Archive for July, 2007

Prediction Markets for consumer market forecasting

Sunday, July 29th, 2007

The New Yorker magazine’s financial correspondent, James Surowiecki, has an article in the issue of 2007-07-09 about the use of prediction markets to forecast the success of Hollywood movies, and the uptake of new consumer products.  One advantage of prediction markets over focus groups or delphi forecasting techniques is that prediction markets value diversity of opinion and differences in private information, and thus do not suppress these differences in a desire to achieve a consensus.

“MediaPredict, however, is wagering that in the real world success is, at least in part, predictable, and it follows a model that, over the past decade, has proved surprisingly effective in forecasting a wide range of events: the prediction market. Prediction markets function like futures markets, except that, instead of betting on the future performance of a company or a commodity, people can bet (often with play money) on things like election outcomes, current events, and product sales. Rather than relying on the gut instincts of a single decision-maker, prediction markets tap the collective intelligence of everyone playing the market. The most successful media prediction market is the Hollywood Stock Exchange, in which traders collectively forecast the box-office performance of Hollywood films, Oscar nominations and results, and the performance of individual actors, with striking accuracy. The market on average picks more than eighty per cent of Oscar nominees correctly, and hasn’t missed more than one Oscar winner in the past four years. More important, it has also done a good job of predicting box-office performance. According to a study by Anita Elberse, a professor at Harvard Business School, the market’s forecasts are off, on average, by sixteen per cent—far from perfect, but a track record that most studio marketing departments would be proud of.

It isn’t just Hollywood, either. A British firm called Brainjuicer has been using collective intelligence to research the prospects of everyday consumer products, and its findings suggest that such techniques can forecast more accurately and subtly than traditional consumer research methods, which have a reputation for producing mediocre results. For instance, prediction markets avoid many of the faults of focus groups, which tend to be dominated by the loudest and most opinionated people, to be driven toward consensus decision, and to discourage disagreement, making them of limited usefulness. (“Seinfeld,” famously, was a complete bust with focus groups.) Prediction markets, by contrast, are competitive environments, and so they encourage diversity of opinion, minimize people’s influence on one another, and force people to think not only about their own tastes but about those of consumers as a body.”

Algo-trading one third of all US share trades

Sunday, July 29th, 2007

Posting the other day about Alternative Trading Systems and algorithmic trading in Canada reminded me that I’d not posted this recent article from The Economist about the growth of algorithmic trading.  The main applications seems to be in arbitrage — detecting and exploiting price differences for the same stock on different markets — and rapid exploitation of breaking news.   Fast analysis of news feeds, of course, is a great example of semantic technologies in action, and requires subtle computational linguistic analyses. 

“As the time taken to process computer-generated trades falls to thousandths of a second, algorithms are being created to react to news headlines faster than the eye can scan them. Dow Jones and Reuters, the news providers, now offer electronically “tagged” news products that algorithms pick up to make programmed trading decisions. (Dow Jones claims the business is so secretive that it cannot divulge details of customers.) Britain’s Financial Services Authority, a regulator, also hopes to use algorithms to comb through trading data to find hints of suspicious activity, which it reckons takes place before about a quarter of all takeover announcements.

Algorithmic trading accounts for a third of all share trades in America and the Aite Group, a consultancy, reckons it will make up more than half the share volumes and a fifth of options trades by 2010. On June 18th the London Stock Exchange unveiled an electronic system catering to the growth of algorithmic trading, which cuts trading times down to ten milliseconds. On its first day, it processed up to 1,500 orders a second, compared with 600 using its previous system. The ability to push up volumes should help dissuade customers from moving to faster platforms elsewhere.

The aim is to reduce the delay between order and execution, known as latency. Every moment is crucial in “black-box” and “statistical arbitrage” trading, where computers prowl through the market for price distortions that may last only for a split second. Order-handling algorithms, which break up large trades, must also move faster than the blink of an eye to ensure they get the best electronic prices.

According to TowerGroup, a research firm, $480m is likely to be spent in America this year on developing technology for algorithmic trading. Such is the focus on speed that even location counts. Servers positioned nearest to a trading venue can shave milliseconds of the timing of a trade and get a better price.

Low latency could also help investors get a jump on news of economic data as it flashes across the wires. According to Andrew Silverman of Morgan Stanley the use of news feeds for algorithmic trading is at an early stage. The software, which relies on keywords to generate buy and sell orders, may misunderstand the context surrounding a headline. For example, a market-moving word such as “surprise” may indicate numbers are better, or worse, than expected. Mr Silverman explains that news algorithms are best used with other variables, such as share price and volume, which may reinforce the buy or sell signal.”

July 2007 ACE Newsletter now out

Sunday, July 29th, 2007

The latest newsletter on Agent-based Computational Economics by Leigh Tesfatsion is available from here.

2007 CAT Tournament complete!

Thursday, July 26th, 2007

The 2007 TAC Market Design (CAT) Tournament is now complete, and the winners were:

First Place:  IAMwildCAT from University of Southampton, UK

Second Place:  PSUCAT, from Penn State University, USA

Third Place:  CrocodileAgent, from University of Zagreb, Croatia.

 Congratulations to the three winning teams!  

There were 10 finalists, from Australia, Croatia, Greece, Iran, Romania, UK and the USA.   The final scores of the ten finalists were as follows:

1. IAMwildCAT 365.496
2. PSUCAT 328.333
3. CrocodileAgent 308.813
4. jackaroo 272.239
5. Havana 256.441
6. PersianCat 218.458
7. PhantAgent 146.208
8. Mertacor 133.912
9. TacTex 107.925
10. MANX 95.976

The scores are also available from the game results pages, here.

Thank you to everyone who participated, and thanks to all those who helped make this game a great success – the AAAI organization staff, the technical staff at the Hyatt Vancouver, the Trading Agent Competition Committee, the Brooklyn College CAT Development Team, the Southampton University CAT Design Team, and the Liverpool University CAT Management Team.   Thankyou to everyone for a successful first CAT Tournament!

Algo trading near the Arctic

Sunday, July 22nd, 2007

In Vancouver for the finals of the TAC Market Design or CAT Tournament, being held at AAAI 2007. 

By coincidence, the weekend edition of the National Post newspaper published yesterday a feature story on [tag]algorithmic equity trading[/tag] (which seems to be hidden behind a pay subscription wall, and not even accessible via the paper’s search engine*), and a related article on Canada’s emerging market for [tag]alternative trading[/tag] of equities, alternative trading systems, or so-called “[tag]dark pools[/tag]“.  The first article quotes Forefactor, a Toronto research firm, as saying that 36% of all equity trades originating in [tag]Canada[/tag] use some form of [tag]algorithmic execution[/tag].  

The CAT Tournament starts tomorrow, Monday 23 July 2007, at 0830 American Pacific time.  You’ll be able to watch the game progress here.

* Some newspaper executives still don’t get it.  Even if the Post article has to be paid-for to be read, at least let us see that the article exists online via your search engine!  Or is it the case that an article on software trades does not even exist online? 

Online auction for security bugs

Monday, July 9th, 2007

BBC news has reported that “Security researchers who find holes in software can now sell their findings to the highest bidder.” Specifically, The idea behind this marketplace, namely WabiSabiLabi, is to motivate security researcher to make loopholes known, so that they can be corrected, instead of being given away for free or even sold to cyber-criminals.