The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

We examine the asymmetric impact of shocks to macroeconomic expectations and their underlying dispersion on equity risk premia across different market regimes. First, we rely on a two-state logit mixture vector autoregressive model and use Consensus Economics survey data on GDP growth,...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

We examine the asymmetric impact of shocks to macroeconomic expectations and their underlying dispersion on equity risk premia across different market regimes. First, we rely on a two-state logit mixture vector autoregressive model and use Consensus Economics survey data on GDP growth,...

We examine the asymmetric impact of shocks to macroeconomic expectations and their underlying dispersion on equity risk premia across different market regimes. First, we rely on a two-state logit mixture vector autoregressive model and use Consensus Economics survey data on GDP growth,...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Stock market recessions are often early warning signals for financial or economic crises. Hence, forecasting bear markets is important for investors, policymakers, and economic agents in general. In our two-step procedure, we first identify stock market regimes in the US using three different...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...