Empirical Finance Research
Rigorous investigation of investment questions using quantitative and evidence-based methodologies.
Research Driven Consulting for Asset Managers
K2Q Capital Limited
We combine academic research, artificial intelligence, alternative data, quantitative finance, and practical market knowledge to translate complex research questions into actionable investment insights.
Who We Are
We act as an external research partner for investment teams
K2Q operates at the intersection of academic research and institutional asset management, combining rigorous method with practical insights.
Research
K2Q
Application
AI, Machine Learning & Alternative Data
Applying advanced technologies and unconventional information sources to uncover information traditional approaches may miss.
Institutional Investment Understanding
Research designed around the practical questions, constraints, and decision-making processes of investment teams.
Japanese Financial Markets Expertise
Specialized knowledge and research capabilities focused on Japanese equities and financial markets.
Research-to-Hypothesis Translation
Moving from an academic or investment question to a testable and potentially investable research hypothesis.
Our Position
Between academia and institutional asset management.
We combine the depth and rigor of academic research with the practicality and relevance of institutional investment management, independently developing evidence-based research that can inform investment decisions.
What We Do
Research built around the investment question.
We work with investment teams on research questions that require deeper empirical investigation than is normally possible within the day-to-day investment process.
Projects may begin with a market observation, an academic finding, a proprietary hypothesis, or a new dataset.
How We Work
We begin with the question,
not with a predetermined model.
From investment questions to investment applications.
01
Investment Question
- Is there information in a dataset that the market is not fully processing?
- Does an existing investment signal survive more rigorous testing?
- Can AI identify economically meaningful relationships that conventional classifications miss?
- Why does an investment strategy work, and under what conditions does it fail?
- 02
Research Design
We identify the appropriate data, empirical methodology, benchmark, and identification strategy.
- 03
Validation
We test robustness, alternative explanations, factor exposures, out-of-sample behaviour, economic significance, and, where relevant, implementation considerations.
- 04
Investment Application
The research is translated into a form that an investment team can evaluate and potentially incorporate into its research process. This may include a signal, portfolio framework, research model, prototype, or decision-support tool.
Depending on the research question, the outcome may be a signal, portfolio framework, research model, prototype, or decision-support tool that an investment team can evaluate within its own process.
Research Highlights
Featured Research & Application
Research that challenges conventional ways of observing the market.
AI & Corporate Disclosures
From Words to Returns: Sentiment Analysis of Japanese 10-K Reports Using Advanced Large Language Models
Advanced LLMs extract investment-relevant information from corporate disclosures that conventional methods may miss, using large-scale Japanese filings.
Peer-Reviewed Research
PeerJ Computer Science, 2025
K. Okada, M. Nakasuji, Y. Tsukioka, T. Yamasaki
Dynamic Investment Themes
Momentum Without Momentum: Text-Based Themes and Return Predictability in Japan
Text-based themes connect economically related companies across sector boundaries, revealing return predictability even in a momentum-weak market.
Research in Progress
Deep Learning & Market Information
Decoding the Unique Price Behavior in the Japanese Stock Market with Convolutional Neural Networks
Using convolutional neural networks on price charts, this study uncovers patterns in market behavior that conventional models may fail to capture.
Research in Progress
Meet the Team
The people behind K2Q
Aman Oberoi
CEO & PM
Mr Oberoi has been trading Japanese equities and derivatives in various capacities since 1989, including establishing and running Citibank’s Japanese Equity derivatives business. During his 16 year stint at Citigroup he started and ran various derivative trading businesses in New York, Tokyo and London. He was also a member of the EM Macro Proprietary trading group at Citigroup. From 2007 onwards as Managing Director he ran Bank Sal Oppenheim's trading, quantitative research and technology business in Zurich and Frankfurt. In his most recent position, he was a Senior MD and member of the Executive Committee at Mizuho International Plc, London. He has a B. S. in Electrical Engineering and Computer Science from Duke University and an MBA from the University of North Carolina at Chapel Hill.
Katsuhiko Okada
Head of Research
Mr Okada is a tenured Professor of Finance at Kwansei Gakuin University, and his research interest is in behavioural asset pricing. He founded and runs Magne-Max Capital, based in Osaka, and works very closely with K2Q Capital in research and development. Mr Oberoi and Mr Okada have worked together since 2011 and have known each other since 1994. He co-founded a hedge fund management firm, Halberdier Capital, in Singapore in 1997. Mr Okada currently serves as president of the JFA and publishes influential papers on asset management in Japan. He holds an MBA from Washington University’s John M. Olin School of Business and a PhD in financial economics from Kobe University.
Maxwell Trautman
Risk and Investor relations (External)
Max has extensive experience in global macro trading, risk management and fund raising. Currently, CEO of his firm New Sparta Asset Management focusing on renewable energy investments. Previously a portfolio manager at Millennium Capital Partners. A founder and CIO of Stoneworks Asset Management LLP that managed the Investcorp Stoneworks Global Macro Hedge Fund with an AUM of over $500MM. A founding partner at Peloton Partners Hedge Fund. Executive director at Goldman Sachs where he was proprietary trading first at J Aron FX and Commodity division in New York and later at FICC (Fixed Income Currencies and Commodities) team in London. He started his financial career as Vice President at Citibank in EM Structured products in New York. Max has a BA in International Relations from American University and an MA in International Banking and Economics from Columbia University.