Curve Fitting Trading

Are you tired of hearing about “guaranteed” trading strategies that end up causing more harm than good? If so, you may have fallen victim to the dangerous practice of curve fitting.

This article will explore curve fitting, why it’s dangerous, and how to avoid it. We’ll also provide some strategies for reducing curve fitting and improving your chances of success in the market.

What is curve fitting trading?

In the world of trading, curve fitting, aka overfitting, is creating a strategy that fits historical data so closely that it fails to perform well in the future.

But you’ll be thinking, “oh, but why does it fail? Isn’t looking at the historical data good?”

Not quite!

A strategy tailored to historical data may work well in a specific market condition, but it falls apart as soon as conditions change.

When you rely too much on backtested data, it can lead to over-optimization of trading strategies, resulting in strategies that worked well in the past but failed to perform well in real-time trading.

When talking about curve fitting, we have to talk about its’ two types; parameter fitting and strategy fitting.

Parameter Fitting

It involves adjusting the parameters of a trading strategy until it fits historical data perfectly. For instance, you may tweak the settings of technical indicators, such as moving averages or oscillators, until the strategy matches past market conditions.

However, this can lead to an overly complex strategy that cannot adapt to changing market conditions.

Strategy Fitting

This involves creating a strategy that perfectly fits historical data by incorporating specific market conditions, such as trend direction or volatility.

However, this can lead to a too narrowly focused strategy and an inability to adapt to changing market conditions.

How to avoid curve fitting in trading strategies?

While curve fitting can be dangerous, there are some approaches you can use to avoid curve fitting. They are:

Keep it simple

Avoid creating overly complex strategies that rely on many indicators or parameters. Instead, focus on a few key indicators that have proven effective in different market conditions.

Simpler strategies are more adaptable and can perform well in various market conditions.

Avoid over-optimization

Avoid adjusting the parameters of a trading strategy to fit historical data too closely. Instead, you should balance fitting historical data and creating a strategy that can adapt to new market conditions.

Regularly monitor performance

Regularly monitor the performance of a trading strategy to ensure it is still effective in current market conditions. If a strategy is not performing well, you need to re-evaluate and adjust the strategy to fit current market conditions better.

Diversify trading strategies

You must diversify trading strategies across different markets, asset classes, and timeframes. This reduces the risk of over-reliance on a single curve-fitted strategy and can help capture profitable opportunities.

Final thoughts

Curve fitting is a common problem in trading and can lead to losses in trading and false confidence in a strategy’s effectiveness. By using the methods above, you can avoid curve fitting and improve your chances of success.