High-Frequency Technical Analysis and Systemic Risk Indicators

58 Pages Posted: 16 Jun 2021

See all articles by Ryuichi Yamamoto

Ryuichi Yamamoto

Waseda University - School of Political Science and Economics

Date Written: June 9, 2021

Abstract

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

Yamamoto, Ryuichi, High-Frequency Technical Analysis and Systemic Risk Indicators (June 9, 2021). Available at SSRN: https://ssrn.com/abstract=3863084 or http://dx.doi.org/10.2139/ssrn.3863084

Ryuichi Yamamoto (Contact Author)

Waseda University - School of Political Science and Economics ( email )

1-6-1 Nishi-Waseda
Shinjuku-ku, Tokyo 169-8050, Tokyo 169-8050
Japan

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