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dc.identifier.citationBorg, A. (2013). Using stable distributions to model local financial data (Bachelor's dissertation).en_GB
dc.description.abstractStable distributions are a family of probability distributions which have many properties that are useful in applications in many fields such as finance. One of their main characteristics is that they allow for skewness and heaviness of tails. The normal distribution, which is a member of this family, is a special case, since it is the only distribution that has a finite variance. Due to this characteristic, there are several works in literature that show that non-normal stable distributions are a better alternative to the normal distribution (which is also a stable distribution). In this dissertation we will review some of the main concepts of stable distributions. There are over thirteen methods of parameter estimation of stable distributions available nowadays, we shall describe two of these methods which are, the Integrated Squared Error Estimation method (ISEE) adopted by Heathcote (1977) and the Maximum Likelihood Estimation (MLE) method adopted by Nolan (2001). We will prove that both methods lead to estimators that are asymptotically normal and consistent. Then we shall apply the two methods on local financial data which includes exchange rates and stock returns. The parameter estimates obtained from the two methods are compared graphically and tested for their goodness of fit. Both methods allow us to accept the stable distribution as a model of the local exchange rates but force us to reject the stable distribution as a model of the local stock returns.en_GB
dc.subjectDistribution (Probability theory)en_GB
dc.subjectEstimation theoryen_GB
dc.subjectGoodness-of-fit testsen_GB
dc.subjectCharacteristic functionsen_GB
dc.subjectForeign exchange ratesen_GB
dc.titleUsing stable distributions to model local financial dataen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.publisher.institutionUniversity of Maltaen_GB
dc.publisher.departmentFaculty of Science. Department of Statistics and Operations Researchen_GB
dc.contributor.creatorBorg, Alida (2013)-
Appears in Collections:Dissertations - FacSci - 1965-2014
Dissertations - FacSciSOR - 2000-2014

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