Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We study daily information shares for markets with partially overlapping trading hours. The established methodologies consider price discovery measures computed either for exactly overlapping trading hours or in sequential markets. In contrast, we develop a framework that exploits all price information generated during a full trading day in which any market can be open or closed at any time and propose a contribution-weighted information share. We apply this new method to the S&P 500 and NASDAQ-100 ETF and E-mini futures markets. It turns out that conventional information shares for the ETF markets are overestimated. E-mini futures are traded almost continuously throughout the trading day and process additional pricing relevant information when the ETF markets are closed.