Homegrown Software Fuels Mexico's Stock Exchange Adam Thomson - Financial Times
go to original October 4, 2012

There were a few nerves jangling at Mexico’s stock exchange last week. One well-publicised reason had to do with the public offering of Santander Mexico, the local arm of the Spanish bank.

The 25 per cent of the company offered to investors raised more than US$4.1bn and was the largest public offering in the history of the exchange, known by its Spanish acronym of BMV. The international portion of the offering, carried out in New York, was over-subscribed five times on an otherwise gloomy day for global stocks.

But there was a second, less-publicised reason in the form of the biggest test yet of MoNet, the BMV’s brand-spanking-new trading engine, which had its formal inauguration less than a month before on September 3. As Luis Téllez, president of the BMV, told the FT recently, “our margin of error for putting this in place was zero”.

As it turned out, the engine performed even better than expected and experienced no significant problems – unlike the implementation of the London Stock Exchange’s Millennium platform.

According to Enrique Ibarra, who is in charge of implementation, it handled 15,799 trades in Santander Mexico shares last Wednesday – the day of the offering. That is a record for the number of shares in a single company traded in one day. Not only that, the engine handled them at an average latency, or lag time, of about 70 microseconds.

For anyone familiar with trading engines, that is pretty fast. Nasdaq’s platform has a latency of about 110 microseconds and the London Stock Exchange’s is 125 microseconds.

The upgrade – Sentra, the engine MoNet replaced, was at least 300 times slower – has several important implications as the BMV looks to attract a wider global investor base. The first is that the exchange and its capabilities can now handle far more orders.

Over the past few years, investors have started to use computers running complex algorithms to generate buy or sell orders in ever-higher volumes. That has led to an exponential growth in the number of orders an engine has to process. In the BMV, the volume of daily orders one day in August last year hit 3.1m. In 2005, the highest number was 65,500.

The second implication is that the new engine makes the BMV potentially much more attractive for so-called “sophisticated investors”, who use this algorithm-based high-frequency trading.

Such trading requires fast engines at the exchanges to take advantage of trading opportunities that may last only tiny fractions of a second. BMV’s new engine now provides the power to make them happen. As Mr Ibarra says, “it allows for an explosive growth of the market”.

So where does this super engine come from? London, perhaps? Asia? The answer is downtown Mexico City. The exchange enlisted the help of the Software Engineering Institute of Carnegie Mellon, IBM, Oracle Java Labs and Roland Tibell & Bourse Consult. But the end product was an in-house solution.

Mr Téllez admits that the decision was controversial not least because of the relatively small operation: total market capitalisation is only about 42 per cent of Mexico’s gross domestic product (GDP) compared with about 150 per cent in the case of the Brazilian bourse.

But he also says that the benefits are numerous. First off, he says, being a small exchange magnifies your dependency on a third-party provider. “Whenever there is a new request from an operator, you need upgrades and that is very expensive in the long run,” says Mr Téllez. “Now, if we want to change something, we can just go ahead and do it.”

The second benefit is cost. At US$11.5m, including development and implementation, the engine is substantially cheaper than one from a third party, which the BMV estimates would have cost at least US$20m.

So what’s next? According to Mr Ibarra, the vertically-integrated BMV is looking to extend the platform to handle its derivatives market. Tests will start in December and, if all goes well, it should be up and running by March of next year.

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