Price Discovery without Trading: Evidence from Limit Orders

Abstract

We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to changes in HFTs’ behavior. Consistent with adverse selection arising from faster reactions to public information, HFTs’ informational advantage is partially explained by public information.

Order Flow Segmentation, Liquidity and Price Discovery: The Role of Latency Delays

“…Work on high-frequency liquidity demanders finds that they may increase price efficiency (Carrion 2013) but also increase transaction costs (Chakrabarty et al 2014). Further studies find that HFTs improve price discovery through both liquidity supply (Brogaard, Hendershott, and Riordan 2015;Conrad, Wahal, and Xiang 2015) and demand (Brogaard, Hendershott, and Riordan 2014). Our paper complements these existing works by generating new empirical predictions regarding the impact of HFTs on price efficiency and trading costs when a delay is present.…”

Price Discovery of a Speculative Asset: Evidence from a Bitcoin Exchange

“…O'Hara (2015) argues that this assumption is increasingly detached from the reality of trading in today's high frequency trading world. Recent work has argued that informed traders can also utilize limit orders to exploit their information advantage (for theoretical work, see, e.g., Boulatov and George 2013;Ricco et al 2018; and references therein; for empirical evidence, see, e.g., Fleming et al 2018;Brogaard et al 2018;Cont et al 2014, among others.) As Cont et al (2014) (CKS2014) argue, trades are not sufficient to capture price movements given the sheer amount of limit order book events between any two trades.…”

Cross-Asset Market Order Flow, Liquidity, and Price Discovery

“…In addition to the lagged auto-correlation and lagged cross-correlation of returns as explanatory variables, the order flow variables of order imbalance, liquidity supply, liquidity demand, and volume are included. Brogaard, Hendershott, and Riordan (2019) show that despite their lower individual price impact, limit orders provide the majority of price discovery because they are far more numerous than market orders. They show that more aggressive orders have a higher price impact.…”

“…In Table 7.B we present a formulation closer to Brogaard et al (2019) by adding variables that account for the relative NBBO location of order flow activities. In the case of illiquid securities, which have spreads wider than 1 tick, the predictions for the impact of order flow positioning are straightforward.…”