Electronic & Algo Trading: Make or Buy?
Automated trading refers to the use of computer technology and the Internet to trade in electronic markets. It transformed trading in the main markets for equities, fixed income, currencies, commodities, and derivatives.
Nowadays, hedge fund and other traders can auto trade financial instruments on public exchanges such as NYSE, LSE, CME and LIFFE, and other venues offering electronic trading, via third party platforms or direct market access (DMA).
The simplest form of automation comes from using stop and limit orders, opening or closing positions when a set price level gets hit. The most complex form employs quasi-AI based (such as machine learning).
Older electronic trading venues (the public exchanges above) tend to develop their own systems, while some newer venues are happy to use third party software. They offer two access options:
- GUI – traders run an exchange application on their desktop to connect to the venue
- API – traders plug their own platforms directly into the venue
Traders can analyse markets in depth and place orders using third party platforms such as Bloomberg or Reuters, or their own platforms.
The process of connecting counterparties is supported by the Financial Information eXchange (FIX) Protocol. It is the standard financial organisations use to communicate trade information.
More and more electronic trades are generated by hedge funds and other trading firms running fully automated systems. Which let machines manage the all trading process, including what to trade, when and where.
These systems employ algorithms. Some of them are relatively simple, some are quite complex.
In order to gain an edge, many hedge funds are employing “super algos”, which are quasi-AI based trading strategies. For example – algorithms searching for patterns, adjusting to what works in the markets that day, week or year.
Algorithms are used in many trading strategies. A lot of algo-trading today is high-frequency trading (HFT), which takes advantage of short term opportunities, leveraging automation to buy and sell financial instruments in short time spans.
Make or buy
Developing an automated trading platform in-house is expensive to develop and manage, especially if the trading strategies require access to several exchanges, complex algorithms and people with advanced degrees in subjects such as Mathematics, Physics and Statistics.
There are third party solutions which are cost effective, and tried & tested. The make or buy decision depends, among other things, on trading strategies. Strategies include Momentum, Statistical Arbitrage (Statarb) and many more.