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In-depth Analysis of Multi-Factor Combination Mechanisms and Bull-Bear Market Performance of Strategy-Based Value Indices

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December 15, 2025
In-depth Analysis of Multi-Factor Combination Mechanisms and Bull-Bear Market Performance of Strategy-Based Value Indices

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In-depth Analysis of Multi-Factor Combination Mechanisms and Bull-Bear Market Performance of Strategy-Based Value Indices
1. Core Mechanisms of Multi-Factor Combinations to Improve Win Rates
1.1 Theoretical Basis of Multi-Factor Models

Strategy-based value indices effectively improve A-share investment win rates through systematic multi-factor combinations, with core mechanisms reflected in four dimensions:

Value Factor Enhancement
: Screen undervalued stocks based on valuation indicators such as PE, PB, PS to provide a margin of safety for the portfolio [0]

Quality Factor Improvement
: Select high-quality companies through financial indicators such as ROE, ROA, and cash flow to enhance long-term profit stability

Volatility Factor Control
: Introduce low volatility factors to reduce portfolio systemic risk and provide defensive capabilities during market declines

Momentum Factor Capture
: Combine price momentum trends to capture short-term upward momentum and improve medium-term returns

1.2 Optimized Design of Sampling Mechanisms

789eaf11_multi_factor_analysis.png

As can be seen from the chart, multi-factor value strategies achieve risk-return optimization through scientific factor weight allocation:

  • Value Factor
    (30% weight): Provides basic margin of safety
  • Quality Factor
    (30% weight): Ensures healthy corporate fundamentals
  • Low Volatility Factor
    (20% weight): Reduces portfolio volatility
  • Momentum Factor
    (20% weight): Captures trend opportunities

This balanced weight design allows the strategy to maintain the core of value investing while significantly improving adaptability in different market environments.

1.3 Innovative Breakthroughs in Weighting Methods

Traditional market capitalization weighting has a “large-cap bias” problem, while strategy-based value indices adopt innovative methods such as

factor weighting
,
equal weighting
, or
fundamental weighting
:

  • Factor Weighting
    : Allocates weights based on comprehensive factor scores, with advantageous factors receiving higher allocations
  • Equal Weighting
    : Avoids over-concentration and reduces individual stock risk
  • Fundamental Weighting
    : Allocates weights based on fundamental indicators such as revenue and profit
2. Performance Differences in Bull and Bear Markets and Risk-Return Characteristics
2.1 Offensive Performance in Bull Markets

8aa0aa18_bull_bear_analysis.png

In bull market environments, the performance of various strategies shows significant differences:

Huazheng Value Preferred 50
performed the most outstandingly, with an annualized bull market return of 25.54% and a win rate of 75%, reflecting the advantages of selected individual stock strategies in bull markets

CSI 300
as a broad-based benchmark had the highest bull market return of 28.06%, but also the largest volatility (14.73%), with moderate risk-adjusted returns

CSI Value 100
and
CSI Smart Select 300 Value Stable
showed balanced performance, with returns of 15.12% and 14.97% respectively

Dividend Value Index
had relatively conservative bull market performance (11.44%) but the lowest volatility (7.73%)

2.2 Defensive Analysis in Bear Markets

In bear market environments, defensiveness becomes a key consideration:

Dividend Value Index
showed the strongest defensive capability, with an annualized bear market decline of only 4.95% and a win rate of 38.3%, significantly outperforming other strategies

CSI Smart Select 300 Value Stable
ranked second in bear market performance, with a decline of 6.01% and a win rate of 40%, reflecting the rationality of its “stable” naming

Huazheng Value Preferred 50
, although excellent in bull markets, had the largest decline in bear markets (13.61%), reflecting the double-edged sword nature of high-offensive strategies

2.3 Comprehensive Evaluation of Risk-Return Characteristics

92c4751d_risk_return_analysis.png

Based on risk-return analysis, strategies can be divided into three categories:

High Offensive Type
(Huazheng Preferred 50, CSI 300): Excellent bull market returns but large bear market volatility, suitable for investors with higher risk preferences

Balanced Type
(CSI Smart Select, CSI Value 100): Relatively balanced returns and risks, suitable for long-term value investment

High Defensive Type
(Dividend Value Index): Outstanding bear market defensive capability and highest win rate stability, suitable for risk-averse investors

3. Strategy Selection and Asset Allocation Recommendations
3.1 Strategy Rotation Based on Market Cycles

Based on historical data analysis, it is recommended to adopt a

cycle rotation strategy
:

  • Bull Market Phase
    : Prioritize allocation to high-offensive strategies such as Huazheng Value Preferred 50
  • Volatile Phase
    : Allocate to balanced strategies such as CSI Smart Select 300 Value Stable
  • Bear Market Phase
    : Focus on allocation to defensive strategies such as the Dividend Value Index
3.2 Core Strategies for Long-Term Investment

For long-term investors, it is recommended to adopt a

core-satellite strategy
:

Core Allocation
(60-70%): CSI Smart Select 300 Value Stable Index, providing a stable return foundation

Satellite Allocation
(30-40%): Dynamically adjust based on market environment, increase Huazheng Preferred 50 in bull markets and Dividend Value Index in bear markets

3.3 Key Conclusions and Investment Insights
  1. Multi-Factor Combinations Are Effective
    : Through scientific multi-factor combinations, strategy-based value indices significantly improve investment win rates

  2. No Perfect Single Strategy
    : Different strategies have their own advantages in different market environments, so selection needs to be based on market conditions

  3. Clear Risk-Return Characteristics
    : Huazheng Preferred 50 is suitable for offense, Dividend Value for defense, and CSI Smart Select for balance

  4. Obvious Long-Term Allocation Value
    : From a 10-year perspective, these strategy-based value indices generally outperform market benchmarks

References

[0] Gilin AI Financial Data API - Multi-Factor Analysis and Bull-Bear Market Performance Evaluation of Strategy-Based Value Indices

[1] Stock Market Dynamic Analysis Weekly - Value Investment Strategy and Index Performance Analysis in the A-Share Market

[2] Index Investment Era Special Topic - Development Status and Prospect Analysis of Strategy-Based Index Products

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.