Rule based investing strategies refer to strategies that follow a pre-defined set of rules to make investment decisions. These rules can be based on technical analysis, fundamental analysis, or quantitative models. The key advantage of rule based strategies is that they are systematic and backtestable. However, they can be inflexible and fail to adapt to changing market conditions. This article will analyze the composition, methods, advantages and disadvantages of rule based investing strategies, and compare them to discretionary strategies.
Common methods for formulating rule based investing strategies
There are several common methods used to formulate rule based investing strategies:
1. Technical analysis: Using indicators like moving averages, RSI to generate buy and sell signals. For example, a strategy may buy when the 50-day moving average crosses above the 200-day moving average.
2. Fundamental analysis: Screening stocks based on financial ratios like P/E, P/B ratios and defining rules to select stocks that meet the criteria.
3. Quantitative models: Developing statistical, machine learning models to predict stock returns and generating trading signals based on model outputs. These complex models can uncover non-linear relationships and interactions between multiple factors affecting stock prices.
4. Combination methods: Many strategies combine both technical and fundamental factors in the rule formulation process to benefit from both.
Advantages of rule based investing strategies
There are several key advantages of rule based investing strategies:
1. Systematic: The rules are precisely defined, backtested and executed systematically without emotions influencing decision making.
2. Backtestability: Historical data can be used to backtest the strategy and analyze its past performance.
3. Versatility: Rules can be formulated around many different trading philosophies like trend following, mean reversion, momentum etc.
4. Risk management: Stop losses, position sizing and other risk metrics can be programmed alongside the entry and exit rules.
5. Scalability: Once coded, rule based strategies can be easily scaled to multiple markets and asset classes.
Disadvantages and risks of rule based investing
While rule based strategies have merits, they also come with the following disadvantages:
1. Overfitting bias: Formulating too many complex rules creates a modeling bias leading to overfitting of historical data.
2. Lack of flexibility: Rules fail to adapt to evolving market conditions and changing macroeconomic regimes.
3. Crowding: Similar rules used by many investors simultaneously can exacerbate price shocks and liquidity events.
4. Programming errors: Coding errors can lead to incorrect execution of trades.
Overall, rule based strategies, while relatively easy to implement, require finding the right balance between complexity and robustness. A simple strategy with a few meaningful signals generally performs better out of sample than an overly optimized complex strategy.
Comparison to discretionary investing strategies
Discretionary investing strategies rely more on human judgment rather than just rules. For example, traditional stock picking analysis done by fund managers fall under discretionary strategies. While discretionary strategies can adapt better to changing markets, they often suffer from emotional biases, lack of consistency and difficulty in backtesting historical performance.
Ultimately both rule based and discretionary strategies have pros and cons. Many quant funds start with rule based strategies to eliminate biases and over time incorporate more discretionary overlay on top of the rules to improve performance. The future of investing is likely going to involve a hybrid approach combining quantitative rules with human discretion.
In summary, rule based investing strategies, while systematic, can suffer from overfitting and lack of flexibility. Combining rules with human discretion can potentially improve on these limitations.