Intraday Price Discovery in Fragmented Markets

Quantile information share

“…Existing studies on price discovery often implicitly assumes that relative contributions of different markets or trading venues to the efficient price innovations to be constant over the sample period. As Ozturk et al () point out, this may not always hold true in empirical data with large samples due to changes in the characteristics of underlying exchanges and securities—such as increases in trade volume and electronization of trading mechanisms. Over the past decade, there have been empirical interests in studying time variation in measured shares of price discovery for individual markets.…”

“…For example, rather than defining information share within a reduced form time series model as the Hasbrouck and the CS measures, De Jong and Schotman’s () suggest a new measure which is defined directly within a structural time series model. This new measure has been applied and extended by Westerlund, Reese, and Narayan () and Ozturk, van der Wel, and van Dijk (). On the other hand, while IS focuses on innovation variance allocation, Sultan and Zivot () propose the price discovery share based upon volatility decomposition which is order‐invariant and unique.…”

When stock futures dominate price discovery

“…A closer examination suggests that a potential resolution of this puzzle may lie in noisy measurement and difficulties in estimation. Price discovery has traditionally been analysed as an average across stocks and over time, though if derivatives are used to trade information, these are likely to dominate spot prices only during periods of high information or HI (Brogaard, Hendershott, & Riordan, ; Chen & Gau, ; Ozturk, van der Wel, & van Dijk, ). For instance, when trading is fragmented across multiple exchanges with different microstructure in different time zones, the precisely synchronous data that are required to capture the true nature of price discovery are missing.…”

Estimation of Market Information Shares: A Comparison

“…For example, rather than defining information share within a reduced form time series model, De Jong and Schotman's () new measure is defined directly within a structural time series model. Ozturk, van der Wel, and van Dijk () take one step further and estimate a structural model with time‐varying parameters in state space to study intraday variation in the contribution to price discovery. Westerlund, Reese, and Narayan () incorporate this new measure with a factor analytical approach.…”

“…We assume that contributions of different markets to the efficient price innovations to be constant over the sample period. As Ozturk et al () point out, this may not always hold true in empirical data for long samples due to changes in the characteristics of exchanges and securities ‐ such as increases in trade volume and electronization of trading mechanisms.…”