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The Journal of Portfolio Management

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ETFs, High-Frequency Trading, and Flash Crashes

Irene Aldridge
The Journal of Portfolio Management Fall 2016, 43 (1) 17-28; DOI: https://doi.org/10.3905/jpm.2016.43.1.017
Irene Aldridge
is a managing director of research and development at , Able Alpha Trading, Ltd., and BigDataFinance.org in New York, NY.
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  • For correspondence: irene@ablemarkets.com
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Abstract

This article presents a model of distributional properties of returns on financial instruments tied to exchange traded funds (ETFs) via high-frequency statistical arbitrage. As the author’s model shows, the securities subject to an ETF arbitrage exhibit a well-defined behavior, largely dependent on the behavior of other securities comprising the ETF. The model can be used to improve the risk management of long-term portfolios and, in particular, allow hedging of flash crashes. Furthermore, the author shows that in electronic markets that allow high-frequency trading, the intraday downward volatility for the underlying securities constituting an ETF is bounded from below; as a result, it is less extreme than that of securities not included in any ETFs. Also, downward price movements are more extreme in markets that restrict high-frequency trading than in markets in which it is present.

TOPICS: Exchange-traded funds and applications, statistical methods

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The Journal of Portfolio Management: 43 (1)
The Journal of Portfolio Management
Vol. 43, Issue 1
Fall 2016
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ETFs, High-Frequency Trading, and Flash Crashes
Irene Aldridge
The Journal of Portfolio Management Oct 2016, 43 (1) 17-28; DOI: 10.3905/jpm.2016.43.1.017

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ETFs, High-Frequency Trading, and Flash Crashes
Irene Aldridge
The Journal of Portfolio Management Oct 2016, 43 (1) 17-28; DOI: 10.3905/jpm.2016.43.1.017
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  • Article
    • Abstract
    • MODELING THE IMPACT OF HFT ETF ARBITRAGE ON OTHER FINANCIAL INSTRUMENTS
    • HOW DO THESE THEORETICAL INFERENCES HOLD UP TO DATA?
    • ANALYSIS
    • BANNING ETFS?
    • CONCLUSIONS
    • ENDNOTES
    • REFERENCES
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