Keywords
Citation
Harwood, C.J. (2000), "Modelling Financial Derivatives with Mathematica", Kybernetes, Vol. 29 No. 1, pp. 144-155. https://doi.org/10.1108/k.2000.29.1.144.4
Publisher
:Emerald Group Publishing Limited
Readers of this journal have already (see Altonen and Östermark, 1998; Östermark and Altonen, 1999; Östermark and Söderlund, 1999; Östermark et al., 1999) received an insight into the problems of modelling financial derivatives and associated researches. This book shows how a software package “Mathematica” can be used in such a context. For non‐specialists perhaps it would be useful to first read about this package and the book is written with this in view. But to a degree it is self‐explanatory and much of its thesis can be followed without reverting to a software manual. The author is quite clear as to what he wishes to achieve. He wants to show how the package can be used to model financial derivatives and also the mathematical development is to be described. It is also his intention to offer comparisons of the various methods that are currently available. The reader does need to have a good general knowledge of mathematics but need not be a specialist in this area to understand the problems of modelling this application or appreciating the choice of methods. Not all the necessary mathematics that supports the theory is included; cyberneticians, on the other hand, who are specialists in the field, will wonder why so much has not been included.
What is needed, I believe, is a good knowledge of modelling in a financial environment. The terms used and goals set out do need to be understood to be appreciated. If you are a practising financial modeller then you will be delighted to receive the CD that is provided with the book. It includes virtually all of the Mathematica packages dealt with in the book. Should I buy the book? Well that depends very much on your interest in the field of financial modelling and also your level of mathematics. A knowledge and interest in stochastic differential equations and the workings of such software packages as Mathematica would encourage you to make the purchase.
References
Altonen, J. and Östermark, R. (1998), “Mixed Markov modelling of financial success: empirical evidence with Swedish data”, Kybernetes, Vol. 27 No. 1, pp. 54‐70.
Östermark, R. (1999), “Forecasting stock returns with reference to global capital asset forces”, Kybernetes, Vol. 28 No. 9, pp. 1027‐41.
Östermark, R. and Altonen, J. (1999), “Competing transformation models: Part I Methodology; Part II Empirical results”, Kybernetes, Vol. 28 No. 4, pp. 441‐60.
Östermark, R. and Söderlund, K. (1999), “A multiperiod firm model for strategic decision support”, Kybernetes, Vol. 28 No. 5, pp. 538‐56.
Östermark, R., Höglund, R. and Saxen, H. (1999), “Estimating system response to a regime shift: some evidence of international asset pricing”, Kybernetes, Vol. 28 No. 6/7, pp. 732‐52.