Thomson Reuters Gives Elite Traders Early Advantage
cnbc.com
cnbc.com
It was already known that they released the data 5 minutes early to subscribers who wished to pay more. It's not really a stretch to think they'd offer tiers for people who wished to pay more.
The data is, after all, legally theirs to release, and Michigan University knew and approved it.
If this is something people don't like then they can vote with their feet and move to a different news source.
Once again Nanex is all over this.
A significant chunk of the money Reuters pays for the reports, which they recoup through subscriptions, winds up going to pay for the production of the reports anyway. The only thing that surprises me about this is how much money they are likely leaving on the table. They should let people bid for early access.
However, if "everyone" knows that some companies can buy these reports minutes ahead of time, then when people lose out on trades in the minutes afterwards, isn't it the fault of the people taking the trade?
It's not wise to trade with people who might have more knowledge than you. It seems like there's a reasonable expectation that the people on the other sides of these trades should know about the paid access.
We have decided that it should be illegal for public companies to give information selectively for the purposes of trading. We could easily change this law, but history has shown us that it isn't heavy handed and does have a positive impact on the market.
(It's actually worse - it's six clicks from the home page to the document.)
' "...I eventually had to go down to the cellar to find [the plans]."
"That's the display department."
"With a torch."
"Ah, well, the lights had probably gone."
"So had the stairs."
"But look, you found the notice, didn't you?"
"Yes," said Arthur, "yes I did. It was on display in the bottom of a locked filing cabinet stuck in a disused lavatory with a sign on the door saying 'Beware of The Leopard'." ' - Douglas Adams
I'm not sure if I'm joking or not.
You could easily group things into 500ms classes though. But 500ms is kind of an eternity in these types of things and you'll never really have someone thinking that they have a system fast enough to beat someone who started 500ms earlier.
That said, serious traders who object to this tax can predict the signal from more-primary sources.
There is a certain amount of overhead involved in the creation of the dataset. Hiring people to call and collect answers, filtering the data, formatting it, fielding questions about it, etc. The University of Michigan seems to partially pay for this by the fees they charge Reuters. I am not sure if they make a profit on it or, if so, how much. But you could probably found some company to collect and provide the same amount and quality of data for cheaper.
However, even if you were able to beat them on cost, you wouldn't be able to charge nearly the same amount that UofM does for it. The reason is that the UofM data goes back for over three decades, so traders can do all sorts of backtesting with it. They are also a recognized "brand" in this field and over time sources of trading information like the UofM report become ingrained in traders' minds as "indicators" of one type or another. So, for various practical and psychological reasons, your hypothetical startup would have to charge a much lower price for the same data and spend many years earning the confidence of traders.
Ironically, you might be able to make more money by selling the data as an early predictor of the UofM report. Since traders know that the UofM report can be a market moving event, any early predictor of it (even one with ~90% accuracy) would be valuable. This would probably just force UofM to collect and release the data earlier and with less polish though, negating much of your advantage.
It doesn't matter how good your own data is if the data's release doesn't affect stock prices.
It would be hard to enforce a true "blackout period". Traders trade on all kinds of information, not just controlled data. Wouldn't liquidity tend to be lower on a non-realtime exchange, because everyone is essentially trading on outdated information, resulting in worse prices than the realtime exchange?
But I know very little about this stuff, so maybe I'm completely wrong.
I think prices would be better for people not playing the low latency response game. Liquidity within an hour would probably cost a premium as you'd have to get the money from someone on the real time market.
That would make no sense at all.
Someone at Michigan should make a startup that builds a system to sell this information at market value, which most certainly is way more than $1 million per year.