3 papers in the archive (2025–2026), average empirical rigor 3.7/10, average math complexity 4.3/10. Quadrant mix: Lab Rats ×1, Philosophers ×2.
Works mostly in Market Simulation & Agent-Based Models, Market Microstructure, High-Frequency Trading & Optimal Execution.
Frequent co-authors: Isao Yagi (3), Shuto Endo (1), Ryuki Hayase (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
Order book imbalance (OBI) - buy orders minus sell orders near the best quote - measures supply-demand imbalance that can move prices. OBI is positively correlated with returns, and some investors try to use it to improve performance. Large orders placed at once can reveal intent, invite front-runni
Leveraged ETFs (L-ETFs) are exchange-traded funds that achieve price movements several times greater than an index by holding index-linked futures such as Nikkei Stock Average Index futures. It is known that when the price of an L-ETF falls, the L-ETF uses the liquidity of futures to limit the decli
Some investors say increasing investors with the same strategy decreasing their profits per an investor. On the other hand, some investors using technical analysis used to use same strategy and parameters with other investors, and say that it is better. Those argues are conflicted each other because