The collection in Volume 43 Part A of Advances in Econometrics serves as a tribute to Professor M. Hashem Pesaran. Hashem is one of the most innovative, influential, and productive econometricians of his generation, with over 200 papers published in leading scientific journals to his credit...

This paper develops textual sentiment measures for China's stock market by extracting the textual tone of 60 million messages posted on a major online investor forum in China from 2008 to 2018. We conduct sentiment extraction by using both conventional dictionary methods based on customized word...

This research demonstrates the success of the new CDAR-family global market integration indices in the prediction of equity returns, which have not been thoroughly investigated in the past. We comprehensively investigate the predictive ability of the new CDAR-family indices by means of commonly...

We develop an easy-to-implement method for forecasting a stationary auto-regressive fractionally integrated moving average (ARFIMA) process subject to structural breaks with unknown break dates. We show that an ARFIMA process subject to a mean shift and a change in the long memory parameter can...

We explore the usefulness of combining opinion surveys with time-series data to forecast Japanese economy. We demonstrate that the businessmen's judgemental variables might summarize contemporaneous information beyond that of actual series. The combined models do yield substantially more...