State Street · Benjamin Regnat;Ying Lan;Divit Sinha · 08/31/2026

Expanding the sources of portfolio alpha with quant-anchored TAA

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Quant-anchored tactical asset allocation provides a disciplined, data-driven framework for identifying cross-asset opportunities—combining systematic signals, risk-aware portfolio construction, and experienced investment judgment to help allocators pursue differentiated sources of alpha within clearly defined risk parameters. Strategic and tactical asset allocation are both key components in shaping long-term investment outcomes. Strategic asset allocation (SAA) establishes the long-term target weights across asset classes, outlining an investor’s return objectives, risk tolerance, and investment timeframe, while tactical asset allocation (TAA) is an active overlay strategy designed to enhance returns relative to the strategic benchmark. By temporarily deviating from the long-term SAA, TAA seeks to add incremental value while supporting long-term investment objectives. This can result in an uncorrelated source of alpha compared to the alpha generated by the average active manager at the asset class level (Figure 1). Figure 1: TAA excess returns have historically shown low correlation to traditional active management Rolling 3-year correlation of median global TAA manager excess return versus median active global equity and fixed income managers (December 2013-December 2025) By introducing flexibility to enhance performance and manage risks, TAA offers notable benefits for institutional investors, including: Return enhancement: TAA strategies aim to identify investment opportunities to potentially capture excess returns, which can be anything from exploiting temporary mispricings or valuation anomalies across asset classes, sectors, or geographies, to aligning portfolio exposures with prevailing market or macroeconomic trends, such as interest rate shifts, inflation expectations, or geopolitical developments. Risk management and capital preservation: TAA’s dynamic mechanism allows investors to reduce exposure to riskier assets during periods of high volatility or uncertainty, thereby mitigating drawdowns and preserving capital. Understanding the level of risk aversion inherent in the capital markets is an important part of tactical asset allocation (Figure 2). Figure 2: Tactical growth asset positioning across market volatility cycles TAA aims to enhance a portfolio’s risk-adjusted performance. It can be a valuable complement to long-term strategic allocation frameworks that adds a layer of responsiveness and adaptability, contributing meaningfully to long-term investment success.

Considerations for designing a tactical asset allocation mandate

Designing an effective TAA mandate requires a thoughtful balance between flexibility, governance, and alignment with the broader investment framework. A well-designed TAA mandate must clearly define the extent of flexibility granted to the manager and the risk parameters within which tactical decisions can be made to ensure that the strategy remains aligned with the investor’s overall objectives while allowing room for value-added decisions. Risk budget is the maximum amount of risk the tactical strategy is allowed to take, relative to the strategic benchmark. It helps ensure that tactical decisions do not compromise the portfolio’s overall risk profile. Components of a risk budget may include tracking error limits, volatility targets, drawdown constraints, and other risk metrics such as value-at-risk (VaR). Tactical leeway: Tactical leeway refers to the range of permissible deviations from the strategic asset allocation. It sets the boundaries within which a manager can adjust exposures to asset classes, sectors, or geographies, such as allocation bands of asset classes. Tactical leeway can be either directional (across broad asset classes) or relative value-based (within equity, fixed income or commodity segments).

Comparing fundamental, quantitative, and combined TAA approaches

There are two foundational approaches to tactical asset allocation—fundamental and quantitative—with all combined approaches building on these two frameworks. The fundamental approach constructs and manages an investment portfolio based on analysis of the intrinsic value of assets. It relies more heavily on the expertise and judgment of analysts and portfolio managers over purely algorithmic or quantitative strategies. Portfolio managers analyze financial statements, industry trends, competitive positioning, management quality, and macroeconomic factors to evaluate different assets. The quantitative approach uses systematic models and data-driven algorithms to identify tactical opportunities and execute trades, reducing the influence of human biases and emotions. It utilizes extensive datasets so that the quantitative manager can provide a disciplined framework to evaluate market opportunities set. It also provides managers with a modular tool that can be leveraged across a global portfolio management team, and is easier to calibrate and tailor to meet the specific needs of clients based on their objectives and investment universe. Managers also combine the two approaches when implementing their tactical asset allocations, developing different ways of integrating these two foundations within the investment process to leverage the benefits of both. Based on eVestment global tactical asset allocations universe data, while quantitative TAA remains a relatively small share of industry assets, its differentiated return pattern and low correlation to other TAA approaches suggest it may offer allocators a potentially underutilized source of diversification (Figure 3).

Figure 3: eVestment global tactical asset allocation universe by investment approach (AUM weighted)

Portfolios employ a quantitative TAA strategy Portfolios employ a fundamental TAA strategy Portfolios employ a combined TAA strategy Source: eVestment, as of December 31, 2025.

The case for quant-anchored TAA

While fundamental and combined strategies account for most of the assets under management across the investment universe, employing quant-anchored tactical asset allocation (QTAA) approaches can offer additional advantages

1. Diversification

Quantitative frameworks and models enforce the systematic use of technical signals, rather than reliance on human judgment, which helps mitigate cognitive biases such as loss aversion and herding behavior. By screening a broad range of factors through disciplined, data-driven processes, quant-anchored approaches reduce the impact of emotional decision-making. Correlation analysis between median quantitative, fundamental, and combined managers further supports evidence of this differentiation (Figure 4). It is worth noting that this data shows significant differentiation exists even between the combined and quantitative TAA strategies. Figure 4: Quantitative TAA strategies show the lowest correlation with both fundamental and combined TAA strategies Source: eVestment, as of December 31, 2025. Data shows excess return correlation of median fundamental, quantitative and combined TAA managers for the past 10 years ending December 2025.

2. Scalability and customization capability

Quantitative TAA strategies rely on systematic portfolio construction processes, which can be efficiently implemented across multiple portfolios and asset bases while maintaining consistency and governance. They additionally allow managers the flexibility to configure parameters—risk budgets, eligible investment universes, and allocation constraints—tailoring portfolios to client‑specific objectives without altering the underlying methodology.

3. Transparency

Quantitative strategies are generally supported by back-testing, given their systematic structure and clearly defined decision rules. This enables investors to assess performance across different market regimes and evaluate the attribution of individual models to tactical views. This transparency supports better risk management and informed decision making. In contrast, fundamental approaches can be more esoteric in nature for clients, as they typically rely on the manager’s judgement and experience, reducing scope for back-testing.

4. Extension to absolute return-oriented objectives

Model-driven strategies provide flexibility in design and ongoing adjustments, enabling the development of multiple strategy types, including those focused on absolute return. Absolute return strategies can leverage quantitative models while placing greater emphasis on signals that enhance strategy agility and improve downside risk mitigation.

How State Street Investment Management approaches quantitative tactical asset allocations

While quantitative models allow for the analysis of large amounts of data in an efficient and repeatable way, they have their limitations. They lack the fundamental approach’s ability to address factors not fully captured by the quantitative models—political events, market disruptions, or unconventional policies. Thus, our investment process, anchored in a quantitative approach and refined with qualitative views, can offer a more effective way to exploit market inefficiencies and add value. Our approach is anchored in a quantitative mode while leveraging the vast experience and knowledge of our global portfolio managers to finalize views. These fundamental views are informed by collaboration across State Street Investment Management teams—including our economists and Macro Policy group—as well as independent research and sell-side publications and are integrated thoughtfully throughout the process.

Calibrating portfolios to shifting risk regime

Investor risk appetite is dynamic and can have implications on asset class performance, making it essential to measure risk appetite and calibrate the portfolio accordingly. Within our framework, we evaluate the top-down levels of risk aversion in the market by using our proprietary Market Regime Indicator (MRI) to gauge risk sentiment and guide directional positioning. For instance, in high-risk-aversion environments, investors often sell risky assets regardless of fundamentals. Hence, identifying and understanding the risk regime is an important part of managing tactical asset allocation portfolios.

Translating quantitative signals into tactical portfolio views

Our quant-anchored tactical asset allocation process relies on both top-down macro-economic factors and bottom-up factors like earnings and dividend yields, valuations, credit spreads, and momentum. Keeping in mind the client’s specific plan characteristics and risk tolerance, we set over- and under-weight positions across asset classes within the portfolio. This breakdown allows us to be more intentional in how we use our quantitative tools and allows us to further emphasize our discretionary insights. We evaluate macroeconomic conditions based on insights from and open discussions with internal investment teams, economists, and the Global Macro Policy team, as well as independent research firms and other third-party partners. These efforts focus on relevant geopolitical issues that may not be factored in by quantitative models but can impact markets. These interactions help us form our discretionary views. We thoughtfully leverage these qualitative views at each point in the process—evaluating the macro environment, asset class review, and final positioning—to ensure we benefit from the disciplined nature of the models without losing the flexibility of adapting to markets based on qualitative review. We categorize our investment opportunities into the following components for diversified alpha generation: Directional: across asset classes—equities vs bonds vs commodities Relative value: intra-asset class—equity by regions or credit vs treasury

Figure 5: State Street Investment Management TAA Models

1. Market Regime Indicator (MRI)—risk awareness 1. Market Regime Indicator (MRI)—risk awareness Positions for risk by adapting exposure across growth and defensive assets, with sizing proportional to the MRI signal strength. Optimized portfolio that uses return forecasts generated by our proprietary quantitative models. Leverages our proprietary Global Equity Model to make country, sector, region, size comparisons. Makes rate, credit comparisons across the treasury, investment grade, and high yield fixed income markets. Source: State Street Investment Management, as of June 2026. Portfolio construction evaluates both directional and relative value opportunities through a structured, multi‑layered governance process. Independent trade teams, each led by a senior portfolio manager, review the portfolio, assess proposed trades, and recommend refinements. These recommendations are then reviewed by the TAA Investment Group—comprising the senior portfolio managers leading each trade team—who debate ideas and agree on a set of consensus trades. A formal monthly “alpha” meeting is held to review model and optimization outputs, with asset‑class specialists engaged to challenge positioning and mitigate potential bias. Following final debate, trades are approved by the CIO and implemented across the platform. The team also conducts a mid‑month review to assess any material changes or regime shifts and retains the flexibility to convene on an ad‑hoc basis during periods of market dislocation or heightened uncertainty.

From model signals to active portfolio positioning

The following example shows how our four-sleeve QTAA framework translated directional and relative value signals into active portfolio positioning in January 2026. Directionally, our outlook for risk assets in January 2026 was constructive—signals from our quantitative framework reflecting supportive risk appetite and a more favorable environment for growth-oriented investments. In response to these developments, we increased our exposure to risk assets, positioning for potential upside given market conditions had improved, as illustrated in our directional MRI sleeve (Figure 6) and directional alpha sleeve (Figure 7). On the relative value trades side, our regional equity outlook continued to favor US equities and, to a lesser extent, emerging markets. Accordingly, we maintained our overweight allocations to the US and emerging markets, funded by underweight positions in non-US developed equities (Figure 8). On the relative value fixed income side (Figure 9), our fixed income outlook called for a smaller decline in yields and a more constructive stance on credit. Softer commodity momentum and mean reversion still pointed to lower yields, though stronger equity momentum would limit the magnitude of the decline. Credit spreads were expected to tighten, supported by lower rates, improved risk appetite, and reduced equity volatility. We trimmed our overweight in long Treasuries and rotated into long credit bonds. The improved outlook for spreads made this move an opportunity to enhance returns without significantly altering duration profile. Figure 9: Relative value fixed income sleeve Figure 11: State Street Investment Management TAA model portfolio active changes, January 2026 Source: State Street Investment Management, as of January 2026.

QTAA: A disciplined framework to pursue differentiated tactical alpha

QTAA offers institutional investors a disciplined, data-driven approach for targeting portfolio performance and managing risk by capturing uncorrelated sources of alpha across a broad range of asset classes. By leveraging diversification, scalability, transparency, and customization, QTAA strategies stand out as a robust approach for navigating complex markets. At State Street Investment Management, our quant-driven models are complemented by qualitative investment judgment to help interpret signals in the context of evolving market conditions. This quant-anchored, qualitatively informed approach is designed to support more adaptive portfolio positioning while maintaining the discipline and governance institutional investors require. State Street Global Advisors (SSGA) is now State Street Investment Management. Please click here for more information. Investing involves risk including the risk of loss of principal. The whole or any part of this work may not be reproduced, copied or transmitted or any of its contents disclosed to third parties without State Street Investment Management’s express written consent.

Publisher disclaimer

All information is from State Street Investment Management unless otherwise noted and has been obtained from sources believed to be reliable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy, reliability or completeness of, nor liability for, decisions based on such information, and it should not be relied on as such. The views expressed in this material are the views of the authors through the period ended June 30, 2026, and are subject to change based on market and other conditions. This document contains certain statements that may be deemed forward looking statements. Please note that any such statements are not guarantees of any future performance and actual results or developments may differ materially from those projected. The information provided does not constitute investment advice and it should not be relied on as such. It should not be considered a solicitation to buy or an offer to sell a security. It does not take into account any investor’s particular investment objectives, strategies, tax status or investment horizon. You should consult your tax and financial advisor. SSGA uses quantitative models in an effort to enhance returns and manage risk. While SSGA expects these models to perform as expected, deviation between the forecasts and the actual events can result in either no advantage or in results opposite to those desired by SSGA. In particular, these models may draw from unique historical data that may not predict future trades or market performance adequately. There can be no assurance that the models will behave as expected in all market conditions. In addition, computer programming used to create quantitative models, or the data on which such models operate, might contain one or more errors. Such errors might never be detected, or might be detected only after the Portfolio has sustained a loss (or reduced performance) related to such errors. Availability of third-party models could be reduced or eliminated in the future. The information contained in this communication is not a research recommendation or ‘investment research’ and is classified as a ‘Marketing Communication’ in accordance with the Markets in Financial Instruments Directive (2014/65/EU) or applicable Swiss regulation. This means that this marketing communication (a) has not been prepared in accordance with legal requirements designed to promote the independence of investment research (b) is not subject to any prohibition on dealing ahead of the dissemination of investment research. This communication is directed at professional clients (this includes eligible counterparties as defined by the appropriate EU regulator) who are deemed both knowledgeable and experienced in matters relating to investments. The products and services to which this communication relates are only available to such persons and persons of any other description (including retail clients) should not rely on this communication. Equity securities may fluctuate in value and can decline significantly in response to the activities of individual companies and general market and economic conditions. Bonds generally present less short-term risk and volatility than stocks, but contain interest rate risk (as interest rates raise, bond prices usually fall); issuer default risk; issuer credit risk; liquidity risk; and inflation risk. These effects are usually pronounced for longer-term securities. Any fixed income security sold or redeemed prior to maturity may be subject to a substantial gain or loss. Generally, among asset classes, stocks are more volatile than bonds or short-term instruments. Government bonds and corporate bonds generally have more moderate short-term price fluctuations than stocks, but provide lower potential long-term returns. Asset Allocation is a method of diversification which positions assets among major investment categories. Asset Allocation may be used in an effort to manage risk and enhance returns. It does not, however, guarantee a profit or protect against loss. Diversification does not ensure a profit or guarantee against loss. The trademarks and service marks referenced herein are the property of their respective owners. Third party data providers make no warranties or representations of any kind relating to the accuracy, completeness or timeliness of the data and have no liability for damages of any kind relating to the use of such data. Index returns reflect capital gains and losses, income, and the reinvestment of dividends. Index returns are unmanaged and do not reflect the deduction of any fees or expenses. The performance data quoted represents past performance. Past performance does not guarantee future results. State Street Global Advisors Worldwide Entities © 2026 State Street Corporation. All Rights Reserved. 9058940.1.1.GBL.INST Exp. Date: August 31, 2027

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Key arguments

TAA provides an uncorrelated source of alpha compared to traditional active management.
Quantitative TAA strategies offer discipline, scalability, transparency, and customization.
Quantitative models reduce cognitive biases such as loss aversion and herding.
Combining quantitative models with qualitative judgment enhances adaptability.
The Market Regime Indicator helps gauge risk sentiment and guide positioning.

Risks

Quantitative models may not capture political events, market disruptions, or unconventional policies.
Investor risk appetite is dynamic and can affect asset class performance.
Tactical decisions may involve tracking error and drawdown risks.