A Systematic Investment Framework in High-Uncertainty Markets: A Practical Paradigm Balancing Certainty and High Odds

The current global market is in a special period of

. From the 2025 market performance, the global economy shows many counter-intuitive and counter-common-sense characteristics: multiple types of assets with different logics have achieved simultaneous growth; asset rotation is intense, with quarterly themes prominent; market driving clues switch frequently, making it difficult for investors to accurately grasp the core driving factors[1]. The core characteristics of this market environment are as follows:

. Whether it is the relative performance of tech stocks in different markets, the trend of the US dollar, or changes in global asset capital flows, all can be reasonably explained through fluctuations in the credit cycle[1]. The pattern of “excess liquidity chasing assets with scarce returns” in the Chinese market has not changed, which provides a key to understanding market fluctuations.

From the perspective of sector performance, the current US stock market shows obvious differentiation: the communication services sector performed the best (+0.70%), while the consumer discretionary sector performed the weakest (-0.47%)[0]. This structural differentiation exactly confirms the complexity and variability of the market, and also provides a basic environment with both opportunities and challenges for systematic investment.

In the AI era, the core competitiveness of investment is undergoing profound changes. The shift from traditional “art” (human decision-making) to “science” (systematic decision-making) has become an irreversible trend[2]. The real goal of all big tech companies and unicorns in Silicon Valley in 2026 is no longer to create a smarter model, but to create

[2]. This means:

• AI is no longer a tool, but an executor; no longer a function, but a position
  . Enterprises are no longer buying ChatBot dialog boxes, but assembly lines of capabilities[2].
• Silicon Valley is redefining: how should companies operate?
  This is the inevitable result of the capability stack war[2].
• The shift from “AI+” to “AI-Native” entrepreneurial paradigm—not adding AI to industries, but
  using AI to completely rewrite the operating logic of industries
  [2].

Against this background, the core competitiveness of investment has shifted to

and . Organizations that can arrange models, tools, people, and processes into an automated value chain will take the lead in future competition[2].

China’s stock market is in the upward cycle of the “Transformation Bull Market”, and its underlying logic has undergone a fundamental transformation[3]:

1. More confident externally:
   China’s response to Sino-US risk challenges is more systematic and mature
2. More stable internally:
   Anti-involution constitutes a major turning point in economic governance thinking, reducing macro tail risks
3. RMB appreciation, stock market improvement, and real estate stabilization in progress:
   The contraction cycle of RMB assets is coming to an end

1. Decline in risk-free returns:
   The breaking of two types of “rigid redemption”, leading to a surge in social capital “seeking assets” and asset management demand
2. Capital market reform:
   The basic system reform starting with the “New Nine Regulations” has effectively boosted the investability of China’s market
3. Increased certainty of China’s transformation and development:
   Emergence of new technologies/new industries, expansion of capital expenditure, and China’s manufacturing industry entering a global development cycle[3]

This structural transformation requires investors to establish a more systematic and scientific investment framework to capture certain opportunities in the uncertain market.

The evolution of investment cognition usually goes through three stages:

Investors in this stage firmly believe that “selecting good companies can lead to easy wins”, over-rely on in-depth research of individual stocks, and pay insufficient attention to timing and portfolio management. The core problems of this thinking mode are and .

Begin to realize the importance of timing and asset allocation, try multiple investment strategies, but often fall into the dilemma of strategy switching, lacking a consistent investment philosophy.

Recognize that . Form a complete closed-loop system from stock selection to betting, from capital management to psychological construction. This is the cognitive height that professional investors must reach.

In an uncertain market, the core of establishing a systematic investment framework is the

:

Stock selection is not about finding “perfect” companies, but about finding

and :

• Understandability and sustainability of business models
• Stability of cash flow creation ability
• Safety margin of valuation
• Industry position and competitive advantages

, rather than simply chasing technical hotspots. The transformation of the home appliance industry from “passive response” to “active service” is a concrete manifestation of this understanding of business essence[4].

This is the key link to investment success or failure, including:

• Position management:
  Dynamically adjust positions according to odds and win rates
• Diversification strategy:
  Dumbbell-shaped allocation, balancing between certainty (high-dividend blue chips) and high odds (tech growth)
• Rebalancing mechanism:
  Regularly adjust the portfolio structure to maintain dynamic balance
• Stop-loss strategy:
  Set stop-loss points based on fundamental changes rather than price fluctuations

The core idea of the

is: when the trend is relatively clear, concentrating on one end can bring higher returns; when the trend is somewhat chaotic, implementing the dumbbell strategy and maintaining a good balance is necessary[5]. The 2025 market trend fully verified the effectiveness of this strategy: tech stocks rose at the beginning of the year, large-cap blue chips performed strongly in the second quarter, and multiple tech themes broke out in the second half of the year[5].

This is the most easily overlooked but most important part:

• Recognize your own cognitive biases:
  Overconfidence, loss aversion, anchoring effect
• Establish decision-making discipline:
  Strictly abide by system rules and not be swayed by emotions
• Maintain patience:
  Wait for the emergence of high-certainty opportunities
• Continuous learning:
  Continuously evolve in the changing market

The

emphasizes controlling the density of the net (depth of research and investment) and the posture of casting the net (trading execution). Investment is like fishing—both need the patience and ability to weave the net, and the decisiveness and precision to cast the net at the right time.

, because it requires investors to make long-term predictions about the future of enterprises, which is extremely challenging in an uncertain environment.

• Reflects a cautious attitude toward uncertainty
• Covers the cost of equity risk
• Provides sufficient safety margin

• Based on business models rather than historical data
• Consider industry cycles and competitive patterns
• Adopt scenario analysis (pessimistic/neutral/optimistic)
• Emphasize cash flow quality rather than accounting profits

• Avoid over-reliance on the perpetual growth assumption
• Adopt reasonable terminal value multiples instead of perpetual growth rates
• Consider the long-term competitiveness of enterprises and industry evolution

The essence of valuation is not to calculate the precise “intrinsic value”, but to find

and . High-odds opportunities usually appear in:

• Valuation discounts caused by excessive market pessimism
• Short-term difficulties covering long-term value
• Bottom of industry cycle
• Structural opportunities brought by policy or technological changes

In an uncertain market, risk management is the foundation of survival and development:

• Investment opportunity screening:
  Establish clear stock selection criteria and negative lists
• Position limits:
  Upper limits for single stock and single industry positions
• Diversified investment:
  Portfolio construction across industries, markets, and styles
• Stress testing:
  Simulate portfolio performance under extreme market scenarios

• Real-time risk measurement:
  Indicators such as VaR, maximum drawdown, and volatility
• Correlation monitoring:
  Avoid implicit over-concentration in the portfolio
• Liquidity management:
  Ensure good liquidity of the portfolio
• Fundamental tracking:
  Continuously monitor changes in the fundamentals of held enterprises

• Attribution analysis:
  Distinguish between alpha and beta returns
• Error summary:
  Establish an investment mistake collection
• System optimization:
  Continuously optimize the investment system according to market changes
• Psychological construction:
  Learn from failures and maintain rationality

, because it requires investors to make long-term predictions about the future of enterprises, which is extremely challenging in an uncertain environment.

• Reflects a cautious attitude toward uncertainty
• Covers the cost of equity risk
• Provides sufficient safety margin

• Based on business models rather than historical data
• Consider industry cycles and competitive patterns
• Adopt scenario analysis (pessimistic/neutral/optimistic)
• Emphasize cash flow quality rather than accounting profits

• Avoid over-reliance on the perpetual growth assumption
• Adopt reasonable terminal value multiples instead of perpetual growth rates
• Consider the long-term competitiveness of enterprises and industry evolution

The essence of valuation is not to calculate the precise “intrinsic value”, but to find

and . High-odds opportunities usually appear in:

• Valuation discounts caused by excessive market pessimism
• Short-term difficulties covering long-term value
• Bottom of industry cycle
• Structural opportunities brought by policy or technological changes

In an uncertain market, risk management is the foundation of survival and development:

• Investment opportunity screening:
  Establish clear stock selection criteria and negative lists
• Position limits:
  Upper limits for single stock and single industry positions
• Diversified investment:
  Portfolio construction across industries, markets, and styles
• Stress testing:
  Simulate portfolio performance under extreme market scenarios

• Real-time risk measurement:
  Indicators such as VaR, maximum drawdown, and volatility
• Correlation monitoring:
  Avoid implicit over-concentration in the portfolio
• Liquidity management:
  Ensure good liquidity of the portfolio
• Fundamental tracking:
  Continuously monitor changes in the fundamentals of held enterprises

• Attribution analysis:
  Distinguish between alpha and beta returns
• Error summary:
  Establish an investment mistake collection
• System optimization:
  Continuously optimize the investment system according to market changes
• Psychological construction:
  Learn from failures and maintain rationality

In the AI era, the core competitiveness of investment is undergoing fundamental changes:

• Information acquisition is no longer an advantage (popularization of search engines and AI tools)
• Core competitiveness shifts to in-depth interpretation and comprehensive judgment of information
• Understanding of business essence becomes a key differentiating factor

• AI can assist in massive data analysis and pattern recognition
• Human value lies in building a complete investment system
• Integrate AI tools into the investment system rather than replacing it

• Determination to integrate knowledge and action becomes a scarce resource
• Strictly abiding by system rules is more important than pursuing “perfect decisions”
• Psychological construction and emotional management are the keys to long-term success

The application of AI technology in investment systems is mainly reflected in the following aspects:

• Automated collection and analysis of financial reports, news, and announcements
• Mining and processing of alternative data
• Monitoring and early warning of real-time market data

• Recognition of technical indicators and chart patterns
• Mining of fundamental factors and quantitative factors
• Analysis of market sentiment and capital flows

• Screening and ranking of investment opportunities
• Risk assessment and stress testing
• Portfolio optimization and rebalancing recommendations

The final investment decision still needs to be made by humans, because:

• AI cannot understand the subtle differences in business models
• AI is difficult to deal with “never happened” extreme situations
• AI lacks in-depth understanding of human psychology

In the AI era, investors need to reconstruct their own capability framework:

• In-depth understanding of business essence (industry, company, product)
• Financial analysis and valuation capabilities
• AI tool usage and system construction capabilities
• Data analysis and quantitative thinking

• Independent thinking and critical thinking
• Emotional management and psychological resilience
• Rapid learning and adaptability
• Communication and collaboration capabilities

• Ability to integrate AI tools into investment systems
• Balance between quantitative analysis and qualitative judgment
• Ability to make decisions in uncertain environments
• Execution ability to integrate knowledge and action

According to the article background, the 2025 portfolio achieved excellent performance with

and . This achievement is due to:

• Correct implementation of the 10/40/50 rule
• Defensiveness of the dumbbell strategy in market fluctuations
• Strict risk management and position control
• Disciplinary execution at the psychological level

• Seized the opportunity of tech stocks at the beginning of the year
• Allocation of large-cap blue chips in the second quarter
• Participation in multiple tech themes in the second half of the year
• Balance adjustment of the dumbbell strategy at the end of the year

• Maximum drawdown controlled at -13.3%, far lower than the market average
• Sharpe Ratio >1.0, indicating excellent risk-adjusted returns
• Maintained relatively stable net worth in the market with剧烈轮动

Based on the current market environment analysis, 2026 investment needs to pay attention to the following directions:

• Switch from “dumbbell strategy” to “quality growth”[3]
• Emerging tech as the main line, cyclical consumption depends on transformation
• Large finance is worth optimistic about due to performance improvement and low valuation

1. Credit expansion direction:
   Allocate according to the direction of credit expansion[1]
2. Profit improvement of listed companies:
   The profit growth of all A-shares excluding finance is expected to be above 10.6%, which is the first double-digit growth in nearly 3 years[3]
3. “Deposit搬家” trend:
   A big year from fixed income to “fixed income+”[3]

1. Emerging tech:
   New technology trends such as DeepSeek, robots, and integrated circuits[3]
2. Global expansion of manufacturing:
   Power equipment, engineering machinery, automobiles and parts, etc.[3]
3. Consumption recovery:
   With the advancement of policies such as domestic demand-led and consumption promotion[3]

• Geopolitical risks
• Unexpected changes in macro policies
• Short-term market liquidity risks
• Industrial policy change risks[1]

Establishing a systematic investment framework that balances certainty and high odds in a high-uncertainty market is essentially

.

The core elements of this framework include:

1. Cognitive Upgrade:
   From “stock fundamentalists” to “system guardians”
2. Scientific Decision-Making:
   Paradigm shift from “art” to “science”
3. Risk Awareness:
   Always put risk control first
4. System Thinking:
   Complete closed loop of 10% stock selection, 40% betting strategy and capital management, and 50% psychological construction
5. Continuous Evolution:
   Continuous learning and adaptation in the changing market

In the AI era, investors who can perfectly combine the understanding of business essence, system construction capabilities, and the determination to integrate knowledge and action will stand out in long-term competition.

As the article background says, free cash flow discounting is the most difficult formula in investment, but it is more difficult to insist on executing this formula in the face of market fluctuations. The essence of investment is not to predict the future, but to build a robust system in an uncertain world, and obtain excellent risk-adjusted returns in the long run through continuous learning and evolution.

The 2025 practice has proved the effectiveness of this systematic framework, and the 2026 market changes will be a further test and optimization of this framework. In the upward cycle of the “Transformation Bull Market”[3], adhering to systematic investment, maintaining patience and discipline will be the key to crossing uncertainty and achieving long-term compound growth.

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[0] Jinling API Data - Sector Performance Data (December 29, 2025)

[1] Sohu News - “Seeking Certainty from These Keywords: Tech, Long-Termism, Diversified Allocation | 2025 Snowball Carnival”
https://m.sohu.com/a/969383142_465270

[2] Everyone is a Product Manager - “2026 Enterprise AI Commercialization Value Inflection Point and Survival Prediction”
https://www.woshipm.com/ai/6313329.html

[3] Daily Economic News - “Exclusive Interview with Guotai Haitong Chief Strategy Analyst Fang Yi: A-Shares’ “Transformation Bull Market” is Far from Over, and It is Expected to Challenge the High of Ten Years Ago in 2026”
https://www.nbd.com.cn/articles/2025-12-25/4195890.html

[4] Sina Finance - “Insight 2025: AI-Driven New Home Appliance Era”
https://finance.sina.com.cn/stock/relnews/hk/2025-12-16/doc-inhaywrm8098306.shtml

[5] Securities Times - “Using Dumbbell Strategy to Cope with Year-End Market”
https://www.stcn.com/article/detail/3527872.html