TTU34: The Art of Risk Management ft. Luc Van Hof of Capital Hedge – 2of2

Top Traders Unplugged

Niels Kaastrup-Larsen

Business, Business News, Investing, News

4.8 • 670 Ratings

🗓️ 25 September 2014

⏱️ 82 minutes

🔗️ Recording | iTunes | RSS

🧾️ Download transcript

Summary

In the second part of our interview with hedge fund founder Luc Van Hof, we dive into the philosophy and creation behind his trading models. We also discuss why he is a risk averse person, what hobbies help him stay focused at work, and what investors and fund managers can do to grow their business and trade smarter.

Welcome to Part 2 of our conversation with Luc Van Hof.

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In This Episode, You’ll Learn:

How to avoid model decay and how to avoid the risk when the model may stop working in the future.
How to diversify your types of models – dynamic filtering that takes place. Automatic de-leveraging when a certain market goes down.
How Luc chooses his models and why he does:
Short term trend following
Short term mean reversion
What concepts for his models repeat themselves over and over again, pattern recognition.
About volatility risk premium strategies.
How he tests his models that have so many moving parts in short timeframes.
His views on position sizing.
What investors should look at in terms of risk management
Maximum Exposure for a trade – determines the maximum risk that a trade can generate for the total of the portfolio.
How Luc deals with drawdowns.
Why he is a risk averse person.
Why he is still researching other trading ideas when he thinks he’s found a way that mitigates risk effectively.
How he gets his ideas from math puzzles, reading about geometry and logic.
Why investors should look at the predictability of returns and how to convince investors what and how you are going to trade is something that is going to work.
Why discipline is the main characteristic that people need to be a successful fund manager.
The books that he recommends for managers starting out wanting to be successful.
How his hobbies such as nature, reading, and music help to keep him balanced in a busy financial world.

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Resources & Links Mentioned in this Episode:

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Transcript

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0:00.0	You're listening to Top Traders Unplugged, episode number 034, where I continue my conversation with Luke Vanhoff, founder and CEO of Capital Hedge.
0:12.6	This episode is sponsored by Swiss Financial Services.
0:16.9	Welcome back to Top Traders Unplugged, where the best traders in the world come to share their experiences, their successes, and their failures.
0:24.9	Let's rejoin the conversation with your host, veteran hedge fund manager, Niels Kastrop Larson. It's not going to be extremely high, it's not going to be extremely low.
0:45.3	We know it's going to be probably in that confidence interval.
0:48.3	And then you have a better, I think, probability of reaching your objective in terms of what you were hoping for in terms of
0:56.8	risk and return let me let me try and and and and give you a real life example and and I want to
1:06.0	hear sort of your feedback because I think there are a lot of traders and investors out there who probably have
1:12.8	similar experiences. Now, we've done a lot of research in the strategies that I've been involved in,
1:20.6	and some of it has been in the relatively short-term space. And all I can say is that the research
1:26.6	were very robust and no optimization,
1:31.7	lots of different markets and certainly tested across, you know, different markets as you
1:37.9	suggested and all the numbers going back, you know, 15, 20 years looked really robust.
1:44.5	Then comes along 2010, 11, 12.
1:49.2	I don't remember exactly when it is, but there is a time in that period,
1:54.3	and 13 in particular, as far as I recall, where the performance really changes.
2:01.1	And I just wonder what it is that you do differently to, because it seems to me that you
2:10.4	somehow can, and I don't know whether it's filtering in order to, because some of these
2:16.2	models will go for a long time working fine,
2:19.6	but there tend to come a time in a model's life. And especially in the short-term trading space
2:27.2	where a lot of firms would argue that there is, you know, decay on models life to down to even two
2:33.7	years and then they have to come up with
	...

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