# Weekly Seminars

**2007 – 2008**

##### Abstract

This is joint work with Q. Yao, London School of Economics.

October 11, 2007

## Asger Lunde

*Aarhus School of Business, Denmark*

## Bipower Variation with Noisy Data (Paper)

##### Abstract

October 19 and 20, 2007

## Stevanovich Center 2007 Conference on Credit Risk

November 2, 2007

## Yazhen Wang

*National Science Foundation*

*University of Connecticut*

## Modeling and Analyzing High-Frequency Financial Data

##### Abstract

November 9, 2007

## Amir E. Khandani and Andrew W. Lo

*Massachusetts Institute of Technology*

## What happened to the quants in August 2007

##### Abstract

November 16, 2007

## Alexander Lindner

*Technische Universität München, University of Marburg
University of Braunschweig, Germany*

## A continuous time GARCH process driven by a Levy process

##### Abstract

November 30, 2007

## Amil Dasgupta * *

*London School of Economics
Centre for Economic Policy Research*

## The Price Impact of Institutional Herding

##### Abstract

December 10, 2007

## Dale Rosenthal

*The University of Chicago*

## Signing and Nearly-Gamma Random Variables

##### Abstract

December 12, 2007

## Ilze Kalnina* *

*London School of Economics*

## Subsamplig High Frequency Data* *

##### Abstract

##### Abstract

*n*, and with round-off errors

*αn*tending to zero, of a diffusion process. We give from this sample an estimator of the integrated volatility of the asset. Our method is based on variational properties of the process. We prove the accuracy of our estimation procedure is

*αn*

*∨ n−*1

*/*2. We also give limit theorems in the case of a homogeneous diffusion.

January 11, 2008

## Nassim Taleb

## From Practice to Theory, the Origins of Model Error: Preasymptotics and Inverse Problems in Quantitative Finance

February 22, 2008

## Stathis Tompaidis

*University of Texas*

## Pricing American-Style Options by Monte Carlo Simulation: Alternatives to Ordinary Least Squares

##### Abstract

April 4, 2008

## Qiwei Yao

*London School of Economics*

## Analysing Time Series with Nonstationarity: Common Factors and Curve Series

##### Abstract

April 11, 2008

## Kenneth Singleton

* Stanford University*

## Why Do Risk Premiums in Sovereign Credit Markets Covary?

April 18, 2008

## Mathieu Kessler

*Universidad Politecnica de Cartagena, Spain*

## Exact filters for discretized diffusions

April 24, 2008

## Ronnie Sircar

*Princeton University*

## Homogeneous Groups and Multiscale Intensity Models for Multiname Credit Derivatives

##### Abstract

1. realistic modeling of the firms’ default times and the correlation between them; and

2. efficient computational methods for computing the portfolio loss distribution from the firms’ marginal default time distributions.

We revisit intensity-based models and, with the aforementioned issues in mind, we propose improvements

1. via incorporating fast mean-reverting stochastic volatility in the default intensity processes; and

2. by considering a hybrid of a top-down and a bottom-up model with homogeneous groups within the original set of firms.

We present a calibration example from CDO data, and discuss the relative performance of the approach.

This is joint work with Evan Papageorgiou.

April 25, 2008

## Dag Tjostheim

*University of Bergen*

## Estimation in time series that are both nonlinear and nonstationary

##### Abstract

May 2, 2008

## Jianqing Fan

*Princeton University*

## Modeling and Estimation of High-Dimensional Covariance Matrix for Portfolio Allocation and Risk Management

##### Abstract

May 9, 2008

## Jostein Paulsen

*University of Bergen
The *

*University of Chicago*

## Optimal dividend payments and reinvestments of diffusion processes with both fixed and proportional costs

##### Abstract

1. Whenever assets reach a barrier they are reduced by a fixed amount through a dividend payment, and whenever they reach 0 they are increased to another fixed amount by a reinvestment.

2. There is no optimal policy, but the value function is approximated by policies of the form described in Item 1 for increasing barriers. We provide criteria to decide whether an optimal solution exists, and when not, show how to calculate the value function. It is discussed how the problem can be solved numerically and numerial examples are given. The talk is based on a paper with the same title to appear in SIAM Journal of Control and Optimization.

May 30, 2008

## Sebastian Jaimungal

*University of Toronto*

## Hitting Time Problems with Applications to Finance and Insurance

##### Abstract

Armed with these tools, there are two natural applications: one to finance and one to insurance. In the financial context, the Brownian motion may drive the value of a firm and through a structural modeling approach I will show how CDS spread curves can be matched. In the insurance context, suppose an individuals health reduces by one unit per annum with fluctuations induced by a Brownian motion and once their health hits zero the individual dies. I will show how life-table data can be nicely explained by this model and illustrate how to perturb the distribution for pricing purposes.

This is joint work with Alex Kreinin and Angelo Valov