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Financial Transaction Taxes and the Informational Efficiency of Financial Markets: A Structural Estimation
We develop a new methodology to estimate the impact of a financial transaction tax (FTT) on financial market outcomes. In our sequential trading model, there are price-elastic noise and informed traders. We estimate the model through maximum likelihood for a sample of sixty New York Stock Exchange (NYSE) stocks in 2017. We quantify the effect of introducing an FTT given the parameter estimates. An FTT increases the proportion of informed trading, improves information aggregation, but lowers trading volume and welfare. For some less-liquid stocks, however, an FTT blocks private information ...
Working Paper
Microstructure Invariance in U.S. Stock Market Trades
This paper studies invariance relationships in tick-by-tick transaction data in the U.S. stock market. Over the 1993?2001 period, the estimated monthly regression coefficients of the log of trade arrival rate on the log of trading activity have an almost constant value of 0.666, strikingly close to the value of 2/3 predicted by the invariance hypothesis. Over the 2001?14 period, the estimated coefficients rise, and their average value is equal to 0.79, suggesting that the reduction in tick size in 2001 and the subsequent increase in algorithmic trading resulted in a more intense order ...
Working Paper
Who is Minding the Store? Order Routing and Competition in Retail Trade Execution
Using 150,000 actual trades, we study the U.S. equity retail broker-wholesaler market, focusing on brokers’ order routing and competition among wholesalers. We document substantial and persistent dispersion in execution costs across wholesalers within brokers. Despite this, many brokers hardly change their routing and even consistently send more orders to the more expensive wholesalers, although there is considerable variation among brokers. We also document a case where, after a new wholesaler enters, existing wholesalers significantly reduce their execution costs. Overall, our findings ...
Working Paper
Machines vs. Machines: High Frequency Trading and Hard Information
In today's markets where high frequency traders (HFTs) act as both liquidity providers and takers, I argue that information asymmetry induced by liquidity-taking HFTs' use of machine-readable information is important. This particular type of information asymmetry arises because some machines may access the information before other machines or because of randomness in relative speed. Applying a novel statistical approach to measure HFT activity through limit order book data and using a natural experiment of index inclusion, I show that liquidity-providing HFTs supply less liquidity to stocks ...
Working Paper
Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers
We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTFs), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of ...
Working Paper
Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book
An extensive empirical literature documents a generally negative correlation, named the ?leverage effect,? between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect ? i.e. a relation between contemporaneous jumps in prices and volatility ? in high-frequency data with market microstructure noise. We present local tests and estimators for price jumps and volatility jumps. Five years of transaction data from ...