A typical stock adjustment model is a partial adjustment process to maintain simultaneously the two kinds of equilibrium relationships: a flow-flow relationship and a stock-flow relationship. We show that the stock adjustment model is an error correction model of 'multicointegrated' time series,...

A unified framework for various nonparametric kernel regression estimators is presented, based on which we consider two nonparametric tests for neglected nonlinearity in time series regression models. One of them is the goodness-of-fit test of Cai, Fan, and Yao (2000) and another is the...

The artificial neural network (ANN) test of Lee et al. (Journal of Econometrics 56, 269–290, 1993) uses the ability of the ANN activation functions in the hidden layer to detect neglected functionalmisspecification. As the estimation of the ANN model is often quite difficult, LWG...

The literature on excess return prediction has considered a wide array of estimation schemes, among them unrestricted and restricted regression coefficients. We consider bootstrap aggregation (bagging) to smooth parameter restrictions. Two types of restrictions are considered: positivity of the...

To find forecasts that are closest to Greenbook forecast from the Survey of Professional Forecasters, this paper looks for SPF cross-sectional percentile forecasts that are not encompassed by Greenbook forecast under Greenbook's loss preference, which exhibits time-varying asymmetry. To evaluate...

The literature on excess return prediction has considered a wide array of estimation schemes, among them unrestricted and restricted regression coefficients. We consider bootstrap aggregation (bagging) to smooth parameter restrictions. Two types of restrictions are considered: positivity of the...