Publication Details
Design Of Autonomous Algorithmic Models For Time Series Prediction
statistical arbitrage, fair value, high frequency data, time series, econometrics, business rule
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.
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.
@inproceedings{BUT111561,
author="Eva {Zámečníková}",
title="Design Of Autonomous Algorithmic Models For Time Series Prediction",
booktitle="STUDENT EEICT 2014",
year="2014",
series="Volume 3",
pages="279--283",
publisher="Brno University of Technology",
address="Brno",
isbn="978-80-214-4924-4",
url="https://www.fit.vut.cz/research/publication/10584/"
}