Dave Bergstrom Interview - Chat With Traders Episode 103

In this episode, we’re joined by Dave Bergstrom, a quant trader at a high frequency trading firm, who surprisingly enough started out on the same path of many retail traders.

Unlike many of our previous podcast guests, Dave is unique from many traders due to his methods of using data-mining techniques to develop trading strategies. You may have a poor association with data mining in trading, but Dave posits that this is rooted in bad practices and poor evaluation of methods.

On top of the reasons why data mining has a negative connotation in trading, we also discuss escaping randomness, how to reduce curve fitting, learning to write code, setting expectations, Dave’s three laws for strategy development, and tons more.

What’s Covered in This Interview:

Why Dave couldn’t “escape randomness” at the start, how he ended up at an HFT firm, and the reason for becoming a more data-driven trader.
Dave’s drive to learn how to program, in multiple languages, and how it’s pretty much like having “superpowers,” plus a handful of tips to learning the basics of programming.
What’s so great about data mining? Dave gives us his high-level overview for how he gets an edge by mining data and the ways he reduces curve fitting.
The “three trading laws” Dave abides by when developing strategy, the pros of variance testing, and how Monte Carlo analysis helps set up realistic expectations.