The forecast combination puzzle refers to the finding that a simple average forecast combination outperforms more sophisticated weighting schemes and/or the best individual model. The paper derives optimal (worst) forecast combinations based on stochastic dominance (SD) analysis with...

We establish the consistency and asymptotic normality for a class of estimators that are linear combinations of a set of v n- consistent estimators whose cardinality increases with sample size. A special case of our framework corresponds to the conditional moment restriction and the implied...

The present study aimed at investigating the existence of long memory properties in ten developed stock markets across the globe. When return series exhibit long memory, the series realizations are not independent over time and past returns can help predict future returns, thus violating the...

We derive simple algebraic expressions for score tests of serial correlation in the levels and squares of common and idiosyncratic factors in static factor models with (semi) parametrically specified elliptical distributions even though one must generally compute the likelihood by simulation. We...

This paper develops maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we estimate conditional expectations nonparametrically in...

A new way of constructing efficient semiparametric instrumental variableestimators is proposed. The method involves the combination of a large number ofpossibly inefficient estimators rather than combining the instruments into anoptimal instrument function. The consistency and asymptotic...

This paper develops methodology for nonparametric estimation of apolarization measure due to Anderson (2004) and Anderson, Ge, and Leo(2006) based on kernel estimation techniques. We give the asymptoticdistribution theory of our estimator, which in some cases is nonstandard dueto a boundary...

We propose a multivariate generalization of the multiplicative volatility model ofEngle and Rangel (2008), which has a nonparametric long run component and aunit multivariate GARCH short run dynamic component. We suggest variouskernel-based estimation procedures for the parametric and...

In this note we propose a simple method of measuring directional predictability and testing for the hypothesis that a given time series has no directional predictability. The test is based on the correlogram of quantile hits. We provide the distribution theory needed to conduct inference,...