In the IHT, Hal Varian reports analysis of 1.5 million messages from online trading chat rooms [1]. Two researchers, Werner Antweiler and Murray, used their statistical tools and were able to glean a few clues and predictions for markets trades [2].
Not terrifically much, it seems, but that's to be expected if one follows the efficient market hypothesis. However, it's not that far off a scam or two that's been going on. Allegedly, I hear, rumour has it, and all normal caveats....
The place to look at is not the public chat rooms, which anyone will tell you is mostly noise, but the private places. The chat community of choice is the traders in the large banks. To get access to their chat, which is much more focused on big and real trading, you either have to be an insider, or very cunning.
The cunning way to do it is to attract the traders to get into your own chatroom and encourage them to think about trading. This can be done by setting up a fantasy trading system. In these systems, you post trades that are nominal or virtual, and encourage traders to get involved and play. It's a bit like fantasy football, if you've seen that. As traders do well on the predictions, they get rewarded, with value that is "outside" their normal salary system in some sense or other (extra points if the rewards can be delivered tax free!).
So the traders are encouraged to reveal the insider secrets of their employer banks in order to score big in the game. Is it that simple? Yup. Traders really don't care about the secrets, but they sure as hell care about scoring big in the games ... and perversely, the banks enourage this behaviour as they go hunting for analysts who've proven themselves in the game world!
Then, of course, the system operator takes all the chat and all the trades and pumps it into their black boxes. Out spews the predictions, the operator passes it on to another sister company who arbitrages the banks, and they make out like bandits.
Here's how the insider does it. Being on the inside, and being able to tap directly into the networks, one can collect all the trader and analyst chat in real time, and pump it into an analytics engine. Then out comes all the predictions ... so far so good.
But, if the insider does all this, they need some infrastructure, and it's hard to do that without getting noticed. Not to mention that if they were able to make a trade, they'd be betting against their own bank!
So one could be excused for thinking this was unlikely. Until the advent of the mutual funds scandal that is, where we discover all sorts of egregious behaviour, including mutual funds trading against their own parent manager banks [3]. In that scandal, many mutual funds were operated by major banks or other large institutions. Some of them, it seems, were simply listening to all the insider info, analysing it, and betting against their own organisation.
What's going on here? Well, the mistake of the outsider is two-fold: firstly, to assume that the bank operates with one goal in mind, and secondly to assume that if they bet against their own trades, they are stealing their own money.
It turns out that all the trading that they are arbitraging is trades of clients. For which fees are earnt, in a competitive framework. So as long as the client doesn't know, nobody cares. And, it turns out that what with Chinese walls and results-oriented management, there is no problem whatsover with one department betting against another; some banks even do it as a matter of policy.
So, what we have is a fairly aggressive framework where managers of mutual funds are sucking their own trading floors for profits. Where it gets eggregious would be if they are doing it via insider information - chat, for example. And if they are doing it in such a fashion where the insiders that are getting paid off are keeping the scam a secret: encouraging the traders to reveal and perform worse than they otherwise would.
Of course, we don't know where or if this precise scam is going on. But, all the building blocks are in place: the means, the motive, the weapon. It would be a shock to me if it wasn't a done deal.
Hal R. Varian NYT Friday, September 24, 2004
Online messages presage active trading
Talk is cheap, particularly on the Internet. Stock message boards are a case in point. Every day, participants post tens of thousands of tips about which way various stocks are heading. Is any of this worth reading?
Recently, two financial economists from the University of British Columbia, Werner Antweiler and Murray Frank, examined the message board phenomenon in a paper titled "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," published in the June 2004 issue of The Journal of Finance.
They collected more than 1.5 million messages from two online boards, Yahoo Finance and Raging Bull, and analyzed them using methods of computational linguistics and econometrics.
The computational linguistics techniques allowed them to classify messages with respect to whether they advocated buying, holding, or selling the stock in question. Most of the messages were short and direct, allowing the algorithms to do a pretty good job of classification.
Antweiler and Frank then merged the estimated buy, sell or hold signals into one "bullishness measure," which was a slightly modified version of the ratio of buy to sell recommendations.
During the period they examined in their article, January to December 2000, the Internet bubble dissipated. Bullish messages, however, continued to proliferate.
But did the message volume, timing, and sentiment forecast anything useful? The three most interesting features of a stock on a given day are its return, its volume and its volatility.
The authors found that the characteristics of messages helped predict volume and volatility. Perhaps more surprisingly, they also found that the number of messages on one day helped predict stock returns the next day. The degree of predictability, however, was weak and reversed itself the next trading day.
The bullish sentiment of messages was positively associated with contemporaneous returns, but has no predictive power for future returns. Traders post bullish messages about a given stock on days when its price goes up, but it is hard to determine which way the causation runs. Since postings do not predict future returns, it may be that the returns cause the postings.
The story was different with respect to volatility. It appeared that the more messages posted about a stock one day, the higher its volatility was the next day.
Trading volume was also correlated with messages. However, the apparent causation here was somewhat subtle. Message posting appeared to cause volume when the researchers examined daily data. But when they looked at the market at 15-minute intervals, trading volume seemed to cause messages.
One hypothesis consistent with these observations about volume and messages was that people might tend to post messages shortly after buying a stock. Even though there are two sides to every trade, the seller has little incentive to brag about the dog he just unloaded, while the buyer has a strong incentive to recommend that others buy the stock he has just purchased.
The authors conclude that the talk on message boards is not just noise. Though the predictive power for returns is too small to be meaningful, message board activity does seem to help predict volatility and volume. Varian is a professor of business, economics and information management at the University of California at Berkeley.
[1] Hal R. Varian NYT, "Internet stock talk may have statistical meaning"
[2] Werner Antweiler and Murray Frank, "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," published in the June 2004 issue of The Journal of Finance.
[3] James Nesfield and Ian Grigg, Mutual Funds and Financial Flaws, testimony to the U.S. Senate's finance subcommittee, 27th January 2004.
By monitoring the NASDQ and understanding the prints and who the players are behind the prints, the trades are easily understood. It is like an old group of friends that play poker, over the years everyone knows the other signs, the tells of bluffs and the real hands.
The same scenario happens in all trading markets. The trader that plays every day knows when he is playing against a computer and when he is playing against another player of equal ability. The key is the activity level, which must be large enough to make it worth his time and money to be playing in. Like any good gambler small profits with low risk profiles are best, the more the better.
If you can automate this scenario then you get to play faster and at more hands. Large macro bets are a fools game, grinders never look for the big lick, they fish where the fish are and keep fishing until more fish show up somewhere else.
Flipping for an .125 or simply the rebate can earn 2% per month on the money at 24% per year and the potential for a large trade now and then the rate of return conservatively approachs 30%. In very active market conditions rates of 70% are not unknown. At 70% return per year and margin of 10 to one things are pretty good.
The thing the banks never see officially is the network of cooperation amoungst the grinders. Many of the insiders that gamed the mutual fund field had been doing it for twenty years in a small way without being spotted. Keep the game small with little or no bragging and the game will make you rich. Make it large and it will make you infamous.
IM is way to blunt a tool and easily understood by all that read it.