شناسایی معامله گران آگاه در بازارهای آتی

We use daily positions of futures market participants to identify informed traders. These data contain 8,921 unique traders. We identify between 94 and 230 traders as overnight informed and 91 as intraday informed with little overlap. Floor brokers/traders are over-represented in the overnight informed group. The intraday informed group is dominated by managed money traders/hedge funds and swap dealers, with commercial hedgers under-represented. We find that characteristics such as experience, position size, trading activity, and type of positions held offer significant predictive power for who is informed. An analysis of daily trader profits confirms that we select highly profitable traders.

Informed traders are an essential feature of market microstructure models, but there is little research that establishes who is an informed trader.2 Most researchers detect the presence of informed traders from price responses to order flow. Because permanent price responses signal informed trades, consistent profits gained from positions or trading activity provide an indicator of who is informed. However, data limitations make trader identities unavailable to most previous studies so the characteristics and profits of the informed are generally unknown.3 In this paper, we identify informed traders, those whose actions show they hold valuable short-term price information. Our methods separate these traders from thousands of other participants whose profits (if any) arose due to luck in the sampling process. From the subset we identify as informed, we use inverse regression techniques to analyze their characteristics and to examine how their net trading and end-of-day positions set them apart from other participants. This approach complements that of Menkhoff and Schmeling (2010), who relate price impacts from trades in the dollar/rouble FX market to trader and market characteristics such as order size, timing, total volume, and origin.4 We examine data on trader positions from 2000 to mid-2009 for 12 futures markets. We find that traders who hold information about intraday price changes are not the same as those who hold information about the next day's price—the overnight informed. Depending on the test and reference price, we identify from 94 to 230 traders as overnight informed and 91 traders as intraday informed out of 8,921 unique traders. These two types of informed traders are analogous to the ex ante and ex post notion of informed trading. 5 The ex ante informed are those who possess a precise signal about future returns, such as found when insiders trade in advance of a corporate announcement. The ex post informed are those who process order flow information into accurate predictions of future returns (e.g., Evans and Lyons, 2002 and Evans and Lyons, 2008 in foreign exchange markets, Brandt and Kavajecz (2004) for U.S. Treasury securities, and Deuskar and Johnson (2010) for the S&P 500 index). Our results suggest that the overnight informed are efficient processors of information like the ex post informed; these results are also consistent with a noisy rational expectations model of trading (e.g., Grundy and Kim, 2002). The intraday informed are like the ex ante informed as they appear to possess the best signals about very short horizon price changes and trade to capitalize on this knowledge. We use end-of-day positions and the daily change in these positions to identify informed traders. As such, our methods identify a subset of the informed population: those whose information advantage can be extracted from overnight holdings and net daily trading. Informed traders whose information advantage is realized by specific intraday trades, such as measured by price impact models (e.g., Hasbrouck, 1991) may not be selected by our methods, unless their net daily trading reflects these informed trades. For commodities in which we identify informed traders, we find that the average daily profits per trader are significantly greater for the informed than those of the not informed group. For the overnight informed in crude oil, we find the largest differences in average daily profits: $45,237 for the informed versus losses $3,401 for the uninformed. For intraday informed, the largest difference in average daily profits is found in natural gas: $95,885 for the informed versus losses of $2,693 for the not informed. Our results also show that floor brokers/traders (FBT) are over-represented and commercial firms—those with an underlying reason to hedge—tend to be under-represented among overnight informed traders. These findings support those of Kurov and Lasser (2004) for exchange locals and Anand and Subrahmanyam (2008) for floor traders and specialists.6 The overnight informational advantage of FBTs may stem from their access to order flow as they are not likely to have better access to market fundamentals than commercial firms, nor are they likely to conduct superior analysis compared to hedge funds. Consistent with the latter observation, we also find that the intraday informed are dominated by money managers/hedge funds (MMT) and swap dealers, with commercial firms again significantly under-represented. We find essentially no firms that systematically take losing positions, including natural hedgers such as producers, merchants and processors. Although line-of-business variables predict representation in our informed groups, variables that measure trader characteristics have even stronger predictive power. Using inverse regression methods (e.g., Li, 1991), we estimate that intraday informed traders have 15% more experience, 39% more activity and hold 58% larger positions than the average trader. Informed traders, particularly overnight informed, are generally more likely to trade on both sides of the market (i.e., both long and short). We also find that simultaneously holding positions in more contract expirations affects representation in the informed group, but this effect differs between the overnight and intraday informed. The overnight informed tend to hold positions in more expirations, again consistent with FBTs processing information from order flows, while the intraday informed hold positions in fewer expirations, consistent with selective trading by MMTs and swap dealers based on precise signals. We also develop methods based on intraday trading activity to identify which participants demand and supply liquidity and which participants behave as contrarian or momentum traders. Our results show that commercial firms (hedgers) are over-represented in the group of liquidity suppliers and that MMTs are over-represented in the group of liquidity demanders. This result differs from those using earlier aggregate data, which showed that commercial hedgers brought price pressure to futures markets when they adjusted their positions (deRoon, Nijman, and Veld, 2000). As our sample period includes a substantial increase in index fund participation, our evidence suggests that the normal role of commercial hedgers has changed from that of demanders to suppliers of liquidity (Harris and Buyuksahin, 2009 and Tang and Xiong, 2009). This research builds on a small but insightful body of previous work in commodity futures markets. Early studies of informed trading focused on the forecasting ability of futures traders using data on small traders at a single brokerage firm (Hieronymus, 1977 and Teweles et al., 1977) or placed traders into aggregate groups from monthly or semi-monthly observations (Houthakker, 1957, Rockwell, 1967 and Chang, 1985). Hartzmark (1987) found that commercial traders as a group earn significant daily profits compared to non-commercial traders. This result suggests that commercial traders are informed, but a later study by Hartzmark (1991) finds commercial traders with superior forecasting ability only in the pork bellies market, a finding supported by Leuthold, Garcia, and Lu (1994). In energy markets, Phillips and Weiner (1994) found some intraday profits for large integrated oil companies in the crude oil market, and Dewally, Ederington, and Fernando (2010) found that profitable individual traders in energy futures tend to hold positions opposite those of commercial firms.