investor’s concern is the downside risk. This is especially true when the asset returns are not normal. In this paper, we incorporate value-at-risk (VaR) in portfolio selection and the mean-VaR framework is proposed. Due to the twoobjective optimization problem faced by the meanVaR framework, an evolutionary multi-object...

We provide a necessary and a sufficient condition on an individual’s expected utility function under which any zero-mean idiosyncratic risk increases cautiousness (the derivative of the reciprocal of the absolute risk aversion), which is the key determinant for this individual’s demand for options and portfolio insurance. JEL Classification Codes: D51, D58, D81, G11, G12, G13.

Money doesn’t seem to make us happy for reasons of social comparison and habituation. But does that necessarily mean that we would be better off doing something else instead? This paper suggests that the phenomena of comparison and habituation are actually found in a variety of economic and social activities, rendering policy conclusions more difficult. JEL Classification Codes: D01, D31, H00, ...

We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavy-tailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCH-like time series models. We propose a data-dependent method for the optimal block size selection and investigate its performance by means of a simulation study. JEL CLASSIFICATION NOS: C10,...

This paper presents a simulation study that assesses the finite sample performance of the subspace algorithm cointegration analysis developed in Bauer and Wagner (2002b). The method is formulated in the state space framework, which is equivalent to the VARMA framework, in a sense made precise in the paper. This implies applicability to VARMA processes. The paper proposes and compares six differ...

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MFVAR) approaches to model speci…cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients, whereas MF-VAR does not restrict the dynamics and therefore can su¤er from the curse of dimensionality. But if...