IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/76039.html
   My bibliography  Save this paper

Threshold convergence between the federal fund rate and South African equity returns around the colocation period

Author

Listed:
  • Phiri, Andrew

Abstract

Using weekly data collected from 20.09.2008 to 09.12.2016, this paper uses dynamic threshold adjustment models to demonstrate how the introduction of high-frequency and algorithmic trading on the Johannesburg Stock Exchange (JSE) has altered convergence relations between the federal fund rate and equity returns for aggregate and disaggregate South African market indices. We particularly find that for the post-crisis period, the JSE appears to operate more efficiently, in the weak-form sense, under high frequency trading platforms.

Suggested Citation

  • Phiri, Andrew, 2017. "Threshold convergence between the federal fund rate and South African equity returns around the colocation period," MPRA Paper 76039, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:76039
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/76039/1/MPRA_paper_76039.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrew Phiri, 2017. "Long-run equilibrium adjustment between inflation and stock market returns in South Africa: a nonlinear perspective," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 9(1), pages 19-33.
    2. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    3. Benos, Evangelos & Sagade, Satchit, 2012. "High-frequency trading behaviour and its impact on market quality: evidence from the UK equity market," Bank of England working papers 469, Bank of England.
    4. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    5. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-176, April.
    6. Michael Goldstein & Tina Viljoen & P. Joakim Westerholm & Hui Zheng, 2014. "Algorithmic Trading, Liquidity, and Price Discovery: An Intraday Analysis of the SPI 200 Futures," The Financial Review, Eastern Finance Association, vol. 49(2), pages 245-270, May.
    7. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    8. Viktor Manahov & Robert Hudson, 2014. "The implications of high-frequency trading on market efficiency and price discovery," Applied Economics Letters, Taylor & Francis Journals, vol. 21(16), pages 1148-1151, November.
    9. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    10. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    11. Eun Jung Lee, 2015. "High Frequency Trading in the Korean Index Futures Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(1), pages 31-51, January.
    12. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bazzana, Flavio & Collini, Andrea, 2020. "How does HFT activity impact market volatility and the bid-ask spread after an exogenous shock? An empirical analysis on S&P 500 ETF," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
    3. Olgun, Onur & Ekinci, Cumhur & Arıkan, Ramazan, 2024. "The performance of selected high-frequency trading proxies: An application on Turkish index futures market," Finance Research Letters, Elsevier, vol. 65(C).
    4. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    5. Zhou, Hao & Kalev, Petko S. & Frino, Alex, 2020. "Algorithmic trading in turbulent markets," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    6. Andrew Phiri, 2020. "Structural changes in exchange rate-stock returns dynamics in South Africa: examining the role of crisis and new trading platform," Economic Change and Restructuring, Springer, vol. 53(1), pages 171-193, February.
    7. Phiri, Andrew & Dube, Wisdom, 2014. "Nutrition and economic growth in South Africa: A momentum threshold autoregressive (MTAR) approach," MPRA Paper 52950, University Library of Munich, Germany.
    8. Taiga Saito & Takanori Adachi & Teruo Nakatsuma & Akihiko Takahashi & Hiroshi Tsuda & Naoyuki Yoshino, 2018. "Trading and Ordering Patterns of Market Participants in High Frequency Trading Environment: Empirical Study in the Japanese Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(3), pages 179-220, September.
    9. Viktor Manahov & Robert Hudson, 2014. "The implications of high-frequency trading on market efficiency and price discovery," Applied Economics Letters, Taylor & Francis Journals, vol. 21(16), pages 1148-1151, November.
    10. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    11. Adamantios Ntakaris & Martin Magris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2017. "Benchmark Dataset for Mid-Price Forecasting of Limit Order Book Data with Machine Learning Methods," Papers 1705.03233, arXiv.org, revised Mar 2020.
    12. Anagnostidis, Panagiotis & Fontaine, Patrice & Varsakelis, Christos, 2020. "Are high–frequency traders informed?," Economic Modelling, Elsevier, vol. 93(C), pages 365-383.
    13. Vitale, Paolo, 2018. "Robust trading for ambiguity-averse insiders," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 113-130.
    14. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    15. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    16. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    17. Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2023. "The Impact of High-Frequency Trading on Modern Securities Markets," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 7-24, February.
    18. Frino, Alex & Mollica, Vito & Webb, Robert I. & Zhang, Shunquan, 2017. "The impact of latency sensitive trading on high frequency arbitrage opportunities," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 91-102.
    19. Markus Baldauf & Joshua Mollner, 2015. "High-Frequency Trading and Market Performance," Discussion Papers 15-017, Stanford Institute for Economic Policy Research.
    20. Ligot, Stephanie & Gillet, Roland & Veryzhenko, Iryna, 2021. "Intraday volatility smile: Effects of fragmentation and high frequency trading on price efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).

    More about this item

    Keywords

    Colocation; High frequency trading; Global financial crisis; Federal fund rates; Equity returns; Threshold cointegration; Johannesburg Stock Exchange (JSE).;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:76039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.