... Federico Bandi
Let me ask about a recent magazine story that lauded your work applying high-level mathematical models to financial markets. Apparently you can explain the flash crash!
[laughs] I have not worked directly on it, but I have my opinions. As one would expect, very large sell orders can determine substantial downward price impacts. In times of high-frequency trading, these initial downward swings can be easily exacerbated by additional orders on the same side of the market. The buy side can work similarly.
You and some colleagues have devised a new market indicator called EXIT, measuring idle time in financial pricing. Could you say more about it?
EXIT is an acronym for EXcess Idle Time. In a nutshell, it is a market friction indicator capturing the extent of staleness (or idle time) in observed high-frequency market prices. One could imagine markets as being populated by informed agents (who have some awareness of the fundamental value of an individual asset) and uninformed agents. Uninformed trading decisions amount to little more than tossing a coin to determine trades. Informed decisions are more complex, but they are still intuitive provided we simplify them a bit: Informed agents will buy at the prevailing ask price when the fundamental value is higher than the ask value, they will sell at the bid price when the fundamental value is lower than the bid price, and they will sit idle if the fundamental value is within the quoted bid/ask spread. EXIT is designed to quantify staleness in prices as determined by slow trading or lack of it.
I imagine that EXIT would be particularly interesting in this era of high-frequency trading.
Yes. We've seen renewed awareness that liquidity is an elusive concept with many facets. Its classic definition ("the ability to trade large amounts in a short period of time without considerable price impacts") has three dimensions—volume, price, and time. There is an important interaction between liquidity and asymmetric information, another pervasive market friction. EXIT is formulated to capture this interaction. It is simple to implement empirically, which is a nice feature. It turned out to be a bit less obvious to study formally in terms of its mathematical properties. This study has led to some interesting technical findings, which we believe to be broadly applicable in other areas of high-frequency asset pricing.
You came to the Carey Business School in 2009 to be the chair of the Finance and Economics Committee. What does this involve and what do you see as the Carey School's future?
I was brought on to build the finance and economics side of the business school. Our goal as a school is to be a critical player in business research and training MBAs. In both the part-time MBA and the Global MBA programs, we emphasize areas that other schools do not and that play to the key strengths of Johns Hopkins: health care, real estate and infrastructure, enterprise risk and national security, and financial businesses.
How is social responsibility part of your curriculum?
We stress the necessity of having a conversation about social responsibility in several areas of business training and thinking. We would like this conversation to be technical, rather than ideological. My guess is that social responsibility will be, going forward, a pervasive element of the entire curriculum, not simply of individual courses.
When you're not doing higher math, what do you do for fun? Or to bring yourself down to earth?
Latin dancing! I started about 10 years ago. It's hard to find the time these days and I don't compete, but I'm a serious club dancer. It's easier when I travel, actually. I could find a hidden salsa club in Jakarta in 15 minutes. I've done it! It is a responsibility to be the best bachata dancer in the world, but it is one that I gladly take upon myself. [smiles]
Do you see any link between dancing and mathematics?
They both keep me on my toes.