Algos Take Hold in Fixed-Income Markets
February 8, 2010
Want to make $10 million a year? Simple: Be able to create algorithmic, high-frequency trading applications for bonds and fixed income derivatives that make your firm lots of money.
If your high-speed apps can find arbitrage (read: lucre-making) opportunities, such as being able to pinpoint real-time pricing discrepancies between cash and bond futures, say, or quickly hit and lift optimal Treasury prices streaming from competing inter-dealer brokers' electronic bond trading platforms, you've got a shot at an eight-figure income.
Anyone unconvinced that algorithmic trading has come whole hog into the fixed income world should look at the want ads. Take this posting-and there are many like it-from Jan. 11: "Our client seeks... automated analytical black box trading strategists with proven track records at top-tier investment bank, hedge fund or prop shop ... high-frequency trading strategies for fixed income cash bonds, interest rates and credit derivatives. Compensation: 1M-10MM."
Yet, until recently, algorithmic trading wasn't much applied to fixed income, and then, only sparingly in basic VWAP (volume-weighted average price) analyses. VWAP is a passive strategy aimed at trading at prices that basically match the amount of trading occurring in the security at the time, so the market impact of one's own execution is as slight as possible.
Ubiquitous in equities for years, algos for bonds are now much more complex, varied and numerous, as certain asset classes have become more electronic and therefore applicable: What's made this possible are streaming quotes from the e-trading venues of inter-dealer brokers, which have provided the foundation for automated, model-triggered strategies. Without live, streaming quotes, similar to those long available in stocks on equities exchanges, algorithmic trading is difficult to nigh impossible.
"The high transaction volumes taking place between a relatively small and well-defined set of counterparties make IDB [inter-dealer broker] markets the logical front line for fixed income algo trading," says Billy Hult, president of Tradeweb, which since 1998 has run a multi-dealer-to-buy-side electronic bond trading platform but last year launched an inter-dealer platform called Dealerweb.
"In the 18 months since we've entered this business with Dealerweb ... we've seen an increasing trend towards more automated trading," Hult said.
SPECIFIC BOND ALGOS
Algo-based bond strategies include but are not limited to trading on price discrepancies between Treasury cash bonds offered on the major IDB platforms and Treasury futures on futures exchanges. Similar "arbitrage" strategies are increasingly being applied to interest rate and credit default swaps, as more of these derivatives are trading electronically ahead of regulatory overhauls calling for same. Many current algo job postings are asking for expertise in these over-the-counter derivatives.
A lot of the activity so far, though, occurs over the futures exchanges that offer bond derivatives, like the CME Group, Eurex and NYSE Euronext.
"What we see most in the algo space in Europe involve interest rate futures, Eurodollar futures and bond futures," said Steve Wilcockson, industry manager of computational finance at The MathWorks. The Natick, Mass.-based firm's Matlab programming language is widely used by financial firms to construct proprietary algorithms and quant applications.
"Quite frequently hedge funds will also construct their own yield curves to compare and contrast with the yield curves the market data vendors provide." The idea here is to act quickly on what may be incorrect-albeit consensus-pricing from vendors known for selling "de facto" yield curve data, such as that from Bloomberg or Markit.
