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Order Routing Method – The method of order routing on the 118,967,894 (96,323 trades) shares executed by the day traders. Island represents the 75,704,421 shares (62,987 trades) executed by bidding/offering on the Island ECN. Marketable limit represents the 38,644,960 shares (26,302 trades) executed by routing marketable limit orders to Nasdaq market participants based on their displayed quotes. Listed represents the 3,836,600 shares (5,046 trades) executed on the floor of the NYSE or AMEX exchanges. Other ECN's represents the 781,913 shares (1,988 trades) executed by bidding/offering on Electronic Communication Networks exclusive of Island.
Source publication
This paper investigates how profitable day trading occurs and how it impacts trading on Nasdaq stocks. Our paper analyzes a unique data set on 96,323 trades from the proprietary stock trading team of an U.S. day trading firm. We find profitable day traders trade when and where liquidity traders are present. That is, they prefer and are more profita...
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Citations
... Harris and Schultz (1998) study SOES bandits at two brokers.Garvy andMurphy (2002, 2005) analyze 15 and 1,386 day traders at one U.S. broker.Seasholes and Wu (2007) analyze the trades of ten active traders on the Shanghai Stock Exchange.Linnainmaa (2003) analyzes 7,686 Finnish day traders.Kuo and Lin (2013) analyze the performance of day traders on the Taiwan futures market in2007-2008. 9 Trading also occurred on Saturdays during most of our sample period. ...
Rational models claim “trading to learn” explains widespread excessive speculative trading and challenge behavioral explanations of excessive trading. We argue rational learning models do not explain speculative trading by studying day traders in Taiwan. Consistent with previous studies of learning, unprofitable day traders are more likely than profitable traders to quit. Consistent with models of overconfidence and biased learning (but not with rational learning), the aggregate performance of day traders is negative; 74% of day trading volume is generated by traders with a history of losses; and 97% of day traders are likely to lose money in future day trading.
Received: March 4, 2019; Editorial decision: May 16, 2019 by Editor: Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
... Though the SOES traders lose money almost as frequently as they make money, they earn a small average profit per trade. Similarly, Garvey and Murphy (2001) analyze the trading of 96,000 trades made by fifteen proprietary day traders-traders who use a firm's capital, pay no commissions, and profit share with the firm-at a direct access broker during three months in 2000. They too find these fifteen day traders are able to make money on their day trading activities primarily by placing limit orders on electronic crossing networks (ECNs) that are inside the current best quotes offered by NASDAQ dealers. ...
... Linnainmaa (2003) analyzes 7,686 investors who complete at least one roundtrip intraday transaction. These investors are far less active than those studied by Harris and Schultz (1998) and Garvey and Murphy (2001). The majority of these investors day trade on only one or two occasions and, in aggregate, these investors complete only 185,000 day trades over a two and a half year period (November 1998through May 2000. ...
... Harris and Shultz write that SOES bandits appear to profit by paying close attention to the market and reacting more quickly than most market-makers to changing market conditions. The day traders studied by Garvey and Ryan (2001) also appear to profit from reacting to market changes more quickly than most market makers. We speculate that the successful day traders who we observe profit by reacting more quickly than other investors to changing market conditions just as SOES bandits and the fifteen day traders studied by Garvey and Murphy profit from quick reactions. ...
In this research we investigate the behavior of noise traders and their impact on the market. We do this in an experimental market setting that allows us to determine not only how noise traders fare in a competitive asset market with other traders, but also how the equilibrium changes if a securities transactions tax ("Tobin tax") is imposed. We find that noise traders lose money on average: they do not engage in extensive liquidity provision, and their attempt to make money by trend chasing is unsuccessful as they lose most in securities whose prices experience large moves. Noise traders adversely affect the informational efficiency of the market: they drive prices away from fundamental values, and the further away the market gets from the true value, the stronger this effect becomes. With a securities transaction tax, noise traders submit fewer orders and lose less money in those securities that exhibit large price movements. The tax is associated with a decrease in market trading volume, but informational efficiency remains essentially unchanged and liquidity (as measured by the price impact of trades) actually improves. We find no significant effect, however, on market volatility, suggesting that at least this rationale for a securities transaction tax is not supported by our data.
We use a laboratory market to investigate the behavior of traders who lack informational advantages and have no exogenous
reason to trade. We find that these uninformed traders behave largely as irrational contrarian “noise traders,” trading against
recent price movements to their own detriment. The uninformed traders provide some benefits to the market: increasing market
volume and depth, while reducing bid-ask spreads and the temporary price impact of trades. However, their noise trading also
diminishes the ability of market prices to adjust to new information. A securities transaction tax reduces uninformed trader
activity, but it reduces informed trader activity by approximately the same amount; as a result, the tax does not alter the
impact of noise trading on the informational efficiency of the market.
