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Risk Navigator

Published in Automated Trader Magazine Issue 37 Summer 2015

Katy Kaminski considers herself a divergent risk taker. And though this meant that she tried many different things, ultimately, she pursued her love of mathematics on a path to quantitative finance. Now, she researches divergence and convergence, and applies it to financial markets as a director of research at Campbell & Company, a US-based CTA that's been around over 40 years. We talk to Kaminski about theory, strategy and tech.

Katy Kaminski, Director of Research at Campbell & Company

Automated Trader: Why quantitative finance?

Katy Kaminski: I have a background in engineering and mathematics and spent over 10 years at MIT (Massachusetts Institute of Technology). While at MIT, I worked with my PhD advisor, Andrew Lo, a long-time expert on quants and hedge funds. He was actually running a hedge fund as well at the same time. The questions that he asked me to solve were: Why and when do heuristics work in investments? And why do we use simple rules to invest?

It started off with an early interest in heuristics, quantitative rules and systematic approaches. When I was a doctoral student in the early 2000s, I spent a lot of time studying behavioural finance. I really wanted to try to get a good idea of why we use heuristics and rules to make investment decisions.

The topic was considered somewhat too practical for most of my academic colleagues. Now, the topic is very popular, but about 10 or 15 years ago it was considered much more of a practitioner topic.

I started working at the Stockholm School of Economics and after some time there, I wanted some practical experience so I joined RPM, a CTA fund of funds located in Stockholm Sweden.

The fit was really quite natural because being an allocator to CTAs requires that you understand the model that they use, and how to decipher one strategy from another. This requires some understanding of the technical details.

AT: You're also an author. How did you move into writing?

KK: I met numerous different CTAs and started writing articles about investing in CTAs, and understanding how CTAs work. I wrote an article in 2011 that I called "In search of crisis alpha". This became a popular piece which lead to other pieces about CTA investing - momentum investing, systematic investing, futures trading, etc. After some time as an allocator, writer and researcher on CTAs, I went back to academia and decided to write a book on trend following.

While back in academia, I happened to meet Alex Greyserman, chief scientist from managed futures firm ISAM and co-author of "Trend following with managed futures". We both had a common goal to educate investors on why systematic trend following strategies work.

A book is kind of like a quest, we (Alex and I) sat down and said: what do people need to know as opposed to what do we know?

The book was similar to completing a doctorate, you have an ultimate goal and one of the exciting parts is you never know how you are going to get there. We outlined what people should know and divided up the material in certain areas. We knew good answers for some questions, but in others it was less obvious. And it's particularly those areas where the answer was not so obvious where the results became quite interesting.

AT: For example?

KK: This concept of convergent and divergent risk taking. The basic idea is that given what you believe about risk you will apply different risk taking strategies. Often we take our beliefs for granted, so when people step back and start thinking about: "What do I believe?" They may not realise how severely their beliefs about risk affects their choices. Then you can really simply explain why a systematic trend following (or divergent) approach represents one way of taking risk, whereas the convergent approach is another. And then you can easily argue that these approaches work in different risk taking scenarios over time. What has been hard for the systematic space is the black box label.

People think it is some magical box that makes the decision, but systematic trading is rules that we make up that we implement systematically to help ourselves make decisions which are difficult for us to do discretionarily. This is why they are "long divergence" and often tend to do well when making discretionary decisions becomes difficult.

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