The global foreign exchange may be the world’s most liquid market, with more than $5 trillion traded daily, but that liquidity is not always so abundant when it comes to emerging markets. Can execution algorithms help the buy-side manage uneven and sometimes chaotic market conditions?
Quant Hedge has developed a method for short and medium-term FX and Futures trading that is based on what the systematic firm calls ‘aggregated alpha’. It’s an uncommon approach that also seeks to capitalise on a back-testing model that is the complete opposite of what many firms use. Adam Cox of FXAlgoNews catches up with Quant Hedge’s Managing Director, Victor Lebreton, to discover more about the process.
To an algorithmic trader, Bitcoin is just another foreign currency. It is freely convertible to most major currencies, it can be traded 24×7, and it can even pay interest. Furthermore, one can ask for historical data for backtesting, including level 2 quotes, from most of the exchanges. These exchanges offer application programming interfaces (API) to algorithmic traders for connection to their own automated trading programs. So the only question left is: what sort of systematic strategies can work on Bitcoin
After a period of extensive media attention on the traditionally opaque and free-wheeling foreign exchange industry, FXAlgoNews explores how the regulatory landscape could affect the trend of algo adoption by the buy-side.
Adam Cox catches up with the Zurich-based fund manager Philippe Bonnefoy, who the mid-2000s, started a venture using algorithms to seize short-term FX opportunities, a trading technique he has been honing ever since and which is central to the success of his firm Eleuthera Capital AG.
If you’re new to FX algorithmic trading, one of the first technological challenges you will face is connectivity. And it is not a trivial one. Despite what you might think, optimising connectivity is not something to be left only to high frequency trading firms, as in our current times, bad latency means money left on the table for each trade you make. You may already have a solid background in equities algorithmic trading, and you might consequently treat this question as a “déjà vu”, but this would be a mistake.
Demand by the buy-side for algorithms to trade forex is expected to continue to climb. That’s the collective view from bankers, vendors, industry analysts and developers contacted by FXALGONEWS. The algos are getting better and the focus on best execution has never been higher. That provides a recipe for more and more hedge funds, corporates and large asset managers to adopt algo-based trading strategies.
All the surveys indicate growing take-up of FX algos among corporates and the real-money community. But aren’t they the cautious ones? William Essex wonders how today’s regulatory environment could possibly be a good time to try a new approach to transacting.
Strategy backtesting is a mix of art and science. Quants who rely too much on patterns in data will fall victim to curve fitting, while others create theories to fit their models. Here are leading quants’ perspectives on best practice in strategy backtesting: by Jared Broad of QuantConnect.com
All the building blocks would seem to be in place for the take-up of algorithmic forex trading by the buy-side in the Nordic region, and yet it is still very much a work in progress as Adam Cox discovers.
