A Direct Test of Methods for Inferring Trade Direction from Intra-Day Data

By Thomas J. Finucane. 2000

171 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/1c3e63ac34b87be391ccd4c38f4aa9f93635d3f2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Tarun Ramadorai
2. R. Huang
3. Andrew Ellul
4. Roni Michaely
5. K. Ellis
6. Pilar Corredor
7. Alexander Kurov
8. John Y. Campbell

In Finance

1. Tarun Ramadorai
2. Andrew Ellul
3. Roni Michaely
4. R. Huang
5. A. Lawrence
6. K. Ellis
7. Pilar Corredor
8. Alexander Kurov

In Management Science and Operations Research

1. Roni Michaely
2. K. Ellis
3. Pilar Corredor
4. Alexander Kurov
5. John Y. Campbell
6. Sandra Ferreruela
7. A. Schwartz
8. H. Stoll

Citations in the corpus

• Issues in Assessing Trade Execution Costs (2003, unknown): “Finucane (2000) does not directly evaluate the EMO method, but his results indicate that, while the tick test and the LR method have similar overall success rates, the LR algorithm works better than the tick test for trades executed at the quotes.”
• Investor Sentiment, Trading Behavior and Informational Efficiency in Index Futures Markets (2008, background): “Finucane (2000) shows that, when zero-tick trades are removed, the tick rule performs well as a trade classification algorithm.”
• Does herding affect volatility? Implications for the Spanish stock market (2012, result): “Finucane ( 2000 ) demonstrates how this method yields similar results to others.”
• A Trade-based Analysis of Momentum (2006, unknown): “For instance, Finucane (2000) argues that signed volume is more likely to be underestimated for larger trades. While unlikely, given the nature of the data, one cannot completely rule out that some of the systematic differences in trade imbalances across size groups and momentum portfolios could par”
• Tick Size, Bid-Ask Spreads, and Market Structure (2001, background): “13For studies on the accuracy of trade classification, see Lee and Radhakrishna (2000), OddersWhite (2000), Finucane (2000), Ellis, Michaely, and O’Hara (2000), and Bessembinder (2000).”
• Individual investors and financial disclosure (2013, background): “Specific to this concern, Finucane (2000) and Odders-White (2000) find that trades in illiquid stocks and small trades tend to be more frequently misclassified, and Campbell et al. (2009) provide evidence suggesting that simple size cutoffs used in previous studies are inaccurate and can lead to…”
• The Accuracy of Trade Classification Rules: Evidence from NASDAQ (2000, methodology): “In a recent paper, Finucane (2000) uses the TORQ database to test the accuracy of several classification algorithms (tick, quote and Lee-Ready).”
• IPO underpricing and after-market liquidity (2006, background): “Existing literature ( Finucane 2000; Ellis, Michaely, and O’Hara 2000b) shows that such algorithms have only limited success in classifying aftermarket trades (especially those executed within the best quotes) leading to biased estimates of effective spreads especially when high volumes are transac”
• Caught on tape: Institutional trading, stock returns, and earnings announcements (2009, background): “5 Finucane (2000) and Odders-White (2000) provide evidence that small trades and trades in highly liquid stocks tend to be more frequently misclassified.”