Research ArticleOpen AccessGoogle Scholar indexed
Modelling Intervalling Effect of High Frequency Trading on Portfolio Volatility
College of Business Administration, Hongik University, Seoul, South Korea
- 1 College of Business Administration, Hongik University, Seoul, South Korea
Theoretical Economics Letters·Volume 09 (2019)·Pages 2362–2370·Published 29 August 2019·DOI10.4236/tel.2019.97150
Copy link · social · email
Abstract
This paper theoretically examines whether reducing the minimum trading interval could affect portfolio volatility. Modelling the underlying de-trended asset price with Ornstein Uhlenbeck process, the paper investigates the volatility of portfolios that employ buy and hold strategy and momentum strategy. The paper presents theoretical evidence that the fast trading could increase portfolio price fluctuation and hence potentially suggests another cost of high frequency trading, besides the well-known damages including herding, aggressive trading strategies dark pools, immediate-or-cancel type orders.
KeywordsVolatilityFast TradingMomentum TradingTime Series MomentumIntervalling Effect
- Zhang F. (2010) The Effect of High-Frequency Trading on Stock Volatility and Price Discovery. Working Paper. https://doi.org/10.2139/ssrn.1691679
- Hasbrouck, J. and Saar, G. (2011) Low-Latency Trading. Working Paper. https://doi.org/10.2139/ssrn.1695460
- Glode, V., Green, R.C. and Lowery, R. (2012) Financial Expertise as an Arms Race. The Journal of Finance, 67, 1723-1759. https://doi.org/10.1111/j.1540-6261.2012.01771.x
- Pogue, G.A. and Solnik, B.H. (1974) The Market Model Applied to European Common Stocks: Some Empirical Results. Journal of Financial and Quantitative Analysis, 9, 917-944. https://doi.org/10.2307/2329728
- Levhari, D. and Levy, H. (1977) The Capital Asset Pricing Model and the Investment Horizon. The Review of Economics and Statistics, 59, 92-104. https://doi.org/10.2307/1924908
- Dimson, E. (1979) Risk Measurement When Shares Are Subject to Infrequent Trading. Journal of Financial Economics, 7, 197-226. https://doi.org/10.1016/0304-405X(79)90013-8
- Corhay, A. (1988) The Adjustment for the Intervalling Effect Bias in Beta: A Broader and Multi Period Test. European Institute for Advanced Studies in Management, Brussels, Working Paper No. 88, 26.
- Handa, P., Kothari, S.P. and Wasley, C. (1993) Sensitivity of Multivariate Tests of the Capital Asset-Pricing Model to the Return Measurement Interval. Journal of Finance, 48, 1543-1551. https://doi.org/10.1111/j.1540-6261.1993.tb04767.x
- Hendershott, T., Jones, C.M. and Menkveld, A.J. (2010) Does Algorithmic Trading Improve Liquidity? The Journal of Finance, 66, 1-33. https://doi.org/10.1111/j.1540-6261.2010.01624.x
- Bergstrom, A.R. (1990) Continuous Time Econometrics Modelling. Oxford University Press, Oxford.
- Lo, A.W. and Wang, J. (1995) Implementing Option Pricing Models When Asset Returns Are Predictable. Journal of Finance, 50, 87-129. https://doi.org/10.1111/j.1540-6261.1995.tb05168.x
- Kramer, R. and Richter, M. (2007) A Generalized Bivariate Ornstein-Uhlenbeck Model for Financial Assets. Tagungsband zum Workshop ‘Stochastische Analysis’. Chemnitz.
- Onalan, O. (2009) Financial Modelling with Ornstein-Uhlenbeck Processes Driven by Levy Process. Proceedings of the World Congress on Engineering, London, 1-3 July 2009, 1-6. https://doi.org/10.1007/978-90-481-8776-8_38
- Hong, K. and Satchell, S. (2015) Time Series Momentum Trading Strategy and Autocorrelation Amplification. Quantitative Finance, 15, 1471-1487. https://doi.org/10.1080/14697688.2014.1000951