Part II: Analytic techniques continued...
6) Do you believe the future movement of the market data is, to some extent, driven by the models used by major financial institutions, even though these models may not be correct?
Albert: Does the market move because the model is assumed to be correct? I would say yes. Consider the market crash in 1987. Prior to the crash, there was no “volatility smile,” but there was after the crash. The market had actually been acting correctly, according to the model, until they realized the model made terrible assumptions. The market moved much more than their model implied. One event is meaningless; however, this highlights an incorrect model driving the market.
For a more current example, look to the way mortgages were priced before the recent mortgage bubble. Banks priced mortgages with the assumption that housing prices wouldn’t fall. The entire market priced that way because that was what everybody else did; it was group think. They used this assumption because the price had never gone down in their historical data set. Models are only as good as their assumptions. Could somebody have built a better model and actually predicted the housing price collapse? Yes, it could have been done and a few people did it.
Unfortunately, in a time of high earnings, it is easy to ignore risk. Risk is especially underweighted when quarterly earnings are prioritized over long term security. I feel that compensation packages are lagging the culture shift at most companies. This disconnect leads people to act as individuals focused on their personal bonuses rather than acting as representatives of their company. Further, a system which provides bailouts for bad behavior begets that bad behavior. The “smart” companies wouldn’t receive a bailout, leading some to assume they are better off to employ the incorrect group think model. Of course, this would not work in a free market.
7) Does your company use stochastic models? If it does, what kind of models are used?
Albert: We primarily work with customers who have reasons for the models they use. Sometimes, they ask us to implement specific models in their system. Other times, they come to us for advice asking what model may be best. For instance, in regards to interest rates, I am a big fan of the Libor Market Model (also known as the BGM Model). It is a term structure model. However, the industry almost exclusively seems to use short rate models. The Hull-White Model is very common because it’s very easy to parameterize, simple, and everyone else is using it.
However, I enjoy commodities more than interest rates or equities. In commodities, we have different issues because it is such a physical market. These models can be much more complicated. If I picked a favorite model, it is one that I was lucky enough to have helped develop (I’m biased). That model takes the term structure for a commodity and relates it back to the spot price allowing them to be simulated together. I really enjoy working with that model. In general, my favorite model is the right model for the situation; a model that makes logical sense and fits the data.
Part III: Risk management
8) How do the recent financial crisis and the regulation policies enacted after that affect the behavior of your company?
Albert: As a vendor, our business is based on our customers’ business. A crisis like that causes additional regulation or at least the changing of regulation. To handling that regulation it is very logical that a third party, a vendor would make a solution and sell it to customers. Typically, that type of regulation would cause a company like SAS to make a new product and be able to provide that solution to more people. Unfortunately, the capital expended on satisfying regulations cannot be used elsewhere in the economy.
9) The goal of risk management is to achieve a balance between returns and risks. Thus, with lots of capital and human resource spent, risk management may, to some extent, reduce a company’s profits. Now suppose you are a leader of a financial institution. Driven by the motivation of maximizing the profits, will you pay enough attention for risk management?
Albert: As a risk professional my answer must be yes. There are two aspects to consider in regards to risk: monitoring and management. Consider risk monitoring first. One should spend resource and pay attention to know the rules of the game. For an example, let’s think back to mortgages. What if housing prices could go down? I may go bankrupt. Well, that would be very important to know. If you don’t know the rules of the game, you cannot play your best.
In the same way, you need risk monitoring to help you see what the possibilities are. In terms of risk management, it’s like getting an insurance policy. Let’s say I have a house and all my money is in my house. If my house burns down, I may go bankrupt. I should clearly buy fire insurance on my house. That’s how risk management can be considered as well. Yes, if I am concerned about anything other than the very short term, I would spend enough resource on risk management and pay attention to my risk team.
Part IV: Suggestions & Advice
10) What skill sets are important to succeed in your field?
Albert: I get asked that question often: by students, by some of my friends, and some of my peers. I change the details of my answer almost every time, but there are key components that remain consistent. First and foremost is communication. No matter how smart you are, no matter how brilliant your model may be, if you cannot convince others and if you cannot explain your ideas, it is not going to matter.
Another component in my list is passion. Passion is not a skill, but an ingredient to success. Is it necessary? No. But if you are not passionate about your field, why work in it? Your passion allows you to have better ideas and think outside of the box which is critical. If you just think like everyone else, you are very replaceable. This makes it more difficult to advance. Your passion may present itself in the form of problem solving. This is an important skill.
Another skill of importance is programming. In our field, people are often not formally trained in programming. We are more likely to be self-taught with at most one or two university courses in programming. This is very different than those people who come out of school with an entire degree in computer science. They have different level of understanding the way a machine thinks. In some parts of our field, this understanding is critical and you will need to learn it. Being skillful enough to have a computer automate you work is always important. Automation frees your time to think and add real value.
Thank you Albert for inviting us to SAS for coffee and taking the time for this fun and informative interview!