Application of non-homogeneous Markov chain analysis to trend prediction of stock indices

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23510%2F13%3A43919711" target="_blank" >RIV/49777513:23510/13:43919711 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Application of non-homogeneous Markov chain analysis to trend prediction of stock indices

Popis výsledku v původním jazyce

The present paper concerns with prolongation of our study aims to predict the stock index trend of various stock indices using Markov chain analysis (MCA). The prediction of the trend using MCA is done using short, medium and long-term data. Each downloaded data is divided into two periods. The first one is used for estimating the trend, whereas the second one is used for comparison and evaluation, too. In the basic framework, we may use either homogeneous MC or nonhomogeneous one. When building model we are focused both on various state space discretizations and corresponding construction of transition probability matrices. Non-homogeneous matrices are constructed by linear interpolants between two transition probability matrices at given time steps.These objects represent a core of any MCA and its application. The results of the trend prediction using both versions of MCA are compared. Numerical calculations and computer implementations have been done by Excel and Mathematica module

Název v anglickém jazyce

Application of non-homogeneous Markov chain analysis to trend prediction of stock indices

Popis výsledku anglicky

The present paper concerns with prolongation of our study aims to predict the stock index trend of various stock indices using Markov chain analysis (MCA). The prediction of the trend using MCA is done using short, medium and long-term data. Each downloaded data is divided into two periods. The first one is used for estimating the trend, whereas the second one is used for comparison and evaluation, too. In the basic framework, we may use either homogeneous MC or nonhomogeneous one. When building model we are focused both on various state space discretizations and corresponding construction of transition probability matrices. Non-homogeneous matrices are constructed by linear interpolants between two transition probability matrices at given time steps.These objects represent a core of any MCA and its application. The results of the trend prediction using both versions of MCA are compared. Numerical calculations and computer implementations have been done by Excel and Mathematica module

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Mathematical Methods in Economics 2013: 31st International Conference: Proceedings

ISBN

978-80-87035-76-4

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

881-886

Název nakladatele

College of Polytechnics Jihlava

Místo vydání

Jihlava

Místo konání akce

Jihlava

Datum konání akce

11. 9. 2013

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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