How do you avoid overfitting, how loose is too loose in terms of loose pants and how should you approach sample sizes when designing your trading systems? What are complex adaptive systems, how do they apply to financial markets and why does regular math just not cut it? How does trend following differ from other strategies, what makes trend following so robust and what are the limitations for traditional statistics? Join us for this fascinating conversation with Richard Brennan.

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Episode TimeStamps:

01:04 - What has been on our radar recently?

03:08 - Industry performance update

08:21 - Q1, Adam: In terms of loose pants, how loose is too loose?

13:36 - Trading with different models

15:42 - Adam Q2: What is a reasonable sample size in real trade observations, to compare against backtest statistics?

18:23 - A deep dive into complex adaptive systems (CAS)

20:29 - The 5 properties of CAS

25:24 - Examples of non-linearty in financial markets

30:50 - Emerging properties in financial markets

33:59 - Self organization

36:33 - Adaption and evolution

40:10 - Feedback loops

43:11 - What does CAS and trend following have in common?

49:38 - The limitations of traditional statistics

01:01:14 - Summing it all up

01:04:48 - What's next?

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