Abstract
We examine the quantile connectedness of returns between the recently developed S&P 500 Twitter Sentiment Index and various asset classes. Rather than a mean-based connectedness measure, we apply quantile-connectedness to explore connectedness of means and, especially, extreme left and right tails of distributions. Using mean-based connectedness measures, the level of return connectedness between the twitter sentiment index and all financial markets is a modest 46%. However, when applying a novel quantile-based connectedness approach, we find that levels of tail-connectedness are much stronger, up to 82%, at extreme upper and lower tails. This suggests that the impact of sentiment on financial markets is much stronger during extreme positive/ negative sentiment shocks. Moreover, return connectedness measures are less volatile during extreme events. Net connectedness analysis shows that the Twitter sentiment index acts as a net transmitter of return spillovers, highlighting the leading role of investor sentiment on predicting other financial markets.