Výzkumná zpráva

Chudoba M., Jirsa L.

Research Report

2226

ÚTIA AV ČR

Praha

2008

RNDr. Ladislav Jirsa, Ph.D. (ÚTIA - Oddělení adaptivních systémů)

Bayesian estimation, finance, transformation of data, hypoth

In the presented work we are introduced to the problem of optimal decision making while dealing on the exchange with so-called "financial futures", i.e. time financial transaction. This task is transferred into the simplified mathematical model, which is solvable using Bayesian estimation methods. Financial data are modelled by auto-regressive model with normal noise, because the tools, which are exploited for prediction of the price on the market and which assume normal noise, have been already developed. The main goal of this work is the comparison of the efficiency of various transformations on input data, so that their noise had normal distribution, therefore the price prediction was as accurate as possible. The applicable algorithm is programmed in Matlab; the presentation of achieved results forms the final part of this thesis.