This paper investigates the nonlinearity in the effects of news shocks about technological innovations. In a maximally flexible logistic smooth transition vector autoregressive model, state-dependent effects of news shocks are identified based on medium-run restrictions. We propose a novel...

We extend the event study methodology into a richer and more dynamic environment by including time-varying parameters. Under the Bayesian framework, useful to update relevant information in a sequential learning mechanism, we use the Kalman filter to consider time dependent parameters, and we...

The stock market is volatile and volatility occurs in clusters, price fluctuations based on sentiment and news reports are common. A trader uses a wide variety of publicly available information to forecast the marketing decision. This paper proposes an advice to traders for stock trading using...