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A Markov chain approach to stock model analysis and inference

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dc.contributor.author BARBU, Vlad Stefan
dc.contributor.author D’AMICO, Guglielmo
dc.contributor.author DE BLASIS, Riccardo
dc.date.accessioned 2020-11-04T07:04:24Z
dc.date.available 2020-11-04T07:04:24Z
dc.date.issued 2018
dc.identifier.citation BARBU, Vlad Stefan, D’AMICO, Guglielmo, DE BLASIS, Riccardo. A Markov chain approach to stock model analysis and inference. In: CAIM 2018: The 26th Conference on Applied and Industrial Mathematics: Book of Abstracts, Technical University of Moldova, September 20-23, 2018. Chişinău: Bons Offices, 2018, p. 70. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/11084
dc.description Only Abstract en_US
dc.description.abstract In this presentation, based on Barbu et al., 2017, we are interested in applications of statistical techniques for Markov chains in financial mathematics. We have modelled through a Markov chain the time evolution of the dividend growth factor of a stock. We were interested in estimating the first two moments of the price of the stock and also in forecasting the price of the stock within n time units. This work represents further advancements of the Markov chain stock model proposed in Ghezzi and Piccardi, 2003. We give theoretical results about the consistency and asymptotic normality of the estimated quantities and apply our findings to real dividend data. The statistical techniques for Markov chains are mainly based on Sadek and Limnios, 2002. en_US
dc.language.iso en en_US
dc.publisher Bons Offices en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject financial mathematics en_US
dc.subject Markov chains en_US
dc.subject stocks en_US
dc.subject stocks price en_US
dc.subject dividends en_US
dc.title A Markov chain approach to stock model analysis and inference en_US
dc.type Article en_US


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