Drew D Creal
Biographic Data
| ID | 8920051 |
|---|---|
| NAME | Drew D Creal |
| GIVEN NAMES | Drew D |
| FAMILY NAME | Creal |
| SIGNATURE | CREAL D D |
| AFFILIATIONS | The University of Chicago Booth School of Business, Chicago, IL 60637 () |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2017 |
| H-INDEX | 0 |
A Class of Non-Gaussian State Space Models With Exact Likelihood Inference
The likelihood function of a general nonlinear, non-Gaussian state space model is a high-dimensional integral with no closed-form solution. In this article, I show how to calculate the likelihood function exactly for a large class of non-Gaussian state space models that include stochastic intensity, stochastic volatility, and stochastic duration models among others. The state variables in this class follow a nonnegative stochastic process that is…
Market-Based Credit Ratings
We present a methodology for rating in real-time the creditworthiness of public companies in the U.S. from the prices of traded assets. Our approach uses asset pricing data to impute a term structure of risk neutral survival functions or default probabilities. Firms are then clustered into ratings categories based on their survival functions using a functional clustering algorithm. This allows all public firms whose assets are traded to be direct…
No prominent works on this page.
Market-Based Credit Ratings
We present a methodology for rating in real-time the creditworthiness of public companies in the U.S. from the prices of traded assets. Our approach uses asset pricing data to impute a term structure of risk neutral survival functions or default probabilities. Firms are then clustered into ratings categories based on their survival functions using a functional clustering algorithm. This allows all public firms whose assets are traded to be direct…
A Class of Non-Gaussian State Space Models With Exact Likelihood Inference
The likelihood function of a general nonlinear, non-Gaussian state space model is a high-dimensional integral with no closed-form solution. In this article, I show how to calculate the likelihood function exactly for a large class of non-Gaussian state space models that include stochastic intensity, stochastic volatility, and stochastic duration models among others. The state variables in this class follow a nonnegative stochastic process that is…
Computer Science (2 works) · Econometrics (2 works) · Mathematics (2 works) · Statistics (2 works) · Actuarial science (1 work) · Algorithm (1 work) · Applied Mathematics (1 work) · Artificial Intelligence (1 work) · Banking stability, regulation, efficiency (1 work) · Bayesian inference (1 work)