Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 2.00 MB
Add to list
  1. Search results
  2. Intraday seasonality and volatility p...

Intraday seasonality and volatility pattern : an explanation with recurrence quantification analysis

Baki Ünal, Güray Küçükkocaoğlu and Eyüp Kadioglu (UGent)
(2023) INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS. 33(3).
Author
Organization
Abstract
The Recurrence Quantification Analysis (RQA), a pattern recognition-based time series analysis method, can be successfully utilized for short, nonstationary, nonlinear, and chaotic time series. These RQA measures quantify several properties of time series, including predictability, regularity, stability, randomness, and complexity. In this regard, first, we analyzed the intraday seasonality with RQA and demonstrated how RQA measures change among the intraday periods by using 160 million row matched orders of 100 shares from Borsa Istanbul Equity Market between 2019M10 and 2020M02. We selected 50 stocks from the BIST50 Index group and 50 stocks from outside of the BIST100 Index group. Since these two share groups exhibit similar intraday RQA seasonality, our results are robust. Second, we explained intraday volatility with RQA measures and found a relationship between RQA measures and intraday volatility using a regression model.
Keywords
Intraday volatility pattern, intraday seasonality, recurrence plot, recurrence quantification analysis, realized volatility, intraday, volatility, TIME-SERIES, DYNAMICS, EXCHANGE, RETURNS, MARKETS, PLOTS, OIL, RUN

Downloads

  • Download
    (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 2.00 MB

Citation

Please use this url to cite or link to this publication:

MLA
Ünal, Baki, et al. “Intraday Seasonality and Volatility Pattern : An Explanation with Recurrence Quantification Analysis.” INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, vol. 33, no. 3, 2023, doi:10.1142/S021812742350027X.
APA
Ünal, B., Küçükkocaoğlu, G., & Kadioglu, E. (2023). Intraday seasonality and volatility pattern : an explanation with recurrence quantification analysis. INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 33(3). https://doi.org/10.1142/S021812742350027X
Chicago author-date
Ünal, Baki, Güray Küçükkocaoğlu, and Eyüp Kadioglu. 2023. “Intraday Seasonality and Volatility Pattern : An Explanation with Recurrence Quantification Analysis.” INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 33 (3). https://doi.org/10.1142/S021812742350027X.
Chicago author-date (all authors)
Ünal, Baki, Güray Küçükkocaoğlu, and Eyüp Kadioglu. 2023. “Intraday Seasonality and Volatility Pattern : An Explanation with Recurrence Quantification Analysis.” INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 33 (3). doi:10.1142/S021812742350027X.
Vancouver
1.
Ünal B, Küçükkocaoğlu G, Kadioglu E. Intraday seasonality and volatility pattern : an explanation with recurrence quantification analysis. INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS. 2023;33(3).
IEEE
[1]
B. Ünal, G. Küçükkocaoğlu, and E. Kadioglu, “Intraday seasonality and volatility pattern : an explanation with recurrence quantification analysis,” INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, vol. 33, no. 3, 2023.
@article{01GW717K47ASRN5B5BHV290GCP,
  abstract     = {{The Recurrence Quantification Analysis (RQA), a pattern recognition-based time series analysis method, can be successfully utilized for short, nonstationary, nonlinear, and chaotic time series. These RQA measures quantify several properties of time series, including predictability, regularity, stability, randomness, and complexity. In this regard, first, we analyzed the intraday seasonality with RQA and demonstrated how RQA measures change among the intraday periods by using 160 million row matched orders of 100 shares from Borsa Istanbul Equity Market between 2019M10 and 2020M02. We selected 50 stocks from the BIST50 Index group and 50 stocks from outside of the BIST100 Index group. Since these two share groups exhibit similar intraday RQA seasonality, our results are robust. Second, we explained intraday volatility with RQA measures and found a relationship between RQA measures and intraday volatility using a regression model.}},
  articleno    = {{2350027}},
  author       = {{Ünal, Baki and Küçükkocaoğlu, Güray and Kadioglu, Eyüp}},
  issn         = {{0218-1274}},
  journal      = {{INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS}},
  keywords     = {{Intraday volatility pattern,intraday seasonality,recurrence plot,recurrence quantification analysis,realized volatility,intraday,volatility,TIME-SERIES,DYNAMICS,EXCHANGE,RETURNS,MARKETS,PLOTS,OIL,RUN}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{25}},
  title        = {{Intraday seasonality and volatility pattern : an explanation with recurrence quantification analysis}},
  url          = {{http://doi.org/10.1142/S021812742350027X}},
  volume       = {{33}},
  year         = {{2023}},
}
Altmetric
View in Altmetric
Web of Science
Times cited: