Seminar | September 14 | 3:10 p.m. | 340 Evans Hall
Vadim Gorin, U.C. Berkeley
Cointegration is a property of an N-dimensional time series, which says that
each individual component is non-stationary (growing like a random walk),
but there exists a stationary linear combination. Testing procedures for the
presence of cointegration has been extensively studied in statistics and
economics, but most results are restricted to the case when N is much
smaller than the length of the time series. I will discuss the recently
discovered mathematical structures, which make the large N case
accessible.
On the applied side we will see a remarkable match between predictions of
random matrix theory and behavior of S&P 100 stocks. On the theoretical
side we will see how ideas from statistical mechanics and asymptotic
representation theory play a crucial role in the analysis.
CA, alanmhammond@yahoo.co.uk, 0000000000
Alan Hammond, 000000, 510-00000000