This study proposed a deep neural network (DNN) model for the mortality rates of multiple populations, comprising the long short-term memory (LSTM) and convolutional neural network (CNN) models. As mortality trends are reflected for a long period and summarizing the complicated dependency of...

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...