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Minutes of the Global Algorithmic Trading Conference at UCL


You probably knew that the Alpha Novae's team was represented at the Global Algorithmic Trading Competition conference at UCL. For you readers of Automated Trading we decided to make a small report of what we saw and heard.

For those who didn't follow, the conference took place at UCL ( University College of London ), a prestigious university well known for the quality of its education and its researches as well. The conference was mainly focused on "professional" algorithmic trading so more on institutional algorithmic trading or High Frequency trading than on automated trading as we know it on MT4 ;). All along the day, Microsoft, Barclays Capital, City Knight and LMAX followed one another to offer us twenty minutes presentations. I will try here to give you a brief feedback of the conference and to reveal what all these people are working on ( at least what they're willing to tell us )

First of all let's start with a short visit of the UCL campus

You can see here the main entry of the famous university. All the students who are reading us should note that UCL is, at this date, the only university ( at least european ) to offer education in the algorithmic trading sector with, among others, a MSc in Finantial Computing. In 2010, UCL is ranked 21st in the world (and 3rd in Europe) in the Academic Ranking of World Universities, 4th in the world (and 2nd in Europe) in the QS World University Rankings and 22nd in the world (and 5th in Europe) in the Times Higher Education World University Rankings. If you are a student passionate by automate trading this seems to be a proper education ( however, be careful about the admission conditions and the education fees ). As concerned the conference itself, it naturally took place in the computer science department of the university.


Let's now get to the heart of the matter. Here is my report of the different presentations we attended :

The first intervention was presented by a UCL teacher named Philip Treleaven. He started by remind us how much algorithmic trading was an integrant part of the markets since it represents in the US between 60 et 70% of the shares trades volume. If all this positions were in fact opened automatically we should differentiate the simple execution algorithms, Market Making or arbitrage activities from the famous Black Boxes. Because what is actually interesting us here is the Alpha and the modelling of profits making strategies. Here is an automated trading system diagram as it was presented to us.

So according to this teacher, the data feeds would be for our black boxes what the blood is for human beings. "the more data you have, the more succes" added. And if the classical strategies use today the prices of the instruments traded, the speaker insisted on the opportunity that represents the use of "social" data ( news informations or data extracted from social networks such as twitter ).


The second presentation was held by Chris Donnan from Barclays Capital. We learned here that to make profits in the verry competitive market of the algorithmic trading, Barclays works mainly on 4 factors : the hardware ( more than 800 machines dedicated ) the software ( with a framework developped by and for Barclays ), the networking ( trading data as fast as possible ) and the relationships ( the exchange of ideas and knowledge between traders, quants and other analysts ). The quant desk manages to open 8 positions by second and realizes between 200 and 250 thousands transactions a day( if this is not HFT.. ). The man concluded this way : ' the technology is really the core of the business" even if he underlined that the 3 other factors we were talking about earlier were also important pieces of the automated trading puzzle. To conclude i will add another quote " Working in automated trading is exciting as they are big hairy puzzles to solve "


The third intervention introduced the competition launched by UCL and all its sponsors around automated trading. It's a very attractive competition since, as the man pointed out, the 20 000 pounds of cash prize are nothing compared to the wage of the one who will be able to show off on his CV for having arrived first. I will thus encourage all the interested members of Automated Trading to compete by their own, or even better, to work together for the win since the team projects are allowed. This is now the prizes list :

- The best algorithm Microsoft Prize : 5000 pounds (+ 2500GBP depending on the performance)

- The best use of the Microsoft Technology : 2500 pounds

- Barclays Capital Prize for best competition entry by a female contestant : 2500 pounds

- CitiFX Prize for best trading model : 5000 pounds

- Knight Capital's Prize for Best Use of Data : 5000 pounds


The fourth intervention was held by Dr John Loizides from City and dealt with High Frequency Trading on Forex. The Forex is a quite young sector for automated and algorithmic trading, unlike equities and CFD wich are the "source" markets. In order to trade on UTs shorter and shorter, the algorithms are analyzing more and more data feeds as you can see here


The capacity to process and analyze these data is a decisive parameter in the modelling of algorithms. Today more than 100GB of data are available per day to institutionals. As concerned the programming language, it varies a lot depending on the needs (FPGA’s, C/C++, C#, KDB+, Q, JAVA). I will finally add a quote which attracted my attention "The ability to find real market indicators within the high frequency world with a respectable profit and loss profile is difficult, but very achievable with the correct mathematical and technological approach."

The fifth presentation was the Microsoft's one which presented to us its "new" programming language : the F#. F# can be integrated to an environment using standards for language. It's a mathematical oriented language. This makes F# a verry attractive tool for quants but which can also reveals itself useful for any other financial application.

Let's note also that it allows quants to directly contribute to the tools development ( no need to code in mathematical language and then in C++ )

Finally F# is located somewhere between C++ and a pure mathematical language ( closer from python for example )

To conclude here are the Hardware trends for the future according Microsoft

- Clouding
- Multicore

Finally, LMAX, the London Multiple Asset Exchange, which is the first exchange (MTF) for Forex and CFD trading, gave a conference on its capacity to handle the global trading risk for its clients tick by tick, which is a real innovation in the field. In fact, the platform LMAX based on the Betfaire technology manages everyday more trades than the all the professional market trades. In fact, the retail world multiply the number of traders, who have the tendency to take much more risk than the professionals. Each transaction has thus to be validated, and at each tick the global risk calculated. Knowing that LMAX is oriented to High Frequency Trading, this was impossible with the standard tools. They thus created an inovating low latency environment and were professionally prized for this. And, even more surprising, they opened the code of their framework entitled "disruptor".

For information, Alpha Novae is a partner of LMAX and realizes currently a bridge allowing to duplicate the orders executed via MT4 on LMAX.

Finally the day ended between petit-four and passionate talks. We really enjoyed being able to meet some clients and talk about interesting partnership projects.

Jeremy for Automated Trading

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