We revisit the apparent historical success of technical trading rules on daily prices of the Dow Jones index. First, we use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it is more powerful and not restricted only to the best...

We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We justify block bootstrap approaches to achieve valid inference in a time series setting. The test statistics are computed...

We propose a class of new robust GMM tests for endogenous structural breaks. The tests are based on supremum and average statistics derived from robust GMM estimators with a bounded influence function. They imply a bounded linearized asymptotic bias of size and power under local model...

A large literature studies the predictability of stock returns by other lagged nancialvariables in a predictive regression setting. A common feature of widely used testingprocedures is a failing robustness, which may lead to misleading conclusions determinedby the particular features of a small...

We provide a convenient econometric framework for the analysis of nonlinear dependence in financial applications. We introduce models with constrained nonparametric dependence, which specify the conditional distribution or the copula in terms of a one-dimensional functional parameter. Our...

This paper proposes a Kolmogorov-type test for the shortfall order (also known in the literature as the right-spread or excess-wealth order) against parametric alternatives. In the case of the null hypothesis corresponding to the Negative Exponential distribution, this provides a test for the...

Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number ofhedge funds from a large universe of candidate funds. We analyse whether such a selectioncan be successfully achieved by looking at the track records of the available funds alone,using advanced statistical...

Macroeconomic time series often involve a threshold effect in theirARMA representation, and exhibit long memory features. In this paperwe introduce a new class of threshold ARFIMA models to account forthis. The threshold effect is introduced in the autoregressive and/or thefractional integration...

We introduce a new approach on shape preserving estimation of cumulative distribution functions and probability density functions using the wavelet methodology for multivariate de- pendent data. Our estimators preserve shape constraints such as monotonicity, positivity and integration to one,...