Predictor Choice, Investor Types, and the Price Impact of Trades on the Tokyo Stock Exchange

Ryuichi Yamamoto*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Several agent-based theoretical models demonstrate that the fundamental or trend-following predictor, or the dynamic predictor selection between them, is the main generator of price deviation from fundamental value. However, little research has empirically attempted to determine which theory has the most explanatory power on the empirical phenomenon. This study empirically identifies which predictor is most commonly utilized by actual investors and causes the empirical feature. We identify that life or postal life insurance entities, trust banks, industrial corporations, and other corporations (branches of foreign companies located in Japan or corporations related to governments, employee stock ownership, or labor unions) interchangeably switch fundamental and technical rules over time. We also find individual investors, security companies, and investment trusts to be fundamentalists, while foreign investors are trend-followers, and investors involved in proprietary trading and other financial institutions are contrarians. Furthermore, we demonstrate that all the investors in our sample have experienced a significant price impact in their trades. Our findings provide broad support for several types of agent-based models for the generation of the empirical feature in financial markets. In addition, trust banks—considered long-term investors—use a dynamic predictor selection between fundamental and technical rules but use a contrarian strategy for their technical rule. Meanwhile, trend-following foreign investors—the most active investors in our sample—are usually short-term. Therefore, our evidence on the price impact of their trades is consistent with the finding in Fama and French (J Finance 57: 637–659, 2002) that price momentum persists in the short and medium terms but reverses in the long term. We demonstrate our result by using a unique panel dataset on order flows by investor type from the Tokyo Stock Exchange that covers 87% of the total market volume.

Original languageEnglish
Pages (from-to)325-356
Number of pages32
JournalComputational Economics
Issue number1
Publication statusPublished - 2022 Jan


  • Investor types
  • Predictor choice
  • Price impact
  • Tokyo stock exchange

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications


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