Stock market prediction (SMP) is challenging due to its uncertainty, nonlinearity, and volatility. Machine learning models such as recurrent neural networks (RNNs) have been widely used in SMP and have achieved high performance in terms of "minimum error". However, in the context of SMP, using...

The new impairment reporting standards require banks to move from incurred loss models to sophisticated macroeconomic based expected credit loss models for current impairment estimation. While the impairments estimation is mainly focused on business as usual macroeconomic projections there is a...

We investigate the impact of conditional conservation on the ability of accruals and its components to predict future cash flows. We first demonstrate that conditional conservatism has increased over the period from 1988 to 2013 due to an increase in timely loss recognition and asymmetric timely...