This paper studies the predictive performance of multivariate models at forecasting the (excess) returns of portfolios mimicking the Market, Size, Value, Momentum, and Low Volatility factors isolated in asset pricing research. We evaluate the accuracy of the point forecasts of a number of linear...

Purpose This study aims to use gray models to predict abnormal stock returns. Design/methodology/approach Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the...

This paper provides a new technique for representing discrete time nonlinear dynamic stochastic time invariant maps. Using this new series representation, the paper augments the usual solution strategy with an additional set of constraints thereby enhancing algorithm reliability. The paper also...