The widely accepted belief that asset returns and insurance product line margins are not normally distributed has motivated the use of skewness (or higher than second order moments), in the context of optimal risk-reward portfolio allocation. Here, we propose an optimization-based methodology to substantially improve the skewness of portfolios in the mean-variance efficient frontier. Unlike oth...

The results on the mean-variance hedging problem in Gouriéroux, Laurent and Pham (1998), Rheinländer and Schweizer (1997) and Arai (2005) are extended to discontinuous semimartingale models. When the numéraire method is used, we only assume the Radon-Nikodym derivative of the variance-optimal signed martingale measure (VSMM) is non-zero almost surely (but may be strictly negative). When discuss...

We consider a mean-variance hedging (MVH) problem for an arbitrage-free large financial market, i.e. a financial market with countably many risky assets modelled by a sequence of continuous semimartingales. By using the stochastic integration theory for a sequence of semimartingales developed in De Donno and Pratelli (2003), we extend the results about change of numéraire and MVH of Gourieroux,...

Although Fractal image compression has high quality at high compression ratio, it needs a lot of encoding time so that it has not been widely applied as other coding schemes in the field of image compression. In this paper, an algorithm is devised to improve this drawback. We utilize mean and variance to classify image blocks and combine the transformation reduction techniques to decrease the e...

Difficulties with the interpretation of the parameters of the beta distribution let Malcolm et al. (1959) to suggest in the Program Evaluation and Review Technique (PERT) their by now classical expressions for the mean and variance for activity completion for practical applications. In this note, we shall provide an alternative for the PERT variance expression addressing a concern raised by Hah...

The aim of the paper is to derive the numerical least-squares esti-mator for mean and variance of random variable. In order to do so the following questions have to be answered: (i) what is the statistical model for the estimation procedure? (ii) what are the properties of the estimator, like optimality (in which class) or asymptotic properties? (iii) how does the estimator work in practice, ho...

We use mean-variance hedging in discrete time in order to value an insurance liability. The prediction of the insurance liability is decomposed into claims development results, that is, yearly deteriorations in its conditional expected values until the liability is finally settled. We assume the existence of a tradeable derivative with binary pay-off written on the claims development result and...

Here we study the performance of a one-period investment X0 > 0 (dollars) shared among several different assets. Our criterion for measuring performance will be the mean and variance of its rate of return; the variance being viewed as measuring the risk involved. Among other things we will see that the variance of an investment can be reduced simply by diversifying, that is, by sharing the X0 a...

This paper addresses the problem of segmenting a time-series with respect to changes in the mean value or in the variance. The first case is when the time data is modeled as a sequence of independent and normal distributed random variables with unknown, possibly changing, mean value but fixed variance. The main assumption is that the mean value is piecewise constant in time, and the task is to ...