In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span...

A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as...

U.S. trading in non-U.S. stocks has grown dramatically. Round-the-clock, these stocks trade in the home market, in the U.S. marketand, potentially, in both markets simultaneously. We use a state space model to study 24-hour price discovery. As opposed to thestandard variance ratio'' approach,...

We investigate whether risk seeking or non-concave utility functions can help to explain the cross-sectional pattern0 of stock returns. For this purpose, we analyze the stochastic dominance efficiency classification of the value-weighted market portfolio relative to benchmark portfolios based on...

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source for longer horizon volatility forecasts. In this paper...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

This paper considers the effects of raising the cost of entry for a potential competitor on infinite-horizon Markov-perfect duopoly dynamics with ongoing demand uncertainty. All entrants serving the model industry incur sunk costs, and exit avoids future fixed costs. We focus on the unique...

We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...

Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional correlations processes, although with the drawback, when the number of financial returns series considered increases, that the parameterizations entail too many parameters.In general, the...