Tuning to past data until it fails live. Fitted to noise.

Faster indicators are usually:

Noisier. They react more but give more false signals.

A good strategy should:

Make logical sense. Logic plus testing.

Lag, Noise and Overfitting

Why indicators fail and how to avoid curve fitting.

Smoother indicators lag more, faster ones are noisier. You cannot remove both problems. Choose the trade-off that matches your timeframe.

Overfitting means tuning settings until they look perfect on past data. They then fail on new data. To avoid it, use common settings, test on separate periods and keep rules simple.

A strategy should make sense logically, not just statistically. If you cannot explain why it should work, be suspicious.

Key takeaways

Smooth = lag, fast = noise
Overfitting looks perfect on history and fails live
Keep rules simple and logical

Quiz

Overfitting means: Answer: Tuning to past data until it fails live. Fitted to noise.
Faster indicators are usually: Answer: Noisier. They react more but give more false signals.
A good strategy should: Answer: Make logical sense. Logic plus testing.

Educational content, not financial advice.