High-Frequency Technical Analysis and Systemic Risk Indicators
58 Pages Posted: 16 Jun 2021
Date Written: June 9, 2021
This study conducts a high-frequency technical analysis of individual stocks listed on the Tokyo Stock Exchange. We propose novel technical rules that derive the timing of trades according to traditional systemic risks—such as shock-propagation, quote-stuffing, and tail risks—measured by auto- and cross-correlations in order flows, quote-to-trade ratios, and CoVaRs. We demonstrate that both price-based technical strategies—commonly used in technical analysis such as moving average rules—and the newly proposed rules can exploit the significantly superior performance to the buy-and-hold rule when we trade volatile momentum or trend-reversal stocks of small-sized firms. Accordingly, this study improves stock price forecasts in high-frequency trading. Our results suggest that historic prices and systemic risk indicators assist in the risk management and portfolio choices of stock investors. To the best of our knowledge, this is the first study to demonstrate the superior trading performance of individual stocks using a high-frequency technical analysis—even after considering data-snooping bias and transaction costs.
Keywords: technical analysis, high-frequency trading, systemic risk, CoVaR, data-snooping
JEL Classification: G12, G17, G14
Suggested Citation: Suggested Citation