The adaptive market hypothesis and high frequency trading
1School of Public Policy and Management, Tsinghua University, Beijing, China.
Plos One
|December 17, 2021
Summary
High-frequency trading (HFT) activity increases during periods of low market efficiency, suggesting traders adapt their strategies based on information processing and market conditions. This supports the adaptive market hypothesis.
Area of Science:
- Financial Economics
- Market Microstructure
- Behavioral Finance
Background:
- Market efficiency describes how quickly prices reflect information.
- High-frequency trading (HFT) involves rapid automated trading strategies.
- The adaptive market hypothesis (AMH) posits that market efficiency fluctuates.
Purpose of the Study:
- To investigate the relationship between informational market efficiency and HFT activity.
- To analyze S&P 500 exchange-traded fund (SPY) order book data.
- To test the applicability of the adaptive market hypothesis.
Main Methods:
- Utilized one-minute NASDAQ order book data for SPY.
- Analyzed temporal variations in informational market efficiency.
- Quantified HFT activity levels.
Main Results:
- Market efficiency levels exhibit significant temporal variation and clustering.
- Periods of high efficiency are followed by periods of low efficiency, and vice versa.
- HFT activity is demonstrably higher during periods of lower market efficiency.
Conclusions:
- HFT strategies appear adaptive, with increased activity during less efficient periods.
- Traders adjust strategies from active information processing to passive market-making.
- Findings support the adaptive market hypothesis as a model for price discovery.
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