We provide a new framework for modeling trends and periodic patterns in high-frequency financial data. Seeking adaptivity to ever-changing market conditions, we enlarge the Fourier flexible form into a richer functional class: both our smooth trend and the seasonality are non-parametrically...

The episodes of stock market crises in Europe and the U.S.A.since the year 2000,and the fragility of the international stock markets,have sparked the interest of researchers in understanding and in modeling the markets’ rising volatilities in order to prevent against crises.Portfolio managers...

This paper investigates the properties of Dickey-Fuller tests for seasonally unadjusted quarterly data when deterministic seasonality is present but it is neglected in the test regression. While for the random walk case the answer is straightforward, an extensive Monte Carlo study has to be...

The episodes of stock market crises in Europe and the U.S.A. since the year 2000,and the fragility of the New Technology sector after the explosion of the speculative bubble,have sparked the interest of researchers in understanding and in modeling this market’s high volatility to prevent...

Copulas have enjoyed increased usage in many areas of econometrics, including applications with discrete outcomes. However, Genest and Nešlehová (2007) present evidence that copulas for discrete outcomes are not identified, particularly when those discrete outcomes follow count distributions....

This paper builds on Kočenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε- ranges new critical values for various lengths of the data sets are introduced and through...

The structural vector autoregression (SVAR) has become a central tool for research in empirical macroeconomics. Because the vast majority of these models are exactly identified, researchers have traditionally relied upon the informal use of prior information to compare alternative...

We study the impact of the system dimension on commonly used model selection criteria (AIC,BIC, HQ) and LR based general to specific testing strategies for lag length estimation in VAR's. We show that AIC's well known overparameterization feature becomes quickly irrelevant as we move away from...

This paper extends and generalizes the BDS test presented by Brock, Dechert, Scheinkman, and LeBaron (1996). In doing so it aims to remove the limitation of having to arbitrarily select a proximity parameter by integrating across the correlation integral. The Monte Carlo simulation is used to...

To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a...