Simple Trading Strategies: The Power of Simplicity in a Strategy For Maximizing Profits Explained

The mantra for successful trading is to keep it simple and easy, this is the backbone of any trading strategy.

In this article, we look at some simple trading strategies and why they normally outsmart their complex counterparts.

Why Simple Trading Strategies Prevail

Let’s look at some arguments for why simple trading strategies are better than complex ones:

Fewer Variables, Greater Success

Simple trading strategies with just a handful of variables or parameters should consistently outperform their complex counterparts.

Complexity often leads to increased chances of errors and curve fitting. The key is to create multiple simple strategies that complement each other, adhering to the principle that less is more in the world of trading.

The more variables you have, the more likely you are curve fitting the dataset. And if you curve fit, the chances are low it will help up in the future. Please read our article about why street smarts beat book smarts in trading.

Street Smarts Trump Book Smarts

In the context of trading, street smarts take precedence over book smarts. Building and implementing simple automated trading strategies and edges form the foundation of successful trading. The emphasis is on a few variables, ensuring that the strategies remain robust and adaptable.

The fewer variables you have, the more adaptable it is to changes in the markets. 

List of Simple Trading Strategies

The Power of Simplicity

Experience Trumps Complexity

Contrary to common belief, trading success is not about the complexity of strategies.

Instead, it’s about generating and testing simple ideas. Experience plays a crucial role in this process. Seasoned traders understand that solving complex market problems requires simplicity, not intricate formulas or exceptional coding skills.

Building trading strategies involves some element of curve fitting, and that is why you need some experience. Backtesting is very much a trial-and-error task where you build experience. This is a long-term process – we are talking many years. Rome was not built in a year, and this applies very much to trading. 

Overcoming Bias and Building Strengths

Experienced traders focus on overcoming trading biases, avoiding weaknesses, and capitalizing on strengths.

Additional complexity often leads to overconfidence and curve-fitting, diminishing the accuracy of trading hypotheses. The goal is to remove variables, not add them, to create strategies that stand the test of time.

Solving Trading Challenges with Simplicity

Psychological Explanation

Research suggests a psychological explanation for the preference for complexity. People tend to choose solutions that involve adding new elements rather than removing existing components. This phenomenon is applicable not only in trading but also in various problem-solving scenarios.

The more complex – the more impressive. But think about the Turtle Trader project by Richard Dennis in the 1980s. None of the strategies are for rocket scientists. The strategies are very simple, yet we tend to overcomplicate things by adding variables. 

We tend to add variables when things are not going as planned. “If we only add this variable.” But you need to be very careful to avoid this mindset. Of course, some changes might be warranted, but you need a rational reason for changing a strategy. And above all, you need to think long term. 

Removing Elements for Better Solutions

Removing elements, a seemingly radical idea for many, can lead to better solutions. This principle is highly relevant for traders and those interested in quantifying problems.

The most effective trading strategies often rely on a few simple models, debunking the misconception that success requires complexity.

Why Trading Is Difficult

Multidisciplinary Nature of Trading

Unlike careers in engineering or veterinary science, trading demands a diverse skill set. It involves elements of math, psychology, game theory, history, and more.

The complexity arises from the multitude of criteria that can be incorporated into a trading strategy, making it highly susceptible to change and uncertainty. But again, the more variables you put in, the less likely is the strategy to work in the future. 

The Wisdom of Simplicity

In trading, as Rory Sutherland emphasizes in his excellent book called Alchemy, simplicity is key. Multiplying complexity often results in compounded problems. We tend to get better confidence the more information we have, but this is often flawed. 

Conclusion

In the world of trading, simplicity is supreme. Seasoned traders advocate for simple, time-tested methods over intricate and complicated strategies.

The goal is not to add complexity but to remove complexity: to strip away unnecessary variables, creating robust and reliable trading strategies. As the age-old saying goes, “Keep it simple, and success will follow.”

FAQ:

Why are simple trading strategies considered better than complex ones?

Simple trading strategies are preferred because they have fewer variables, reducing the chances of errors and curve fitting. Complexity often leads to overfitting datasets, making strategies less adaptable to changing market conditions.

How does experience play a role in the success of simple trading strategies?

Trading success is not about the complexity of strategies but about generating and testing simple ideas. Experience plays a crucial role in building and implementing simple automated trading strategies. Seasoned traders understand that solving complex market problems requires simplicity, not intricate formulas or exceptional coding skills.

What is the psychological explanation for the preference for complexity in trading?

Research suggests a psychological tendency to choose solutions that involve adding new elements rather than removing existing components. Traders may overcomplicate strategies by adding variables when facing challenges. The key is to overcome biases, avoid weaknesses.

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