We propose several tests for rational bubbles and investigate their power properties. The focus lies on the case where bubble detection is reduced to testing for a unknown change from a random walk to an explosive process. In simulations, a Chow-type break test exhibits the highest power and...

An important challenge of portfolio allocation arises when the (true) characteristics of returns' distribution are replaced by sample estimates. Such substitutions introduce estimation risk, which adds to traditional financial risk. I develop a new framework to provide a feasible optimal...

The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models since they require the updating of a function. The aim of this paper is to consider the situation of a large number n of individual measurements, called...

Most asset return series, especially those in high frequency, show high excess kurtosis and persistence in volatility that cannot be adequately described by the generalized conditional heteroscedastic (GARCH) model, even with heavy-tailed innovations. Many researchers have argued that these...

We consider a multidimensional, continuous-time model where the observation process is a diffusion with drift and volatility coefficients being modeled as continuous-time, finite-state Markov chains with a common state process. For the econometric estimation of the states for drift and...

We evaluate the informational content of the open limit order book by studying its role in explaining the volatility of the efficient price. We separate transitory (liquidity-driven) volatility from informational (efficient price-related) volatility using a dynamic state-space co-integration...

In this paper we address the issue of forecasting Value--at--Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two-scales realized volatility, realized kernel, as well as the daily range. We propose a dynamic model with a flexible trend...

This paper proposes a structural time-series model for the intraday price dynamics on fragmented financial markets. We generalize the structural model of Hasbrouck (1993) to a multivariate setting. We discuss identification issues and propose a new measure for the contribution of each market to...

In this paper, we show the effects that outliers have on estimation and inference for autoregressive conditional heteroskedasticity (ARCH) models. We propose for a wide class of ARCH models commonly estimated, an empirically tractable solution to this problem by replacing outliers with their...

We provide a Bayesian analysis of pair-copula constructions (PCCs) (Aas et al., 2009), which outperform many other multivariate copula constructions in modeling dependencies in financial data. We use bivariate t-copulas as building blocks in a PCC to allow extreme events in bivariate margins...