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Compare Of Linear And Neural Networks Models For Estimating And Forecasting Black-Scholes Option Pricing Model

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F13%3A43870718" target="_blank" >RIV/70883521:28120/13:43870718 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.ufu.utb.cz/sbornik/proceedings2013.pdf" target="_blank" >http://www.ufu.utb.cz/sbornik/proceedings2013.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Compare Of Linear And Neural Networks Models For Estimating And Forecasting Black-Scholes Option Pricing Model

  • Original language description

    The Black-Scholes formula is a well-known model for pricing and hedging derivative securities. Interesting hypothetical questions that can be raised are: If option pricing model had not been developed, could a technique like neural networks have learnt the nonlinear form of the Black-Scholes type model to yield the fair value of an option? Could the networks have learnt to produce efficient implied volatility estimates? The results in this article from a simplified neural networks approach are rather encouraging, but more for volatility outputs than for call prices. This article will evaluate the performance of alternative neural network models relative to the standard linear model for forecasting relatively complex artificially generated time series.The article shows that relatively simple feedforward neural nets outperform the linear models in some cases, or do not do worse than the linear models.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    AE - Management, administration and clerical work

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 6th International Scientific Conference Finance and the performance of firms in science, education, and practice

  • ISBN

    978-80-7454-246-6

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    72-84

  • Publisher name

    Univerzita Tomáše Bati ve Zlíně, Fakulta managementu a ekonomiky

  • Place of publication

    Zlín

  • Event location

    Zlín

  • Event date

    Apr 25, 2013

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000329435800006