Systematic investing is an investment style that can be used to build an automated portfolio in different conditions. The Systematic investing offers several benefits over conventional discretionary investing because portfolios are generated automatically by adhering to a set of criteria based on data-driven insights and sophisticated computer modelling approaches. Systematic, quantitative, or occasionally algorithmic investing are all used interchangeably as terms for investments that are based on a set of pre-defined rules, although there are some subtle differences.
Features of Systematic Investing Strategies
1. Reliance on a single portfolio manager is low:
A systematic strategy will generally be a combination of signals or factors, which could have been developed by multiple researchers. The core of the strategy is therefore defined by these set of signals or factors and this reduces the amount of daily decision-making required by the portfolio manager. The manager’s role is to assign capital to individual signals periodically and monitor their performance. Therefore, the impact of the systematic manager on overall performance is lower than that of a discretionary manager.
2. Scientific Method:
A systematic approach assumes that there is a pattern to security returns and that this pattern is sustainable, after accounting for transaction costs. The systematic investment technique includes gathering high-quality large data, doing data analysis and mining, and testing investment ideas. Typically the historical analysis is broken down into 2 parts. One to form the hypothesis called training data and one to validate it called test data. In some cases, a third part is created to test out of sample performance. Or this could be done using actual market data going forward.
Risks associated with models are reduced by following this approach.
3. Bias reduction:
A systematic investing method goes beyond discretionary investing by validating strong investment ideas. And weeding out the rest using modelling tools. This approach not only amplifies human judgment but also mitigates bias in your portfolio.
4. Scalability:
Investing systematically prevents concentration risk by constructing well-diversified portfolios that include several kinds of securities. This is accomplished by automating and quickly processing new information while keeping risks in check so that investment strategies can be implemented to their full potential. A systematic strategy can be much broader, in terms of the number of securities analysed, as the processing is done by a machine as opposed to a human.
5. Disciplined risk management
Systematic strategies generally have risk controls built into their construct. And act as the first line of defence in most market scenarios. A rigorous historical analysis ensures that most adverse scenarios have already been factored into some extent. In addition, these strategies allow for having specific exposure and risk limits on a security, sector, asset class or style level and historical simulations will account for the impact of imposing such constraints. Managers can then make an informed decision as to which risks they are comfortable with running and which they would rather reduce.
