利用量化锚定的战术资产配置拓展组合阿尔法来源

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.

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).

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).

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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 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.