Systematic trading (also known as mechanical trading) is a way of defining trade goals, risk controls and rules that can make investment and trading decisions in a methodical way.
Systematic trading includes both manual trading of systems, and full or partial automation using computers. Although technical systematic systems are more common, there are also systems using fundamental data such as those in equity long:short hedge funds and GTAA funds. Systematic trading includes both high frequency trading (HFT, sometimes called algorithmic trading) and slower types of investment such as systematic trend following. It also includes passive index tracking.
The opposite of systematic trading is discretionary trading. The disadvantage of discretionary trading is that it may be influenced by emotions, isn’t easily back tested, and has less rigorous risk control.
Systematic trading is related to quantitative trading. Quantitative trading includes all trading which use quantitative techniques; most quantitative trading involves using techniques to value market assets like derivatives but the trading decision may be systematic or discretionary.
Suppose we need to replicate an index with futures and stocks from other markets with higher liquidity level. An example of systematic approach would be:
- Identify, using fundamental analysis, which stocks and futures should be used for replication.
- Analyze correlations between targeted index and selected stocks and futures, looking for the strategy which provides a better approximation to index.
- Define a coherent strategy to combine dynamically stocks and futures according to market data.
- Simulate the strategy including transaction costs, rollovers, stop-loss orders and all other wanted risk controls.
- Apply the strategy in the real world using algorithmic trading for signal generation and trying to optimize the P&L, controlling continuously the risks.
Following the ideas of Irene Aldridge’s, who describes a specific HFT system, a more general systematic trading system should include these elements:
- Data management (in real time and for backtesting purposes)
- A signal generation system (to create, buy and sell signals according to predefined strategies using quantitative methods)
- A portfolio and P&L tracking system
- A quantitative risk management system (defining exposure per market, group, or portfolio)
- A routing and execution subsystem (usually containing execution trading algorithms, like TWAP, VWAP…)
The key point in systematic trading is the use of backtests to verify (at least partially) strategies and alternatives. It’s a basic point in backtesting to have easy and robust access to trading data.
Systematic trading should take into account the importance of risk management, using a systematic approach to quantify risk, consistent limits and techniques to define how to close excessively risky positions.
Systematic trading, in fact, lends itself to control risk precisely because it allows money managers to define profit targets, loss points, trade size, and system shutdown points objectively and in advance of entering each trade.
- ^Carver, Robert (2015). Systematic Trading. UK: Harriman House. p. 10. ISBN 9780857194459.
- ^Systematic trading, benefits and risks
- ^Aldridge, Irene (2010). High Frequency Trading, A Practical Guide to Algorithmic Strategies and Trading Systems. Wiley Trading. ISBN 978-0-470-56376-2.
- ^Canals, L.F. “Why HFT cannot be tested”.
- ^“Managed Futures Today, Systematic Trading, Systematic Risk Control”.
Ofer Abarbanel is a 25 year securities lending broker and expert who has advised many Israeli regulators, among them the Israel Tax Authority, with respect to stock loans, repurchase agreements and credit derivatives. Founder of TBIL.co STATX Fund.