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Examples of financial market models obtained by euler discretization of continuous models
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Orientador(es)
Resumo(s)
We present a methodology to study discrete time financial models with one risky asset and a risk free asset that may thought to result as a discretization of a suitable continuous time model. In a numerical example we compare the pricing results, obtained with these models, with results obtained from the related continuous time models. Our approach relies on some known important results describing a particular class of discrete time models – the conditionally Gaussian models – a class that, regardless of its particular definition, contains many interesting instances. We aim at a better understanding of the implications of the discretization procedures which are inevitable, both at the parameter estimation and derivative price computation moments, by reason of the observational and computational limitations. We also present a preliminary study of a a model of stochastic differential equations for commodity spot and futures prices that may be studied with the proposed methodology. For that purpose we summarize a naive theory of Ito integration in Hilbert space.
Descrição
This work was done under partial financial support of RFBR (Grant n. 19-01-00451).
Palavras-chave
Commodity prices Coupled stochastic differential equations system Euler-Maruyama discretization Girsanov change of probability in discrete time Naive stochastic integration in Hilbert space Statistics and Probability Discrete Mathematics and Combinatorics