We extend recurrent neural networks to include several flexible timescales for each dimension of their output, which mechanically improves their abilities to account for processes with long memory or with highly disparate time scales. We compare the ability of vanilla and extended long short...

Prior to the onset of Covid-19 pandemic, Indian banks had witnessed worsening asset quality, reduced capital level and declining profits. In this respect, we try to develop an early warning model to assess the riskiness of a bank well in advance in order to prevent the bank falling into...

We examine the predictive value of expected skewness of oil returns for the realized volatility using monthly data from 1859:11 to 2023:04. We utilize a quantile predictive regression model, which is able to accommodate nonlinearity and structural breaks. In-sample results show that the...

This paper focuses on the predictive role of inflation and interest rates in forecasting stock returns. We report economically significant in-sample evidence that stock returns are predictable using cyclical components of inflation and interest rates. The out-of-sample analysis results show that...

This study examines how sell-side analyst’s earnings forecast behavior are influenced by peer analysts’ forecast. Based on uncertainty management theory, we propose that observing the deviation between analysts’ forecast and peers’ forecast will enhance analysts’ perception of...

The magnitude and sign of risk premiums provide relevant information on the structure of a given market. However, there is no consensus on commodity markets if there is a risk premium, and if so, if it is positive or negative. In addition, in recent years, there has been a discussion on the...

Density forecasts of euro area inflation are a fundamental input for a medium-term oriented central bank, such as the European Central Bank (ECB). We show that a quantile regression forest, capturing a general non-linear relationship between euro area (headline and core) inflation and a large...

We study the forecasting behavior of minority sell-side equity analysts. Distinct from the impact of cultural and geographic diversity, we demonstrate that, although minority analyst forecasts have lower accuracy, consistency in their forecasts generates stronger correlation between the...

The numerous literatures have recorded the closely connection across commodity and stock markets. This study empirically examines the role of 7 metal commodities (gold, silver, aluminum, plumbum, copper, zinc and nickel) in predicting G7 stock volatility. The results of individual factor...

We examine whether financial analysts understand the effect of unionization on firm earnings in the U.S. by examining a large panel dataset with firm-level unionization, adoptions of right-to-work (RTW) laws, and union certification elections. We find that forecast errors for unionized firms in...