In this paper the authors set out to date-stamp periods of US housing price explosivity for the period 1830–2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and...

The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock market returns. The Nigerian stock market logarithmic returns time series was tested for the presence of memory using the Hurst coefficient before the models were trained. The...

We adapt the multifractal random walk model by Bacry et al. (2001) to realized volatilities (denoted RV-MRW) and take stock of recent theoretical insights on this model in Duchon et al. (2012) to derive forecasts of financial volatility. Moreover, we propose a new extension of the binomial...