ETF Rotation Strategy

Investing 101

Rules-based investing is an investment approach gathering popularity in the investment community. This approach allows investors to design strategies based on what actually happens, rather than on what people think will happen.

Furthermore, rules-based investing doesn’t leave room for emotions to play a part in the decision making

This article is a brief guide to rules-based investing 101, to give you an idea of what it is and how it differs from traditional approaches.




Rules-Based Investing 101

The Characteristics of Rules-Based Investing

Empirical evidence

Rules-based investing has many names; quantitative investing, systematic investing and rules-based investing. Similar strategies also include Factor-based investing, smart beta, momentum investing and trend following. A common theme that differentiates these strategies from traditional approaches is that they make more use of quantitative analysis than qualitative analysis.

There are two primary characteristics that most rules-based strategies use. Firstly, these strategies exploit relationships and patterns that occur repeatedly in markets. These can be at the asset class level, or at the instrument level. The second characteristic is that signals are implemented mechanically, with little or no discretion.

Taking emotion out of the process

Any book on investing 101 will tell you that two of the biggest negative influences on investment decision-making are the emotions of fear and greed. Investors allow fear to influence them during periods of volatility. And, they allow greed to influence them during strong bull markets.

With rules-based investing, all decision-making takes place when the system is created, rather than when trades are implemented. Consequently, decisions regarding the portfolio are made with a long-term focus and without the influence of emotion. On the other hand, discretionary investments are often made on the fly, and in reaction to short-term events. Without a set of rules based on empirical evidence, there is nothing to stop emotions creeping into the decision-making process.


Most rules-based strategies rebalance portfolios on a regular basis. This can be on a weekly, monthly, quarterly or annual basis. Rebalancing a portfolio ensures that it is constructed correctly and does not drift away from the intended strategy. Furthermore, rebalancing moves profits out of outperforming assets.


Systematic investment strategies make use of hard, rather than soft data. That means that the data is measurable, and not subject to interpretation. Therefore, system developers seldom use soft metrics like management quality and analyst forecasts. Most systems will use hard data like price, volume, volatility, earnings growth and free cash flow. These data sources have the added advantage of being easier to gather.

Strategy development

Developing a strategy starts with observation. Developers may explore data themselves, or refer to academic research into patterns or relationships between asset classes. The developer will then build a basic strategy to exploit those relationships or patterns. Historical data is then used to backtest the strategy. The developer will then adjust the parameters of the system and test it once again. This pattern is repeated with the goal of finding a satisfactory balance between risk and return.

If the system generates satisfactory results it must be tested on a separate data set. This is done to ensure the system doesn’t only perform well on a specific dataset. Finally, the developer will test the system on live market data.


Because rules-based investing makes use of empirical data, the results can be more reliable than strategies that use subjective inputs. Furthermore, discretion is not used when implementing rules-based strategies. This stops emotions creeping into the decision making process.