Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability, and the development of the artificial intelligence industry. To provide investors with a more reliable reference in terms of artificial intelligence index investment,...

We study the predictability of stock returns using an iterative model-building approach known as quantile boosting. Examining alternative return quantiles that represent normal, bull and bear markets via recursive quantile regressions, we trace the predictive value of extensively studied...

Campbell and Shiller’s “accounting identity” implies that the log dividend-price ratio (LDPR) predicts either returns or dividend growths, but neither is significantly predictable, a well-known puzzle. Existence of the long-term mean LDPR is an important assumption behind the accounting...