Prediction Markets: Know the Future, Prepare for the Future
A Japanese-language book on prediction markets as institutions for both learning about the future and preparing for it, now available on Amazon Kindle.
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Researcher Profile
Researches firm value creation through generative AI, information aggregation in prediction markets, machine learning in asset management, and causal analysis of capital-market reform.
Graduated from the Department of Electrical and Electronic Engineering, Faculty of Engineering, Kyoto University, in March 2025, and entered the master's program at the Graduate School of Economics, Kyoto University, in April 2025. He applies the quantitative and mathematical perspective developed through engineering to empirical research in economics and finance. His master's thesis conducts a causal empirical analysis of how TOPIX reform affected the liquidity, volatility, and co-movement with TOPIX of the securities targeted by the reform.
Research spanning firm value, information aggregation, asset management, and capital-market institutions through data-driven economic and financial analysis.
A Japanese-language book on prediction markets as institutions for both learning about the future and preparing for it, now available on Amazon Kindle.
Following the same 1,818 Polymarket markets from 30 days to 12 hours before operational closure, this study measures when and by how much Brier loss declines.
A financial framework that traces generative AI usage through effective work outputs, NOPAT, ROIC, EVA, and firm value while distinguishing AI-related invested capital from AI utilization capital.
An empirical study examining whether machine learning-based strategy allocation adds value over traditional portfolio construction methods such as Equal Weight and Risk Parity.