Next Finance: After your famous book The Complete Guide to Option Pricing Formulas which helped all the traders to make theirs spreadsheets, what’s next à réaliser leur spreadsheets, qu’avez-vous de nouveaux dans les bacs ?

Espen Haug: Next is my forthcoming book Derivatives Models on Models with Wiley publishing. Just now I am doing the last proof reading. It should be out in April/May 2007. This is very different than my Option Pricing Formulas book, and I would say very different from any other derivatives book. I have interviewed 16 expert modelers, philosophers, traders, and quants from the industry and academia about their models and their ideas. To do the interviews was very interesting and I learned a lot. I think also many readers will find this part particular interesting. The book also has a series of technical chapters about everything from traditional derivatives valuation to out-of-the-box ideas like Space-time finance and negative probabilities. In addition the book has a more entertaining part including a colorful midsection with derivatives comic strips. The book is also the first of its kind containing some Quantitative-Finance Art --- basically some artistic photos and oil paintings and cartoons all directly related to quantitative finance.

Together with Oslo Stock Exchange I will in May have the first ever quantitative-finance “art exhibition” in Oslo. It will be in connection to the launch of my new book. Possibly I will move my art exhibition along to London or New York or may be I should try Paris as people there tend to be more open minded to “crazy” ideas? Combining art with quantitative finance and derivatives will hopefully make quantitative finance less of a mystery for most people, or possibly it will make it even more mysterious? Anyway I am looking forward to see people reactions, if any.

Also I have ideas for writing a few more books. I want to write a book about practical option trading, another book about physics, and another book about my life as a trader. The problem is to find time to write them. And to write a book always is three times as much work as expected, at least for me. I look forward to a potential future where I can download the books I already have written in my head and have them printed in a day or two. Or alternatively broadcasted it wireless. I hope at the same time someone has come up with very a good firewall so nobody can hack into my beautiful mind.

I am also playing with the idea of setting up my own hedge fund. Or what I would like to call an Anti-Hedge Fund. That is a hedge fund that will be negative correlated to the typical positive carry hedge fund, at least for big movements in the market. Yes so it is a hedge fund, but with a unique strategy that is based on robust-hedging principles, not on model hedging and or principles that only hold in a fantasy world or at the university campus.

Next Finance: You have worked for J.P. Morgan Chase in New York as a proprietary option trader, and also for the hedge funds Amaranth Advisors and Paloma Partners as an option trader . In what kind of strategies were you involved ?

Espen Haug: I was involved in trading a series of asset classes, markets and instruments; FX, fixed income, commodities, equity and at one point even electricity. In particular I use a lot of options and derivatives with convex pay off in my trading. Convex pay off is my specialty. And even if I have written very little about it, tail events has actually been my main interest since I started my professional trading career. It was actually the crash of 87 that got me interested in options and tail events. During my first years in the hedge fund industry I worked in an office space next to Nassim Taleb’s trading operation. I got interested in tails long before that, but I certainly find his writing and ideas very interesting.

I use a lot of quantitative tools in my trading. But I don’t believe in black box trading, in particular not when it comes to option trading, so I combine it with deeper concepts of randomness, very long times series of empirical data and trading experience. In particular I relay on robust hedging and valuation principles, some of them described in my Derivatives Models on Models book. Most hedging principles described in the academic literature are non-Robust, that is they fail in big time under certain practical relevant scenarios. One of the most important aspects of studying quantitative finance is to find the flaws in the models used by the market. Now if you know other traders use such models and hedging principles without fully understanding their flaws you can potentially put on good relative value bets taking advantage of such model traders. So much of my quantitative insight is actually to take advantage of flawed quantitative models and other traders trusting such models or principles

Next Finance: The success of algorithms trading leads some to say that Machines will replace traders, do you agree with this?

Espen Haug: Machines will and probably should replace the average trader, because I am not impressed with the average positive carry trader selling hidden risk dimensions claiming he is a genius beating the market (until he blow up). A machine or chimpanzee throwing random darts at Wall Street Journal to pick a portfolio of assets will probably do far better than these traders in the long run.

To answer your question we also have to define what is a machine and what is a trader. Humans program computer algorithms and build computers. So computerized trading can simply be seen as having a machine doing the boring part of the job. That is executing your orders based on a set of instructions. Instructions hopefully made by a good quant or quant-trader. Machines are still not good at programming themselves, even if work is going on in this area. So machines are at the moment simply tools used by quants and traders. Or do a trader need to execute the trades to be considered a trader? If I as a trader can sit on the beach or walk in the mountain and think about the big pictures and the deeper philosophical aspects of randomness and get it programmed into a computer executing my trades that would be a wonderful thing. Why should execution traders be highly paid if we can replace them by machines and software?

Another aspect of having a machine/computer algorithm executing the orders is that in this way more of the money can potentially go to the quants that actually came up with the smart ideas. In several trading floors, the people coming up with the good ideas are programming it into a tool. The tool (software) is handled over to the traders. These traders that in some cases relay a lot on such tool to make money are taking 90% of the bonus pool. Some of these traders are often simply doing advanced execution. Some times they not even fully understand the model they base their trading on. In some circumstances it would be better to have the quant running the model and execute the trades through a computer. On the other side many if not most models quants and academics come up with are flawed and non-robust and only works in practice because traders are fudging them based on market experience.

I also know firms where the business idea is to strip successful traders and quants for their knowledge. The idea is to have them to program all their knowledge into computers and then make the software and computerized trading strategies the property of the firm. Such firms tend to have strict non-compete agreements and contracts that strip idea makers for their intellectual property. In this way the top management can pay these people lower, and easily replace them as they have put down most of their knowledge in a computer program. The result is that the politicians on the top are getting most of the money, managers that have raised to the top based on politics are always good at coming up with good deals for themselves. If a firm wants you to give a way all your intellectual property make sure you get paid for it, if not simply leave that firm.

When it comes to my own trading strategy it is far to complicate to turn it all into a computer program at current time. The reason is that humans also are machines. But currently I am a much smarter machine than most computers. So part of my strategy I can program into a computer, the boring repetitive part. However it has to be combined with my trading experience that not that easy to get into a computer. Traders that can take their whole trading strategy and experience and turn it into a black box are probably themselves not very smart machines. Such models have a tendency to work well for some time, until they stop making money or even worse blow up. Almost any computerized trading system are based on back-testing on historical data. The future is not the history. This is particular true when it comes to extreme events and tail probabilities. Today we have models to match historical fat-tailed distributions and we can calibrate models to for example what is known as the volatility surface. But it is the future that counts, and many traders ignore the fact that we actually not can come up with good estimates for future tail probabilities, something I guess has been pointed out several times by Nassim Taleb, Benoit Madelbrot and others. The best firms know this and they have quants and quant traders continuously overseeing their computerized trading models. It looks like computerized trading, but actually it just the computer doing all the repetitive work. The brain behind the few great money-making ideas are still the human brain, not some computer chip. This could at some point in the future change, but we still have a long way to go.

Next Finance: What are you main research studies now? And how do you see the future of financials markets ?

Espen Haug: The last few years I have been studying some very fundament aspects of the markets and the nature, and I think I have found something very interesting, something unexpected. If I am right my study will have effects reaching far outside the field of finance, alternatively I will look like a fool, but I am not afraid to look like a fool. The downside is very limited and the not even the sky is the limit. Most important an enormous amount of empirical data seems to confirm my theory. Possibly standard theories can also explain what the empirical data shows. That is if they just add a few more layers of complex mathematics to confuse our minds. If something has a very simple and fundamental explanation and the alternative explanation is extremely complex, than the simple explanation should win. At least until empirical data or logic proves something else. And I think I have the simple explanation possible. What am I talking about? Well that is a secret, but I will try to publish my idea in 2007/2008?

Beside this I will also try to write more about how traders actually trade and price options. During a sabbatical from trading (only trading my own money) I could finally see how what I felt was a conflict between practical options trading and theory could be solved. My little insight here can be found in chapter 2 of my new book Derivatives Models on Models. Basically I am just putting tougher all the bits and pieces of what has been a model puzzle. All the bits and pieces have been laid out before me, but I have not seen them put together in this way before. I mean the right way (laughs)

Concerning the future of financial markets, I think we are at the beginning of a regime switch in quantitative finance models. The empirical evidence against the classical models and ideas are over helming. For example the equity premium puzzle is not a market puzzle, but a model puzzle. A puzzle created by the modelers themselves, because they use flawed risk measures. Most academic models are made to be consistent with other academic models, not to be consistent with empirical data. Also here adding a layer or two of advanced mathematics researchers has tried to fix this problem. I think we are on the wrong track. We need to go down to the very fundament of randomness and the fundament of robust hedging principles and develop new robust models. Before we can make models consistent with empirical data we also need to understand the empirical data. I think we simply do not understand what the empirical data are telling us, simply because few of us spend time thinking about such questions at a deeper level. I think most great discoveries are ahead of us, not behind us. I think we are in for big changes both in market prices and in the evolution of quantitative finance!