Topic: Capital Markets-Macro & Strategy Research
Report type: Global Multi-Asset Correlation Restructuring and Market Regime Shift Research Report (全球多资产相关性重构与市场范式切换研究报告)

Recently, the correlation structure among multiple asset classes in global financial markets has undergone notable changes, with some assets significantly deviating from their historical behavior patterns and exhibiting pronounced "outlier" characteristics. This has sparked market discussions about a potential regime shift.

In this context, please prepare an in-depth research report titled "Correlation Reconfiguration and Asset Anomalies: Is a Regime Shift Underway in Global Markets?" and address the following analytical tasks:

1. Changes in multi-asset correlation structure:
Based on major asset classes such as equities, bonds, foreign exchange, and commodities, compare recent market behavior with long-term benchmarks and previous structural regimes. Identify key manifestations of correlation reconfiguration and asset anomalies (e.g., weakening correlation between China’s equity and bond markets, diminished safe-haven properties of gold, and sustained high-level volatility in U.S. equities).

2. Drivers of asset anomalies:
Analyze the core factors driving deviations from historical correlations and pricing logic, incorporating perspectives from macroeconomic cycles, monetary policy divergence, geopolitical developments, and evolving industry themes. Distinguish between structural and cyclical influences.

3. Market regime assessment and portfolio implications:
Evaluate whether current market conditions reflect a short-term structural reshuffling or the emergence of a new medium-term asset pricing regime. Discuss the implications of unstable correlations for multi-asset allocation and risk management, and provide actionable strategy recommendations.

## Evaluation Criteria for the Research Report "Correlation Regime Rebuild and Asset Outliers: Is a Paradigm Shift Happening in Global Markets?"

This evaluation framework is designed to provide a systematic, actionable, and quantitative assessment of a deep research report covering: multi-asset correlation regime rebuild + outlier asset identification + causal attribution + paradigm-shift judgment + portfolio implications.

The framework contains 4 primary dimensions and 13 secondary dimensions, with a total score of 100 points. It supports both human review and consistent LLM-based automated scoring.

### 1. Quality of Key Findings and Insights (25 points)

#### (1) Clarity and Testability of Core Conclusions (10 points)
- 9-10: Explicitly answers whether a paradigm shift is occurring / which regime is more likely. Provides testable criteria (e.g., break tests, state-switching probability thresholds, key indicator trigger conditions) and time horizon (short-term / medium-term). Makes an explicit comparison against the market consensus narrative ("the market thinks... but based on ... we think...").
- 6-8: Conclusions are fairly clear, but criteria are mostly qualitative or missing triggers/time orientation; differences vs consensus and falsifiable points are not explicit enough.
- 0-5: Conclusions are vague or "argues both sides"; lacks testable standards and time dimension.

#### (2) "Incremental Insight" on Correlation Regime Rebuild (8 points)
- 7-8: Goes beyond describing correlation changes to identify structurally new features (e.g., "shifting from rate-driven to geopolitics/supply-shock-driven," "USD/real yields become a common cross-asset factor," "conditions under which the classic stock-bond hedge fails change"). Can pinpoint specific asset pairs/regions/tenors.
- 4-6: Some novelty, but largely extends common narratives (e.g., "inflation makes stocks and bonds move together"); lacks granular pinpointing and an evidence chain.
- 0-3: Mostly repeats common knowledge or provides news-style summaries; no meaningful incremental insight.

#### (3) Research Framework and Communication Structure (7 points)
- 6-7: Presents a clear framework (e.g., "measurement -> outlier identification -> attribution -> regime classification -> portfolio mapping"); chapter organization supports a closed-loop reasoning chain.
- 3-5: Structure is broadly complete, but key links (outlier definition / decision criteria / portfolio mapping) are broken or weak.
- 0-2: Loose structure; research path is hard to reproduce.

### 2. Rigor of Data, Measurement, and Methods (30 points)

#### (1) Data Coverage, Comparability, and Documentation (10 points)
- 9-10: Covers equities/bonds/FX/commodities (at minimum with representative indices or yield tenors and clearly defined conventions). Specifies data frequency, sample period, currency conventions, trading time zones, whether FX-hedged, and missing-value handling. Ensures comparability across "recent" vs "long-run benchmark" vs "prior regime".
- 6-8: Broad asset coverage, but insufficient convention details (e.g., mixed tenors, unclear currency basis), reducing credibility of some comparisons.
- 0-5: Data source/conventions unclear or asset representation insufficient, making conclusions non-verifiable.

#### (2) Appropriateness of Correlation Measures (8 points)
- 7-8: Uses at least two types of measures and explains when each is appropriate, e.g., rolling correlation + conditional correlation (DCC/GARCH) / quantile correlation / tail dependence (copula, co-ES). Discusses correlation bias under rising volatility and the limitation that "correlation != causality".
- 4-6: Uses basic methods such as rolling correlation, but lacks treatment/discussion of window choice, heteroskedasticity effects, or tail co-movement.
- 0-3: Only static correlations or a few screenshot-style results; methods cannot support claims of "structural change".

#### (3) Definition and Detection of "Outliers" (6 points)
- 6: Provides a clear, reproducible definition (covers at least one of: correlation outlier / pricing anomaly / volatility anomaly / tail anomaly, with explanation). Uses threshold rules or statistical tests (z-score, quantile thresholds, Mahalanobis distance, anomaly detection, extreme value theory, etc.) and explains false-positive control.
- 3-5: Describes outliers and uses simple thresholds, but lacks robustness (across windows/frequencies/baselines) or does not justify why the definition matches the research question.
- 0-2: Outliers selected subjectively based on narrative; not reproducible.

#### (4) Tests and Robustness for Structural Change / Paradigm Shift (6 points)
- 6: Uses at least one structural-change identification method (breakpoints/change-points: Bai-Perron, CUSUM; regime switching: Markov switching; correlation-network rebuild metrics, etc.) and performs robustness checks (different sample windows, frequencies, excluding crisis periods, alternative proxies).
- 3-5: Shows awareness of testing but relies on a single method or weak robustness; medium credibility.
- 0-2: Entirely qualitative "paradigm shift" claims with no verifiable support.

### 3. Causal Analysis and Structural vs Cyclical/Phase Distinction (25 points)

#### (1) Mechanism Chain: Macro Cycle and Policy Divergence (10 points)
- 9-10: Maps macro variables (inflation, growth, real rates, term premium, liquidity, fiscal expectations) to cross-asset pricing mechanisms (e.g., discount rates, risk premia, carry vs safe-haven channels). Validates with data or events (policy path divergence, rate differentials, inflation-expectation decompositions).
- 6-8: Mechanisms are broadly correct, but evidence is weak (missing key variables, lacking quantitative validation, or weak causal identification).
- 0-5: Slogan-like attribution ("rate hikes explain everything") without mechanism and evidence.

#### (2) Explanatory Power: Geopolitics, Supply Shocks, and Thematic Forces (7 points)
- 6-7: Links geopolitical risk, energy/shipping/supply-chain constraints, and themes (AI, energy transition, defense, etc.) to specific assets (commodity curves, related currencies, sector equities, credit spreads, etc.) and validates via event windows or risk-premium indicators.
- 3-5: Mentions factors, but mapping to asset outliers is loose; lacks verifiable evidence.
- 0-2: Generic discussion; cannot explain why those assets become outliers.

#### (3) Identification and Weighting of Structural vs Cyclical/Phase Effects (8 points)
- 7-8: Provides explicit criteria (persistence, changes in institutional/policy frameworks, permanent shifts in supply-demand curves, regime residence probabilities, etc.). Layers drivers into "structural" vs "phase" components and assesses relative weights (qualitative + quantitative where possible).
- 4-6: Attempts to distinguish but criteria are unclear, or weights are subjective.
- 0-3: No distinction, or distinction contradicts the evidence.

### 4. Market Regime Judgment, Portfolio Mapping, and Risk-Management Actionability (20 points)

#### (1) Regime-Decision Framework and Monitoring Indicators (8 points)
- 7-8: Proposes an executable "regime dashboard" (e.g., inflation/growth percentiles, real rates, USD liquidity, volatility and correlation metrics, risk appetite, cross-asset risk premia) with clear thresholds/triggers and update frequency.
- 4-6: Has a framework but lacks thresholds and operational details; hard to use for ongoing monitoring.
- 0-3: Purely subjective calls without a monitoring system.

#### (2) Implementability of Multi-Asset Allocation Recommendations (7 points)
- 6-7: Under unstable correlations, provides clear allocation principles and instruments (diversify factors rather than assets, dynamic hedging, risk budgeting/volatility targeting, cross-asset relative value, tail hedges). States applicability conditions, transaction costs/margin constraints, and potential side effects.
- 3-5: Directional advice exists, but lacks implementation path (which instruments, when to adjust, how to constrain drawdowns).
- 0-2: Generic advice such as "be cautious/diversify/time the market".

#### (3) Risk Management: Stress Tests, Tail Risk, and Model Risk (5 points)
- 4-5: Provides stress scenarios (policy re-acceleration, growth cliff, geopolitical escalation, liquidity tightening, etc.) and maps them to portfolio P&L. Discusses rising tail dependence and hedge failure; flags model risks (window sensitivity, non-stationarity, structural breaks) and mitigation measures.
- 2-3: Mentions stress tests or tail risk, but scenarios are vague or lacks portfolio-level implementation.
- 0-1: Barely addresses risk management or only lists risks formally.