It’s truly a great pleasure for me to be at the University of California at Berkeley today. Not quite 50 years ago, when I was an undergraduate studying physics in Cape Town, I began applying to go to the United States for graduate school. It seemed to be the right thing to do if you were serious about your field. So I applied to three schools: Columbia, because I knew someone in Cape Town who had just gone there, and because it was in New York City; Caltech, because Feynman was there and had recently been awarded the Nobel prize and also published the stylish and insightful Feynman lectures on physics, though I didn’t understand at the time what he had actually accomplished; and Berkeley, because it was in the news for the start of the revolts against arbitrary authority on campus.

The note titled,” More than you ever wanted to know about Volatility Swaps”, written by Derman, Demeterfi, Kamal and Zhou, is a fantastic fifty page write up highlighting many aspects of valuing a variance swap and a volatility swap. I love the structure followed in the note. Instead of heading right in to the math behind valuation, the paper gives starts off by giving a superb intuition into the need for variance swap and how does one go about pricing a variance swap with nothing more than common sense.

The article titled, “The Log Contract”, is a 20 year old article. It was first article that made a case for the need for a new instrument to hedge volatility. There is something nice about papers written in the old times. The authors give a healthy intuition about the stuff they are about to explain in the paper, use simple equations that do not require too much of “head banging” and at the end of it, the reader pretty much gets the gist of the paper.

[youtube https://www.youtube.com/watch?v=4OBLAW7oQYo?rel=0]

The paper titled, “A Simple Long Memory Model of Realized Volatility”, is one of the most cited papers in the area of long memory volatility models. One typically assumes that log prices follow an arithmetic random walk. In this kind of set up, it has been shown in the previous research that integrated volatility of Brownian motion can be approximated to any arbitrary precision using the sum of intraday squared returns.