Using state-of-the-art recurrent neural network architectures, this study attempts to predict credit default swap risk premia for BR[I]CS countries as accurately as possible. In the time series setting, these recurrent neural networks are ELMAN, NARX, GRU, and LSTM RNNs, considering local and...

The COVID-19 pandemic has adversely influenced economies around the world through supply and demand channels. The increasing uncertainty and the decreasing demand due to the strict social measures of the government to cushion the spread of the pandemic have transformed COVID-19 from a health...

Size and book-to-market equity (BM) strongly explain stock returns’ cross section; the risk they capture is the relative distress of small and value stocks. This study examines the default risk’s pricing power, measured by U.S. firms’ market-revealed credit-default-swap premiums...

Fama and French (1992, 1993, 1995 and 1996) declare that size and book-to-market equity (BM) have strong explanatory power for the cross-section of stock returns, and the risk captured by size and BM is the relative distress of small stocks and value stocks. Firstly, this study examines the...