Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonline...

The class of conditionally heteroskedastic models known as ‘augmented ARCH’ encompasses most linear ‘ARCH’-type models found in the literature and, in particular, two basic ARCH variants for autocorrelated series: Engle (1982) explains conditional variance by lagged errors, Weiss (1984) also by lagged observations. The framework permits an evaluation of whether the restrictions evolving from th...

A new semiparametric proportional hazard rate model is proposed which extends standard models to include a dynamic speci cation. Two main problems are resolved in the course of this paper. First, the partial likelihood approach to estimate the components of a standard proportional hazard model is not available in a dynamic model involving lags of the log integrated baseline hazard. We use a dis...

This article contains two novelties. First, a unified framework for testing and evaluating the adequacy of an estimated autoregressive conditional duration (ACD) model is presented. Second, two new classes of ACD models, the smooth transition ACD model and the time-varying ACD model, are introduced and their properties discussed. New misspecification tests for the ACD class of models are introd...

Abstract This paper considers the parameter estimation problem of a first-order threshold autoregressive conditional heteroscedasticity model by using empirical likelihood method. We obtain ratio statistic based on estimating equation least squares and construct confidence region for parameters. Simulation studies indicate that method outperforms normal approximation-based in terms coverage pro...

Realized covariance matrices are often constructed under the assumption that richness of intra-day return data is greater than portfolio size, resulting in nonsingular matrix measures. However, when for example size large, assets suffer from illiquidity issues, or market microstructure noise deters sampling on very high frequencies, this relation not guaranteed. Under these common conditions, r...

In this article, we develop one- and two-component Markov regime-switching conditional volatility models based on the intraday range evaluate their performance in forecasting daily of S&P 500 Index. We compare with that several well-established return- range-based models, namely EWMA, GARCH, FIGARCH GARCH model, hybrid EWMA CARR model. in-sample goodness fit out-of-sample forecast using a compr...

As hurricanes approach landfall, there are several hazards for which coastal populations must be prepared. Damaging winds, torrential rains, and tornadoes play havoc with both the coast and inland areas; but, the biggest seaside menace to life and property is the storm surge. Wind fields are used as the primary forcing for the numerical forecasts of the coastal ocean response to hurricane force...