Barbara Rindi

Diving Into Dark Pools

This paper examines unique data on dark pool activity for a large cross-section of US stocks in 2009. Dark pool activity is concentrated in large firms, stocks with high share volume, high price, low spreads, high depth, and low short-term volatility. NASDAQ (AMEX) stocks have significantly higher (lower) dark pool activity than NYSE stocks controlling for size, share volume, and price. For a given stock, dark pool activity is significantly higher on days with higher share volume, higher depth, and lower intraday volatility. Dark pool activity is significantly lower for days with larger order imbalances relative to share volume and larger absolute returns. We find no evidence supporting the hypothesis that dark pool activity has a detrimental effect on market quality.

The Quality of the Italian Treasury Bond Market, Asymmetric Information and Transaction Costs

This paper analyzes the microstructure of the Italian secondary bond market and of the effects of the 1994 reform and of the introduction of anonymity in 1997. Based on a microstructure model of price formation, we evaluate the relevance of asymmetric information and other microstructure effects, by estimating the VAR representation of the model. We find that market quality improves over time, which we interpret as resulting from the 1994 reform. This is captured both by decreased first order return autocorrelation and by improvement of our market quality indicators. The introduction of anonymity substantially reduces order fragmentation by investors trying to avoid free-riding by less sophisticated traders. No significant evidence of asymmetric information is found.

Dark Pool Trading Strategies, Market Quality and Welfare

We model a financial market where traders have access both to a fully transparent limit order book (LOB) and to an opaque Dark Pool (DP). When a DP is introduced to a LOB market,orders migrate to the DP from the LOB, but overall trading volume increases. Moreover, inside quoted depth in the LOB decreases, but quoted spreads tend to narrow in deep books and widen in shallow ones. DP market share is higher when LOB depth is high, when LOB spread is narrow, when the tick size is large and when traders seek protection from price impact. When depth decreases on one side of the LOB, liquidity is drained from the DP. When Flash orders provide select traders with information about the state of the DP, more orders migrate from the LOB to the DP but overall market quality improves.

Sub-Penny and Queue-Jumping

Sub-Penny Trading (SPT) is a form of dark trading that allows traders to undercut displayed liquidity. We distinguish between SPT that is queue jumping (QJ) and mid- crossing (MID) and find that QJ is higher for NASDAQ than NYSE stocks. Consistently with Buti, Rindi, Wen and Werner (2013), QJ is positively related to depth and negatively related to stock price. We also find that QJ is associated with improved lit market quality, especially for large capitalization stocks. Sub-penny quotes are allowed for stocks priced below

Trading Fees and Intermarket Competition

1.00, and we use this fact to show that QJ increases, the spread improves but depth deteriorates as the price of a stock crosses from above to below (

Information, Liquidity, and Dynamic Limit Order Markets

1.00).

Informed Traders as Liquidity Providers: Anonymity, Liquidity and Price Formation

We model an order book with liquidity rebates (make fees) and trading fees (take fees) that faces intermarket competition, and use the models insights to explain changes in market quality and market shares following changes in make-take fees. As predicted by our model, we document that fee changes by one venue affect market quality and market shares for all venues that compete for order flow. Furthermore, we document cross-sectional differences in changes in market quality and market shares following a simultaneous decrease in both make and take fees consistent with traders in large (small) capitalization stocks being more sensitive to the change in make (take) fees.

The Microstructure of Financial Markets

This paper describes price discovery and liquidity provision in a dynamic limit order market with asymmetric information and non-Markovian learning. Investors condition on information in both the current limit order book and also, unlike in previous research, on the prior order history when deciding whether to provide or take liquidity. Our analysis shows that the information content of the prior order history can be substantial. Surprisingly, the information content of equilibrium orders can differ from order direction and aggressiveness. JEL classiffication: G10, G20, G24, D40. Keywords: Limit order markets, asymmetric information, liquidity, market microstructure.