Peter Carr Seminar Series: Chao Zhou & Eric Liverance
Chao Zhou
Qube Research & Technologies (QRT)
Title
"Convergence analysis of controlled particle systems arising in deep learning"
Abstract
This paper deals with a class of neural SDEs and studies the limiting behavior of the associated sampled optimal control problems as the sample size grows to infinity. The neural SDEs with N samples can be linked to the N-particle systems with centralized control. We analyze the Hamilton--Jacobi--Bellman equation corresponding to the N-particle system and establish regularity results, which are uniform in N. The uniform regularity estimates are obtained by the stochastic maximum principle and the analysis of a backward stochastic Riccati equation. Using these uniform regularity results, we show the convergence of the minima of objective functionals and optimal parameters of the neural SDEs as the sample size N tends to infinity. The limiting objects can be identified with suitable functions defined on the Wasserstein space of Borel probability measures. Furthermore, quantitative algebraic convergence rates are also obtained.
Bio
Chao Zhou is a Quantitative Research Director at Qube Research & Technologies (QRT). Before joining QRT, he was an Associate Professor in the Department of Mathematics and Risk Management Institute at the National University of Singapore. He earned his PhD in Applied Mathematics from CMAP, Ecole Polytechnique, in France.
Eric Liverance
Bank of America
Title
Fed Monetary Policy and Extracting Fed Funds Expectations From Market Data
Abstract
The Effective Fed Funds Rate (EFFR) is the primary mechanism the Federal Reserve uses to implement monetary policy. We give a short introduction to the Fed's mandate and how it is carried out in the market. With the transition from LIBOR to SOFR now complete, the Fed Funds Futures and SOFR markets are the main markets used to extract expectations of the EFFR. We discuss these markets and the various methodologies used to extract EFFR expectations.
Bio
Eric Liverance is a Director in Bank of America's Quantitative Strategies and Data Group (QSDG) covering the Central Funding Desk (CFD) and the USD interest rate volatility trading desk focusing on statistical hedging, relative value, and systematic trading strategies. He holds a Ph.D. in Pure Mathematics and an M.S. in Computational Finance. He has held postdoctoral and visiting professor positions from universities in Sydney, Tokyo, and LA. Since starting in finance, he has held positions as exotic rates options modeler, systematic rates and vol trader, USD interest rate derivative research analyst, and mortgage quant prior to his current role.
Meeting ID: 922 5939 9979
Password: PCBQE1015