We propose a semi-parametric approach to investigate whether co-dependence across markets increase in periods of extreme returns. Given that returns on one market fall in the extreme tail of their own distribution, we compute the conditional probability that returns on another market will also...

This paper introduces a nonparametric estimator for tail dependence in the constant conditional correlation GARCH framework, in contrast to existing estimators that impose the iid assumption. So long as stationarity is satisfied, the difference between the distribution of the tail dependence...

This paper examines stock market behaviour in India, Sri Lanka, Pakistan, and Bangladesh employing unit root tests, autocorrelation tests and spectral analysis. Evidence suggests that all markets exhibit a random walk. The multivariate cointegration tests based upon the Johansen Juselius (1988,...

This paper studies subsampling hypothesis tests for panel data that are possibly nonstationary, and cross-sectionally correlated and cross-sectionally cointegrated. The tests include panel unit root and cointegration tests as special cases. The number of cross-sectional units in the panel data...

This paper analyses empirically the relationship between money and output in Peru, based on an orthogonal decomposition of series by timescales obtained using wavelets, following Ramsey and Lampart (1998). Specifically, we propose the application of wavelet filtering to analyze cointegrating...

This article presents a non-Markovian regime switching model in which the regime states depend on the sign of an autoregressive latent variable. The magnitude of the latent variable indexes the `strength' of the state or how deeply the system is embedded in the current regime. The autoregressive...

This paper presents a rigurous framework for evaluating alternative forecasting methods for Chilean industrial production and sales. While nonlinear features appear to be important for forecasting the very short term, simple univariate linear models perform about as well for almost every...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors should be serially uncorrelated at the single period horizon with...

This paper derives results for the temporal aggregation of multivariate GARCH processes in the general vector specification. It is shown that the class of weak multivariate GARCH processes is closed under temporal aggregation. Fourth moment characteristics turn out to be crucial for the low...

Under the squared error loss, the optimal forecast is the conditional mean, and the one-step forecast error is a martingale difference (MD). The one-step forecast error forms the conditional moment condition obtained from the loss derivative with respect to the forecast. Similarly, under a...