The Way to Balance Individual Stock Alpha and Systematic Risk Control for Fund Managers

and are essentially a game between :

Dimension	Individual Stock Alpha Capability	Systematic Risk Control System
Focus	In-depth research on single target	Overall risk of investment portfolio
Mindset	Profit maximization oriented	Risk-adjusted return oriented
Decision Basis	Business essence, competitive advantage	Correlation, volatility, drawdown control
Execution Characteristics	High concentration, strong confidence	Diversified, rule-based, strong discipline

From the framework of ‘10% stock selection +40% betting strategy +50% psychology’ you mentioned, this fund manager has deeply realized: **Pure individual stock selection capability can only solve the problem of “what to buy”, while systematic risk control solves the problems of “how much to buy, when to buy, when to sell, and how to combine”.

---

Core characteristics of early “individual stock fundamentalists”:

• Overconfidence
  : Forming belief-level conviction in deeply researched targets
• Ignoring tail risks
  : Such as the Sunac case, the fatal weakness of high-leverage business models when policies shift
• Lack of position management
  : A good company ≠ a good price, even less ≠ a good position
• Psychological fragility
  : Lack of response mechanisms when reality deviates from cognition

: Individual stock research without a risk control framework is like a racing car without brakes— the faster the speed, the greater the risk.

The ‘barbell strategy’ proposed by this fund manager reflects profound balance wisdom:

Barbell Strategy Structure:
┌─────────────────┐    ┌─────────────────┐
│ High Certainty Core │    │ High Odds Satellite │
│ (70-80% position) │    │ (20-30% position) │
│                │    │                │
│ • Industry leader     │    │ • Distressed reversal     │
│ • Stable cash flow   │    │ • Industry consolidation     │
│ • Diversified allocation     │    │ • Concentrated betting     │
└─────────────────┘    └─────────────────┘

:

• Certainty end
  : Obtain “steady Beta+” through diversification and in-depth research
• Odds end
  : Obtain “asymmetric returns” through concentrated betting
• Balance between the two ends
  : The overall portfolio retains aggressiveness while controlling drawdowns

---

Alpha Source Pyramid (Top-Down):
          ┌──────────┐
          │ Timing Alpha │  (10% weight, hard to come by)
          ├──────────┤
          │ Allocation Alpha │  (20% weight, industry rotation)
          ├──────────┤
          │ Stock Selection Alpha │  (40% weight, core capability)
          ├──────────┤
          │ Risk Control Alpha │  (30% weight, often ignored)
          └──────────┘

: True Alpha is not just about selecting bull stocks, but also:

• Avoid major mistakes
  (Avoid Sunac-style wipeout)
• Dare to take heavy positions
  (Bet heavily when opportunities come)
• Hold on
  (Not washed out during volatility)
• Know when to stop
  (Leave decisively when valuation bubbles form)

The core of the “40% betting strategy” is the practical application of the Kelly Criterion:

Optimal position = (Win rate × Odds) / (Odds - 1)

Example:
• Core high certainty target: Win rate 70%, odds1.5:1 → standard position 20%
• Satellite high odds target: Win rate40%, odds5:1 → standard position10%
• Portfolio construction: Achieve "overall asymmetric exposure" through correlation control

:

• Single target upper limit
  : No matter how optimistic, single stock does not exceed10-15%
• Industry concentration
  : Single industry does not exceed30-40%
• Correlation monitoring
  : Avoid “false diversification” (e.g., banks + real estate + insurance)

“50% psychology” is the hardest part to quantify, but also the most important:

Psychological Trap	Corresponding Mechanism
Confirmation Bias	Mandatory counterfactual analysis: “Under what circumstances would I be wrong?”
Loss Aversion	Define stop-loss rules in advance, let the system execute
Anchoring Effect	Re-evaluate regularly, forget the purchase cost
Herd Effect	Record independent investment logic, review regularly

---

In the AI era, the following capabilities are even more scarce:

• Insight into business essence
  : AI is good at data analysis but hard to understand “why”
• Processing of unstructured information
  : Policy signals, management character, industrial cycle inflection points
• Decision-making under extreme pressure
  : AI is trained on history, but the market always has new situations

AI-Enhanced Investment Process:
┌──────────────────────────────────────────┐
│ Traditional Research (Human) │ AI Assistance (Machine) │
├─────────────────────────────────────────┤
│ Business model insight      │ Financial data mining       │
│ Competition pattern judgment      │ Industry chain upstream and downstream analysis   │
│ Management evaluation        │ Text sentiment analysis       │
│ Valuation logic construction      │ Historical similar scenario matching   │
├─────────────────────────────────────────┤
│ Risk monitoring         │ Real-time early warning system       │
│ Position decision         │ Correlation/volatility monitoring  │
│ Trading execution         │ Optimal trading timing selection   │
└─────────────────────────────────────────┘

---

Regularly analyze performance sources to ensure that the circle of competence matches the source of returns:

Performance Attribution Framework:
• Timing contribution: Beta exposure in market ups and downs
• Stock selection contribution: Excess returns relative to the industry  
• Trading contribution: Grasp of buying and selling timing
• Risk contribution: Compounding effect brought by drawdown control

Establish a closed loop of “investment-review-optimization”:

• Monthly
  : Portfolio attribution, verify logic
• Quarterly
  : Strategy stress test, extreme scenario deduction
• Annual
  : System architecture review, circle of competence boundary adjustment

• Transparency
  : Clearly explain strategy logic and risk characteristics
• Education
  : Explain the value of “Sharpe ratio >1.0” (many private funds have Sharpe <0.5)
• Cycle matching
  : Find LPs whose fund term matches the strategy cycle

From “individual hero” to “systematic combat”:

• Knowledge management
  : Explicitize and standardize implicit cognition
• Decision-making process
  : Independent operation of investment committee and risk control committee
• Talent echelon
  : Growth path from researcher to fund manager to partner

---

Action Item	Specific Practice	Expected Effect
Establish risk control checklist	List “10 types of stocks not to touch”	Avoid major losses
Mandatory position record	Record the decision logic for each purchase	Post-review to improve decision quality
Regular stress test	Assume portfolio performance under extreme conditions	Enhance anti-fragility
Independent risk control line	Set stop-loss independent of investment decisions	Separate knowledge and action

1. Cognitive upgrade
   : Continuously learn psychology, behavioral finance, system theory
2. Historical perspective
   : Study a century of investment history to understand the inevitability of cycles
3. Philosophical thinking
   : Think about whether the essence of investment is prediction or response
4. Physical and mental balance
   : Investment is a long-distance race; maintaining physical and mental health is the foundation of risk control

---

**The balance between individual stock Alpha capability and systematic risk control is essentially the balance between “offense” and “defense”:

• Risk control without Alpha
  : Is “mediocre stability”, which underperforms inflation in the long run
• Alpha without risk control
  : Is a “time bomb”, which wipes out the entire army with one zeroing
• True balance
  : Maximize asymmetric returns under controllable risks

The 2025 performance of this fund manager (Sharpe ratio>1.0, maximum drawdown-13.3%) has proven that:

.

---

Jinling AI Prompt

: If you need deeper analysis, I can enable the

Deep Investment Research Mode

to analyze the historical performance, position characteristics, risk control indicators of specific funds, or backtest and quantitatively evaluate certain investment strategies. You can also ask questions about specific fund managers, investment styles or asset allocation.