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.
Empirical Finance Research
Rigorous investigation of investment questions using quantitative and evidence-based methodologies.
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.
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.
Research built around the investment question.
Bespoke Investment Research
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.
We begin with the question,
not with a predetermined model.
From investment questions to investment applications.
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?
Research Design
We identify the appropriate data, empirical methodology, benchmark, and identification strategy.
Validation
We test robustness, alternative explanations, factor exposures, out-of-sample behaviour, economic significance, and, where relevant, implementation considerations.
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.
Featured Research & Application
Research that challenges conventional ways of observing the market.
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.
PeerJ Computer Science, 2025
K. Okada, M. Nakasuji, Y. Tsukioka, T. Yamasaki
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.
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.
The people behind K2Q
Reg No. 10209435 (England and Wales).
Registered office at Alliance House, 29 - 30 High Holborn, London WC1V 6AZ, United Kingdom.