We study stock market reactions to the Brexit referendum on 23 June 2016 in order to assess investors’ expectations about the effects of leaving the European Union on the UK economy. Our results suggest that initial stock price movements were driven by fears of a cyclical downturn and by the...

This paper examines stock market integration between the ASEAN five and the US and China, respectively, over the period from November 2002 to March 2018. The linkages between both aggregate and financial sector stock indices (both weekly and monthly) are analysed using fractional integration and...

In this paper we show, using a Machine Learning Framework and utilising a substantial corpus of media articles on Brexit, confirmed evidence of co-integration and causality between the ensuing media sentiments and British currency. The novel contribution of this paper is that along with...

This paper uses a modelling framework which includes two singularities (or poles) in the spectral density function, one corresponding to the long-run (zero) frequency and the other to the cyclical (non-zero) frequency. The adopted specification is very general, since it allows for fractional...

We show that firm liability structure and associated cash flow matter for firm behavior, and that financial market participants price stocks accordingly. Looking at firm level stock price changes around monetary policy announcements, we find that firms that have more cash flow exposure see their...

How much and over what horizon do households adjust their consumption in response to stock market wealth shocks? We address these questions using granular data on spending and stock portfolios from a large bank and exploiting lottery-like variation in gains across investors with similar...

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...