All episodes of Chat With Traders x Quantopian mini-series are available here.
The worst case in finance is when you think you’re right, but you’re actually wrong. This can be especially dangerous when you’ve used some methodology or statistics to justify a decision, but are unaware of all the subtle biases that can cause false results. In this episode we’ll cover many of the ways that you can be wrong without knowing it in trading and finance.
Sponsored by DataCamp:
- For learning how to program, DataCamp.com is easily one of the top resources available—their online courses focus specifically on data science, stats & finance.
Topics of discussion:
- Why are the barriers of entry to quant finance so high?
- Is a certain level of secrecy necessary amongst traders?
- What is a zero sum game? And does it accurately describe trading…
- False positives, multiple comparisons bias, overfitting, data cleaning bias.
- Exotic and obscure datasets being used by quants (very sci-fi!)
“Good quants are really good at admitting when they are wrong and uncertain and don’t know stuff.”
Links and resources mentioned:
- Jupyter Notebooks
- Quantopian Lectures
- Quantopian Tutorials
- Steve Cohen, Point72, $250M investment
- Quantopian GitHub
- Spurious Correlations
- EP 090: Michael Halls-Moore
How to support this podcast:
- For a quick and easy way to support this free podcast, please write an honest review in iTunes. It’ll take you two minutes, and it helps massively—thank you.