Comparison of algorithmic trading using the homogeneous and non-homogeneous Markov chain analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23510%2F17%3A43932496" target="_blank" >RIV/49777513:23510/17:43932496 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparison of algorithmic trading using the homogeneous and non-homogeneous Markov chain analysis
Original language description
This empirical study deals with stochastic modelling of a short-term share price development. We use Markov chain analysis (MCA) to predict the share price development. When defining a state space we assume that the share price moves in three types of trends: primary, secondary and minor. The subject of our interest is a minor trend, which usually lasts for several days. During this trend the share price accumulates a certain profit or loss in relation to the price at the beginning of the trend. The state space is defined by the amount of the accumulated profit or loss. The aim of this study is to compare two approaches to modelling the state space. In the first approach, we assume homogeneous Markov chains, i.e. approximately the same volatility, and MCA is performed with unvarying state space. In the second approach, we assume non-homogeneous Markov chains, i.e. a changing volatility, and MCA is performed with varying state space. We create trading strategies for automatic generation of buying and selling orders based on these models. Three business systems have been created for each approach. The profitability of each business system is calculated and compared. The study was performed using historical daily prices (opening and closing) of CEZ shares from the beginning of 2006 until the end of 2016. This study has proved that trading models with varying state space, on the average, outperform trading models with unvarying state space.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
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 14TH INTERNATIONAL SCIENTIFIC CONFERENCE PART 2 : EUROPEAN FINANCIAL SYSTEM 2017:
ISBN
978-80-210-8609-8
ISSN
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e-ISSN
neuvedeno
Number of pages
9
Pages from-to
223-231
Publisher name
Masarykova univerzita
Place of publication
Brno
Event location
Brno
Event date
Jun 26, 2017
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000418110800027