In semiparametric models it is a common approach to under-smooth the nonparametric functions inorder that estimators of the finite dimensional parameters can achieve root-n consistency. The requirementof under-smoothing may result as we show from inefficient estimation methods or technical...

We consider the problem of estimating the fractional order of a L´evyprocess from low frequency historical and options data. An estimationmethodology is developed which allows us to treat both estimation andcalibration problems in a unified way. The corresponding procedureconsists of two steps:...

This paper presents a new approach to deriving default intensities from CDS or bond spreadsthat yields smooth intensity curves required e.g. for pricing or risk management purposes. Assumingcontinuous premium or coupon payments, the default intensity can be obtained by solving an...

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as trading costs in an electronic limit order book market. Using data from the Australian Stock Exchange we model 1-minsquared mid-quote returns, average trade sizes, number of...

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be...

Market option prices in last 20 years confirmed deviations from the Black and Scholes (BS) models assumptions, especially on the BS implied volatility. Implied binomialtrees (IBT) models capture the variations of the implied volatility known as \volatility smile". They provide a discrete...

We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

Independent component analysis (ICA) is a modern factor analysis tool developed in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...