Abstract We examine the linkages between dark and lit venues using a proprietary data set. We find that algorithmic trades for less liquid stocks lead to higher spreads and price impact, and correlated trading on the lit venues. Also, signed trades for these stocks predict future returns over the next 15 to 120 minutes. Trades for liquid stocks, trades by the dark venue brokerage desk, and members trading large blocks in negotiated crosses transmit less information to the lit venues. The results suggest that dark venues allow informed agents to trade strategically on both venues and facilitate the price discovery process. JEL Classifications: D53, G12, G28

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Abstract The ability to trade in dark pools without publicly announcing trading orders, concerns regulators and market participants alike. This paper analyses the information contribution of contemporary transaction in dark pools on future prices. The analysis is conducted by performing a nested and non-nested pairwise comparisons between GARCH models, with GED distributed disturbances. We compare several models using (log) scores based on the one-step ahead density forecasts. In each model, different proxies of activity in dark pools (volume and number of transactions) are included in the variance equation. Results indicate that the activity in dark pools conveys meaningful information for the one-step-ahead log-returns density forecast. Furthermore, it is to some extent meaningful to the price discovery. At last, traded volume and transactions in dark pools each provide distinct information.

Abstract The ability to trade in dark-pools without publicly announcing trading orders, concerns regulators and market participants alike. This paper analyzes the information contribution of dark trades to the intraday volatility process. The analysis is conducted by performing a GARCH estimation framework where errors follow the generalized error distribution (GED) and two different proxies for dark trading activity are separately included in the volatility equation. Results indicate that dark trades convey important information on the intraday volatility process. Furthermore, the results highlight the superiority of the proportion of dark trades relative to the proportion of dark volume in affecting the one-step-ahead density forecast. This project has received funding from the European Union 's Seventh Framework Programme (FP7-SSH/2007

This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal

Using a proprietary high frequency data set, we examine the information in trades originated by different types of traders. We find that the prevalence of informed trading in crossing networks is highest for illiquid stocks traded using algorithms against members of the crossing network, as measured by increased spreads and price impact measures on the quoting exchanges following crossing network transactions. Signed trades (motivated traders willing to pay for priority) on the crossing networks for this particular subset of firms also show the highest momentum going forward over the next 15 to 120 minutes. In contrast, trades for liquid stocks, trades by the crossing network brokerage desk, and members trading large blocks in negotiated crosses contain less information. These results suggest that while crossing networks provide a venue for large block trades to transact with little price impact, they also provide a venue for informed traders to trade, and this information appears to spill over and provide price discovery on the quoting exchanges.

This paper studies the workup protocol, a distinctive trading feature in the U.S. Treasury securities market that resembles a mechanism for discovering dark liquidity. We quantify its role in the price formation process in a model of the dynamics of price and segmented order flow induced by the protocol. We find that the dark liquidity pool generally contains less information than its transparent counterpart, and most of the former’s information value is due to workups expanding volume on the aggressive side. Moreover, we show that workups occur more frequently, but contribute less to price discovery relative to pre-workup trades, around volatile times. We also find that higher usage of workups is also associated with higher market depth, lower bid-ask spreads, and higher trading intensity. Collectively, the evidence suggests that workups are used more as a channel to encourage liquidity provision, than as a channel to hide private information.

We exploit a unique natural experiment—recent restrictions of dark trading in Canada—and proprietary trade-level data to analyze the effects of dark trading. Disaggregating two types of dark trading, we find that dark limit order markets are beneficial to market quality, reducing quoted, effective and realized spreads and increasing informational efficiency. In contrast, dark midpoint crossing systems do not benefit market quality. Our results support recent theory that dark limit order markets encourage aggressive competition in liquidity provision. We discuss implications for the regulation of dark trading and tick sizes. JEL classification: G14

In this section, I discuss institutional details of dark pools and dark liquidity in addition to that

We exploit a regulatory discontinuity in the minimum pricing increment, or tick size, to explore the mechanism by which tick size regulations benefit “dark ” trading venues at the expense of traditional stock exchanges and the associated effects on displayed liquidity and price discovery. Under Rule 612 of Regulation NMS, orders priced at or above $1.00 per share are required to be priced in penny increments, while all other orders can be quoted in subpennies. Using all trading data from 2011-2013, our regression discontinuity analysis of this $1.00 cut-off confirms that the penny tick size facilitates “queue-jumping ” of exchanges by dark pools; however, we show that the most significant portion of such queue-jumping occurs by means of trades at the midpoint of the NBBO—a form of trading that is generally considered to have significant benefits for institutional investors. Further, while queue-jumping in dark venues is associated with a significant decrease in the quantity of displayed liquidity on public exchanges, we show that the largest effect is on liquidity providers utilizing high frequency trading (HFT) algorithms, thus revealing an important inverse relation between dark trading and HFT. Finally, notwithstanding the drop in displayed liquidity associated with dark trading, a