The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models developed by Duan (1994) is extended to account for the fact that observed equity prices may have been contaminated by trading noises. With the presence of trading noises, the likelihood function based on the observed equity prices can only be evaluated via some nonlinear filtering scheme. We devis...

In this paper I describe a wavelet filtering approach to separate a time series, the signal, into its main components. With this approach I can separate stochastic from structural components. The statistical predictive analysis will be performed on the filtered signal while the stochastic term could be a-posteriori reintroduced through statistical simulation approaches (such as Markov Chain Mon...

The authors develop a self-contained theory for linear estimation in Krein spaces. The derivation is based on simple concepts such as projections and matrix factorizations and leads to an interesting connection between Krein space projection and the recursive computation of the stationary points of certain second-order (or quadratic) forms. The authors use the innovations process to obtain a ge...

In this paper we propose a new, information-based approach for modelling the dynamic evolution of a portfolio of credit risky securities. In our setup market prices of traded credit derivatives are given by the solution of a nonlinear filtering problem. The innovations approach to nonlinear filtering is used to solve this problem and to derive the dynamics of market prices. Moreover, the practi...

In this paper, we compare the spatially adaptive iterative filtering (SAIF) approach with Weighted Encoding with Sparse Nonlocal Regularization (WESNR) to maintain the denoising strength locally for any spatial domain method. These approaches has ability of filtering local image content iteratively using the given base filter, and the type of iteration and the iteration number are automatically...

The increasing size of messaging communities increases the risk of information overload, especially when group communication tools like mailing lists or asynchronous conferencing systems (like Usenet News) are used. Future messaging systems will require more capable filters to aid users in the selection of what to read. The increasing use of networks by non-computer professionals requires filte...

This paper focuses on a topical and important area of theory and practice ie. The risk premium in financial markets. While there exists a vast amount of research into its behaviour, particularly in US markets, this is largely based on regression based techniques which do not capture well the dynamic and forward looking nature of the risk premium. In this paper the time variation of the unobserv...

‎Pricing weather derivatives is becoming increasingly useful‎, ‎especially in developing economies‎. ‎We describe a statistical model based approach for pricing  weather derivatives by modeling and forecasting daily average temperatures data which exhibits long-range dependence‎. ‎We pre-process the temperature data by filtering for seasonality and volatility an...