Mean first passage times of four mean-reverting processes

Author(s):

Bo Zhao

Topic:
Finance
Industry:
Banking

In this paper, we study stationary states and mean first passage times (MFPT) of four well-known mean reverting processes: the square root process of Feller, the Ahn-Gao model, the GARCH diffusion model and the stochastic Verhulst process.

Updated: 27/10/2011
Comments:
Views: 4,151

Testing for stochastic dominance efficiency

Author(s):

Thierry Post

Industry:
Banking

We propose a new test of the stochastic dominance efficiency of a given portfolio over a classof portfolios. We establish its null and alternative asymptotic properties, and define a methodfor consistently estimating critical values. We present some numerical evidence that our testswork well in moderate sized samples.

Updated: 27/10/2011
Comments:
Views: 3,936

Does risk seeking drive asset prices? A stochastic dominance analysis of aggregate investor preferences

Author(s):

Thierry Post

 et al.
Topic:
Finance
Industry:
Banking

We investigate whether risk seeking or non-concave utility functions can help to explain the cross-sectional pattern of stock returns.

Updated: 27/10/2011
Comments:
Views: 3,396

Spanning and intersection: a stochastic dominance approach

Author(s):

Thierry Post

Industry:
Banking

We propose linear programming tests for spanning and intersection based on stochasticdominance rather than mean-variance analysis.

Updated: 27/10/2011
Comments:
Views: 3,823

Testing for stochastic dominance efficiency

We propose a new test of the stochastic dominance efficiency of a given portfolio over a class of portfolios.

Updated: 27/10/2011
Comments:
Views: 3,685

Approximate basket option valuation for a simplified jump process

Author(s):

Daniel Giamouridis

Topic:
Finance
Industry:
Banking

This paper proposes the use of a simplified jump process, namely the Bernoulli jump process, to develop approximate basket option valuation formulas.

Updated: 22/09/2011
Comments:
Views: 4,956

Backtesting stochastic mortality models: an ex-post evaluation of multi-period ahead-density forecasts

This study sets out a backtesting framework applicable to the multi-period-ahead forecasts from stochastic mortality models and uses it to evaluate the forecasting performance of six different stochastic mortality models applied to English & Welsh male mortality data. The study also finds that density forecasts that allow for uncertainty in the parameters of the mortality model are more plausible than forecasts that do not allow for such uncertainty.

Updated: 22/09/2011
Comments:
Views: 4,064

Evaluating the goodness of fit of stochastic mortality models

This study sets out a framework to evaluate the goodness of fit of stochastic mortality models and applies it to six different models estimated using English and Welsh male mortality data. The methodology exploits the structure of each model to obtain various residual series that are predicted to be iid standard normal under the null hypothesis of model adequacy. Goodness of fit can then be assessed using conventional tests of the predictions of iid standard normality. The models considered are Lee-Carter's 1992 one-factor model, a version of Renshaw-Haberman's 2006 extension of the Lee-Carter model to allow for a cohort effect, Currie's 2006 age-period-cohort model, which is a simplified version of the Renshaw-Haberman model, the Cairns-Blake-Dowd 2006 two-factor model and two generalised versions of the latter that allow for a cohort effect. For the data set considered, there are some notable differences amongst the different models, but none of the models performs well in all tests and no model clearly dominates the others.

Updated: 22/09/2011
Comments:
Views: 4,041

Mortality density forecasts: an analysis of six stochastic mortality models

We investigate the uncertainty of forecasts of future mortality generated by a number of previously proposed stochastic mortality models. We specify fully the stochastic structure of the models to enable them to generate forecasts. Mortality fan charts are then used to compare and contrast the models, with the conclusion that model risk can be significant.

Updated: 22/09/2011
Comments:
Views: 4,126