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Volume 13
Issue 1
Online publication date 2017-02-23
Title Threshold convergence between the federal fund rate and South African equity returns around the colocation period
Author Andrew Phiri
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.
Citation
References
Benos, E., Sagade, S. (2012). High-frequency trading behaviour and its impact on market quality: Evidence from the UK equity market. (Bank of England Working Paper Series, Working Paper No. 469).

Burke, S., Hunter, J. (2005). Modelling non-stationary economic time series: A multivariate approach. Palgrave, Basingstoke.

Carrion, A. (2013). Very fast money: High frequency trading on NASDAQ. Journal of Financial Markets, 16, 637-645. http://dx.doi.org/10.1016/j.finmar.2013.06.005

Enders, W., Silkos P. (2001). Cointegration and threshold adjustment. Journal of Business and Economic Statistics, 19(2), 166-176. http://dx.doi.org/10.1198/073500101316970395

Engle, R., Granger, C. (1987). Co-integration and error correction: Representation, estimation, and testing. Economertrica, 55, 369-384. http://www.jstor.org/stable/1913236

Hansbrouck, J., Saar, G. (2013). Low-latency trading. Journal of Financial Markets, 16, 741-770. http://dx.doi.org/10.1016/j.finmar.2013.05.003

Hansen, B. (2000). Sample splitting and threshold estimation. Econometrica, 68, 575-603. 10.1111/1468-0262.00124

Lee, E. (2015). High frequency trading in the Korean index futures market. Journal of Futures Market, 35, 31-51. 10.1002/fut.21640

Manahov, V., Hudson, R. (2014). The implications of high-frequency trading on market efficiency and price discovery. Applied Economics Letters, 21(16), 1148-1151.  http://dx.doi.org/10.1080/13504851.2014.914135

Manahov, V., Hudson, R., Gebka, B. (2014). Does high frequency trading affect technical analysis and market efficiency? And if so, how? Journal of International Financial Markets, Institutions and Money, 28, 131-157. http://dx.doi.org/10.1016/j.intfin.2013.11.002

Phiri, A. (2016). Long-run equilibrium adjustment between inflation and stock market returns in South Africa: A nonlinear perspective. International Journal of Sustainable Economy, 9(1), 19-33. http://dx.doi.org/10.1504/IJSE.2017.080866

Riordan, R., Storkenmaier, A. (2012). Latency, liquidity, and price discovery. Journal of Financial Studies, 43, 767-797. http://dx.doi.org/10.1016/j.finmar.2012.05.003

Viljoen, T., Westerholm, J., Zheng, H. (2014). Algorithmic trading, liquidity and price discovery: An intraday analysis of the SPI 200 futures. The Financial Review, 49(2), 245-270. 10.1111/fire.12034

Virgilio, G. (2016). The impact of high-frequency trading on marketing volatility. The Journal of Trading, 11(2), 55-63. 10.3905/jot.2016.11.2.055

Zhang, F. (2010). The effect of high-frequency trading on stock volatility and price discovery. Retrieved on March 25, 2017, http://ssrn.com/abstract=1691679.

Keywords Colocation, high frequency trading, global financial crisis, federal fund rates, equity returns, threshold cointegration, johannesburg stock exchange (JSE)
DOI http://dx.doi.org/10.15208/beh.2017.01
Pages 1-9
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