Common Quant Research Mistakes and How to Avoid Them
Beyond your typical "Don't overfit"
Whenever anyone talks about beginner mistakes in quant, it’s usually stuff like “you shouldn’t overfit” or “be careful about look-ahead bias”. While this advice does have a place, we will give some less common advice here and talk about mistakes that are often made that aren’t talked about enough, how to diagnose if you’ve fallen victim to them, and how to mitigate them.
I write about quantitative trading the way it’s actually practised:
Robust models and portfolios, combining signals and strategies, understanding the assumptions behind your models.
Topics I write about include portfolio construction, market making, risk management, research methodology, and more.
If this way of thinking resonates, you’ll probably like what I publish.
What you’ll learn
Common mistakes people make in quantitative research, and why they happen.
How to diagnose if you’ve fallen victim to any of the mistakes.
How to concretely mitigate the mistakes.