Article
Licensed
Unlicensed
Requires Authentication
Approximations of empirical probability generating processes
-
Gábor Szűcs
Published/Copyright:
September 25, 2009
Summary
First we polish an argument of Rémillard and Theodorescu for the weak convergence of the empirical probability generating process. Then we prove a general inequality between probability generating processes and the corresponding empirical processes, which readily implies a rate of convergence and trivializes the problem of weak convergence: whenever the empirical process or its non-parametric bootstrap version, or the parametric estimated empirical process or its bootstrap version converges, so does the corresponding probability generating process. Derivatives of the generating process are also considered.
:
Published Online: 2009-09-25
Published in Print: 2005-01-01
© R. Oldenbourg Verlag, München
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Optimal consumption strategies under model uncertainty
- Perpetual convertible bonds in jump-diffusion models
- On low dimensional case in the fundamental asset pricing theorem with transaction costs
- Optimal portfolios with expected loss constraints and shortfall risk optimal martingale measures
- Approximations of empirical probability generating processes
Articles in the same Issue
- Optimal consumption strategies under model uncertainty
- Perpetual convertible bonds in jump-diffusion models
- On low dimensional case in the fundamental asset pricing theorem with transaction costs
- Optimal portfolios with expected loss constraints and shortfall risk optimal martingale measures
- Approximations of empirical probability generating processes
