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...

We investigate price duration variance estimators that have long been neglected in the literature. We show i) how price duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and ii) how they are affected by a)...

We propose a hybrid penalized averaging for combining parametric and non-parametric quantile forecasts when faced with a large number of predictors. This approach goes beyond the usual practice of combining conditional mean forecasts from parametric time series models with only a few predictors....

Parameter shrinkage applied optimally can always reduce error and projection variances from those of maximum likelihood estimation. Many variables that actuaries use are on numerical scales, like age or year, which require parameters at each point. Rather than shrinking these towards zero,...

This note studies robust estimation of the autoregressive (AR) parameter in a nonlinear, nonnegative AR model driven by nonnegative errors. It is shown that a linear programming estimator (LPE), considered by Nielsen and Shephard (2003) among others, remains consistent under severe model...

We obtain the link between the Laplace transform of the price process and that of the volatility process in the context of a Brownian semi-martingale model. Relying on this result, we build a new nonparametric estimator of the instantaneous volatility which efficiently reconstructs the...

I develop a semiparametric minimum distance from independence estimator for a nonseparable instrumental variables model. An independence condition identifies the model for many types of discrete and continuous instruments. The estimator is taken as the parameter value that most closely satisfies...

In this paper, a semiparametric single-index model is investigated. The link function is allowed to be unbounded and has unbounded support that answers a pending issue in the literature. Meanwhile, the link function is treated as a point in an infinitely many dimensional function space which...

We introduce a simple nonparametric approach to compute impulse response functions. We first search for clusters of recurrent patterns of observations resembling two sets of given initial conditions, one of which contains the impact effect of the structural shock of interest. Then, to trace out...

We propose an observation-driven time-varying SVAR model where, in agreement with the Lucas Critique, structural shocks drive both the evolution of the macro variables and the dynamics of the VAR parameters. Contrary to existing approaches where parameters follow a stochastic process with random...