Research Accepted by Internationally Recognized Finance Journal Finance Research Letters to Be Implemented in WealthForce

MONO Investment Co., Ltd. (Headquarters: Shinagawa-ku, Tokyo; Co-CEOs: Tatsu Sasaki / Ryo Nakanishi; hereinafter "the Company") announces that the paper titled "Subspace regularized principal component analysis using prior exposure information," authored by Professor Kei Nakagawa of the Graduate School of Business, Osaka Metropolitan University—technology advisor to the Company—has been accepted for publication in Finance Research Letters, an internationally recognized peer-reviewed journal in the field of finance.

This research addresses a key challenge in the continuous application of PCA (Principal Component Analysis)—a widely used method in asset management and risk control—where the ordering and interpretation of factors tend to shift over time, leading to unstable and difficult-to-interpret analytical results. To resolve this, the study proposes Subspace-Regularized PCA (SR-PCA), a novel method that stabilizes the factor space (i.e., the major directions of risk factors) by incorporating economically meaningful prior exposure information.

The Company will progressively integrate this research into its AI-powered factor analysis engine, "MONO FactorLens," and deliver it via its advisor-focused CRM platform "WealthForce" and through APIs for financial institutions. This enables banks, securities firms, and IFAs to understand client portfolios not merely in terms of asset class allocations, but in terms of their sensitivity to macroeconomic factors such as economic growth, interest rates, and inflation, thereby allowing clearer explanations of investment rationale and the need for portfolio reviews.

Key Highlights of the Announcement

- A paper co-authored by Kei Nakagawa, technology advisor to MONO Investment and Professor at Osaka Metropolitan University, has been accepted by Finance Research Letters, a globally recognized finance journal.

- The study proposes SR-PCA to address the instability in factor ordering and interpretation that arises when PCA is applied continuously over time.

- The research findings will be incorporated into MONO FactorLens and progressively implemented in WealthForce and financial institution APIs.

- Client portfolio risk factors will be visualized through macroeconomic lenses such as economic growth, interest rates, and inflation.

- Supports standardization of advisory quality, explanation obligations, and ongoing post-sales follow-up at banks and securities firms.

Background: The Hidden "Reasons for Risk" Not Visible Through Asset Allocation Alone

In asset management recommendations at banks and securities firms, it is increasingly important not only to visualize clients’ holdings but also to explain "why this recommendation?" and "which market conditions should be monitored." However, relying solely on asset class breakdowns often fails to reveal which underlying risk factors a portfolio is truly exposed to.

MONO FactorLens is an analytical engine that visualizes these hidden risks by decomposing them into macroeconomic factors such as economic growth, interest rates, and inflation. Integrated into WealthForce, it enables advisors to explain to clients not only asset allocations but also "what their portfolio is sensitive to" and "what should be reviewed" from a macro-factor perspective.

Research Findings: Stabilizing the Factor Space for More Interpretable Risk Analysis

PCA is widely used to extract major risk factors from market data. However, when PCA is applied repeatedly with updated data, the order and interpretation of factors can shift over time—posing challenges for consistent client reporting and post-sale advisory follow-up.

The proposed SR-PCA method flexibly extracts factors from market data while incorporating economically meaningful prior exposure information, thereby stabilizing the factor space—i.e., the overarching directions of risk factors.

Through validation using multi-asset panels, Fama-French portfolios, and minimum variance portfolio construction, the study confirms that, compared to standard rolling PCA, SR-PCA reduces mid-term fluctuations in factor space and turnover in factor portfolios, while maintaining comparable reconstruction accuracy and usefulness as a risk model.

The goal of this research is not to predict future returns, but to enable more stable and interpretable analysis of portfolio risk factors.

Application in WealthForce

By integrating these research findings into MONO FactorLens, WealthForce will enable the following analyses and explanations:

- Economic Growth Factor: Explain sensitivity to changes in economic conditions and corporate earnings

- Interest Rate Factor: Explain the impact of rising or falling interest rates on bonds, REITs, etc.

- Inflation Factor: Explain sensitivity to inflation, commodity prices, and exchange rate movements

- Risk-based Diversification: Identify concentration risks not by asset class, but by actual underlying risk factors

- Rebalancing Recommendations: Visualize which risks a rebalancing action aims to reduce

Financial institutions will be able to explain not only expected returns and risk levels, but also how exposure to specific macro factors improves before and after a recommendation. Additionally, they can monitor how individual client portfolios are sensitive to changing market conditions, enabling targeted follow-ups and rebalancing suggestions.

Future Developments

The Company plans to progressively roll out the SR-PCA-based macro factor analysis functionality within WealthForce, integrating it with client reporting, AI-generated analysis commentary, stress scenario analysis, and Monte Carlo simulations. The functionality will also be offered as an API for banks and securities firms, enabling integration with existing CRM systems, proposal generation tools, and client portals.

Comments

Kei Nakagawa, Technology Advisor, MONO Investment Co., Ltd. (Professor, Graduate School of Business, Osaka Metropolitan University)

"In asset management practice, it is crucial not only to present portfolio risk as a number but also to explain which economic factors drive that risk. At the same time, for factor analysis to be used continuously in practice, the model outputs must be stable and economically interpretable. I hope this research, through its implementation in WealthForce, will support financial institutions and advisors in delivering clear, understandable, and convincing investment advice to clients."

Tatsu Sasaki, Co-CEO, MONO Investment Co., Ltd.

"We believe this research represents a critical step forward from WealthForce’s original goal of ‘visualizing assets’ toward ‘explaining the reasons behind risk.’ In financial advisory, it’s not enough for analysis to be sophisticated—it must also be clearly explainable to clients and usable in daily operations. We are committed to turning research into practical product features that seamlessly integrate into existing workflows at financial institutions."

Paper Information

Title: Subspace regularized principal component analysis using prior exposure information Journal: Finance Research Letters Authors: Kei Nakagawa (Graduate School of Business, Osaka Metropolitan University / MONO Investment, Inc.) Masahiro Kato (Graduate School of Business, Osaka Metropolitan University / Mizuho First Financial Technology Co., Ltd.) Mitsuyoshi Imamura (Department of Systems and Information Engineering, University of Tsukuba)

About MONO FactorLens

MONO FactorLens is an AI-powered factor analysis engine developed by MONO Investment Co., Ltd. Based on client holdings data obtained via securities account linkage, it provides asset class breakdowns, risk-return metrics, and future simulations, while also decomposing and visualizing portfolio risk factors at the factor level.

About WealthForce

WealthForce is a CRM and operational support platform for wealth advisors at banks, securities firms, and IFAs. It supports end-to-end advisory workflows, including client management, case tracking, securities account integration, asset visualization, risk analysis, future simulations, and proposal generation.

Inquiries

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For those interested in asset analysis APIs

We offer advanced analytics for portfolio analysis, investment simulation, and life planning as APIs. Our financial intelligence can be flexibly integrated into existing business systems, web services, or client-facing applications. Please contact us via the form below.

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For individual investors seeking advanced portfolio analysis and advisory services

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About MONO Investment Co., Ltd.

Company Name: MONO Investment Co., Ltd. Founded: January 29, 2020 Leadership: Tatsu Sasaki, Ryo Nakanishi Headquarters: Shinagawa South Tower, 4-4-1 Minami-Shinagawa, Shinagawa-ku, Tokyo Capital: 283,101,200 JPY (including capital reserves) Main Business: Development and operation of web services

The Company develops and provides WealthForce, a digital advisory support tool for banks, securities firms, and IFAs. WealthForce enhances operational efficiency and sophistication by offering client data management, asset analysis, and client-facing proposal support. Additionally, the Company operates "Investment Concierge," a financial media and asset management service for individual investors, to promote informed wealth building.

Inquiry Form: https://monoinv.com/contact WealthForce Website: https://wealthforce.jp/ Investment Concierge: https://www.invest-concierge.com/ Corporate Site: https://monoinv.com/

Note

The analytical models and features described in this release do not guarantee investment performance, nor do they predict or guarantee future market conditions or price movements of individual assets. WealthForce and MONO FactorLens are designed to support financial institutions and advisors in analyzing, explaining, and recommending client portfolios.