Application of fuzzy numbers in binomial tree model and time complexity

DSpace Repository

Show simple item record Kresta, Aleš Zmeškal, Zdeněk
dc.contributor.other Ekonomická fakulta cs 2014-05-22 2014-05-22 2013-08
dc.identifier.isbn 978-80-7372-953-0
dc.description.abstract Discrete binomial models are powerful tools for options valuation. For simple pay-off options they can be viewed as an approximation of famous Black-Scholes option valuation formula. By increasing the quantity of periods in binomial model (i.e. decreasing the length of the period), the results converge to the continuous model. However this approximation is very computationally costly, thus the analytical solution to the valuation is preferable. Nevertheless, the analytical solution does not exist for more complicated pay-off options. In the article we assume the valuation of project with the possibility to change the quantity of products produced. Some input parameters (concretely the volatility and initial cash-flows) are assumed to be uncertain and stated as a fuzzy numbers. Illustrative example is provided in the paper. In this example we examine the time complexity of the algorithm and the influence of the imprecision of input parameters on the appraisal imprecision. From the results it is apparent that the complexity of the model is quadratic. Thus by increasing the quantity of periods in the binomial model it becomes unreasonably time demanding. en
dc.format text
dc.format.extent 343-352 cs
dc.language.iso en
dc.publisher Technická Univerzita v Liberci cs
dc.publisher Technical university of Liberec, Czech Republic en
dc.relation.ispartofseries Liberec economic forum 2013: proceedings of the 11th international conference: 16th - 17th September 2013, Sychrov, Czech republic, EU /[editor Aleš Kocourek];1
dc.subject finance en
dc.subject valuation en
dc.subject investment analysis en
dc.subject fuzzy sets en
dc.subject real options en
dc.subject binomial model en
dc.title Application of fuzzy numbers in binomial tree model and time complexity cs
dc.type Article en
dc.publisher.abbreviation TUL
local.faculty Faculty of Economics
local.access open
local.fulltext yes

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search


My Account