Rong Chen - Rutgers University
Sequential Monte Carlo and its Applications in Finance
Date: 10/16/2014 (Thu)
Time: 3:30pm- 5:00pm
Location: Seminar will be held on-site: NISS: 19 T.W. Alexander Drive, Research Triangle Park.
Organizer: Andrew Patton
Meeting Schedule: Login or email the organizer to schedule a meeting.
All meetings will be held in the same location as the seminar unless otherwise noted.
10:30am - Rong is arriving to Duke at 11am
11:00am - Andrew Patton
11:30am - Tim Bollerslev
12:00pm - Lunch with Andrew Patton and Jia Li
1:00pm - Matt Masten
1:30pm - George Tauchen
2:00pm - Shakeeb Khan
2:30pm - Federico Bugni
3:00pm - Travel to NISS
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
5:30pm - Dinner with Federico, Shakeeb, Denis at Capital City Chop House
Additional Comments: Abstract: Sequential Monte Carlo (SMC) method is a class of Monte Carlo methods that are especially powerful in dealing with nonlinear and non-Gaussian state space models and other complex dynamic systems. By using a set of random samples to represent the underlying conditional distribution of the states given all available observations, and sequentially updating the samples through time to track the dynamic changes of the states, SMC is able to efficiently provide online inference and prediction of the unknown states in the system. In this talk we provide a general overview of SMC under a generalized framework, and discuss several applications of SMC in finance, including modeling and inferences of the risk neutral densities dynamics, yield curve dynamics, return dispersion dynamics, generating diffusion bridges, and others.