Design Of Autonomous Algorithmic Models For Time Series Prediction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU111966" target="_blank" >RIV/00216305:26230/14:PU111966 - isvavai.cz</a>

Result on the web

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10584" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10584</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Design Of Autonomous Algorithmic Models For Time Series Prediction

Original language description

This paper is focused on basic concepts used for processing of high frequency data. The idea of designing of systems for predicting of these time series and its parallel to business proces rules modeling will be mentioned. Designed system will use principles of statististical arbitrage, time series correlation, the use of multivariate variables and characteristics of the distribution of interim data. Newly designed system must meet the condition of econometrics for high frequency data.

Czech name

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Czech description

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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)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2014

Confidentiality

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

Article name in the collection

STUDENT EEICT 2014

ISBN

978-80-214-4924-4

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

279-283

Publisher name

Brno University of Technology

Place of publication

Brno

Event location

Brno

Event date

Apr 24, 2014

Type of event by nationality

CST - Celostátní akce

UT code for WoS article

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