Simon Clinet - Appointed in AY2017
Participant Profile
Simon Clinet
Financial Econometrics2013 Engineering degree, Department of Applied Mathematics, The Ecole Polytechnique 2014 Master of Probability and Finance, University of Pierre and Marie Curie 2017 Ph.D, Graduate school of Mathematical sciences, University of Tokyo Assistant professor at the Faculty of Economics, Keio University since September 2017
Simon Clinet
Financial Econometrics2013 Engineering degree, Department of Applied Mathematics, The Ecole Polytechnique 2014 Master of Probability and Finance, University of Pierre and Marie Curie 2017 Ph.D, Graduate school of Mathematical sciences, University of Tokyo Assistant professor at the Faculty of Economics, Keio University since September 2017
I aim to increase our understanding of stock prices and their characteristics.
My Research Theme and How I Came to It
I have been working on high-frequency financial data and related topics since I was a graduate student in Paris. I met there many specialists on my topic who helped me understand the importance of their research. Recent availability of very large data sets coming from stock markets has made possible the creation of many statistical methods designed to better understand the price structure of stocks. That is why a year later I came to Tokyo to work on the same topic with Pr. Nakahiro Yoshida as a Ph.D student. Together, we could further study the general statistical modelling of financial data, and this long experience gave me the incentive to prolong my research on financial econometrics.
The Appeal and Fascination of My Research Theme
In recent years, understanding stock markets has become fundamental as our world tends to be more and more finance-driven with globalization. My field of research is fairly new and has been developing very fast over the past decade. It aims at using efficient statistical methods on (potentially large) high-frequency financial data sets in order to extract key quantities of interest (such as the volatility of a stock). The major hurdle that one has to overcome is that often stock prices are contaminated by noisy (irrelevant) information. Thus, disentangling price and noise is very challenging and is at the core of my current research.
Message for Students
I recommend that you study what you are really interested in as much as possible. But if you can, try to learn a few notions of statistics as well ! As a future active member of our modern society, you will be confronted with a lot of information and many diverging opinions. It is not always easy to understand what is a fact and what is not. Understanding statistics is not an easy task and may seem burdensome, but nowadays it has become essential in order to understand our big data-driven world. Read the news, watch TV. Listen to politicians. You will see that (even an elementary knowledge of) statistics is what will always help you step back and have a look at the overall picture !
(Interview conducted in December 2017)
*Profile and position are current as of the time of the interview.