Godfrey Cadogan's formula, linking high-frequency trading, bubbles and crashes all into one formula of extreme simplicity (or "parsimony" as Cadogan puts it) leaves our reporter wondering: does the rendering of facts as a formula make them clearer, or does it just create a misleading patina of precision? Emanuel Derman recently warned of the overly simple models of finance economists, and perhaps this is a new token of that type.

Celent says that both the IT world and the financial markets long assumed that the latter had to employ the former in a “batch mode.” A firm would process trades through the day, recording these in a data base. Then at the end of the day, programs that could manipulate this data in search of exploitable patterns would operate on the day’s results as a batch. That is the mode of operation that “has become increasingly obsolete.”

A recent meeting of an advisory group of the CFTC discussed the proper definition for high frequency trading, on the premise that only once a definition is in place can there be focused monitoring of the consequences of HFT.

Could it be that truth is finally stranger than science fiction? The next battle of the quantitative trading strategies may offer some algorithmic features that look downright qualitative.

Spread capture is a percentage of the bid-ask spread, so that if an algorithm always accepts the outstanding offer when buying – if it is always the one to cross -- it will capture 0 percent of the spread. If a deal is concluded on its own bid determined through limit orders, on the other hand, it captures 100 percent of the spread. The spread capture metric is popular, the Pragma paper says, because it “reflects a widespread assumption that the higher the number the better the performance of the algorithm.”

It is by now common knowledge that High Frequency Trading comprises 70 to 75% of market trading in North America and western Europe.  And it helps to remember that the primary usefulness of algorithmic trading is to provide liquidity to the investor class.  We presume that the distinction of said class is that its investment [...]

By Christopher Faille Charles Jones of Columbia Business School made a presentation at an SIFR event in Stockholm, titled “What do we know about algorithmic and high-frequency trading?” Although a distinguished professor like Jones would not put the matter this way, his thoughts do have me thinking of the old human-inhabited trading floors, and their cyberspace [...]

Dennis Lohfert, founder of Ion Asset Architecture, discusses quantitative trading strategies and how they are affected by current market conditions.

AllAboutAlpha.com interviewed Arzhang Kamarei, a partner at Tradeworx, a quantitative investment management firm with expertise in high-frequency and medium-frequency equity market-neutral strategies.

By Christopher Faille It is possible to be nostalgic about the era before computerized trading, and thus before high frequency trading (HFT), when the transmission of orders took place by means of a human voice over a landline telephone.  But we must qualify any such nostalgia.  Consider that the market makers at Nasdaq as recently as [...]

In the alpha world, skill often depends on the support of other factors. Some call them pedigree, process and performance, and rank them in that order. There's only one problem: despite the best pedigree, and the best process, performance can suffer tremendously when something unpredictable occurs – a black swan or tail risk.

Hamlin Lovell reports from The Battle of the Quants 2011.

Carrier pigeons and post roads gave way to telegraph lines, then telephones, then networks of computers. In our own century automation has gone so far that actual human beings on an exchange floor seem destined to share the obsolescence of those pigeons.