ACTIVATE for ANY finance, investment, trading, or market query. Comprehensive value investing framework combining Buffett, Munger, Duan Yongping, and Li Lu methodologies. Use when making investment decisions.
ACTIVATE for ANY finance, investment, trading, or market query. Comprehensive value investing framework combining Buffett, Munger, Duan Yongping, and Li Lu methodologies. Use when making investment decisions.
Systematic value investing compounds at 15-25% annually. A $50K portfolio following this framework generates $7.5K-12.5K/year. With position sizing and margin of safety, drawdowns stay under 20%. One good investment thesis can return 2-10x over 3-5 years.
Revenue Streams
Personal Portfolio — compound your own capital
Investment Research ($2K-10K/report) — sell theses to funds/family offices
Portfolio Management (0.5-1.5% AUM) — manage for others
#!/usr/bin/env bash
# Portfolio health check
mkdir -p ~/wolf-finance/{holdings,research,theses,reviews}
echo "=== Portfolio Health Check ==="
echo "1. List ALL current holdings with cost basis"
echo "2. Run 7-factor Quality Screen (eliminate weak positions):"
echo " - Declining revenue (3yr) -> RED FLAG"
echo " - Increasing debt/equity -> RED FLAG"
echo " - Negative free cash flow -> RED FLAG"
echo " - Insider selling >50% -> RED FLAG"
echo " - Losing market share -> RED FLAG"
echo " - Regulatory risk -> RED FLAG"
echo " - Overvalued (P/E > 3x industry) -> RED FLAG"
echo "3. Flag any position with 3+ red flags for review"
echo "4. Check thesis: has anything fundamentally changed?"
echo "5. Decision: HOLD, INCREASE, or EXIT each position"
Anti-Rationalization Table
Excuse
Truth
"I need more information before deciding"
You have enough to decide. More info = more noise.
"The market is too volatile right now"
Volatility is when value investors buy
"I should wait for a better entry"
DCA in. Time in market > timing the market
Output Format
On completion: "Portfolio: [N] positions, $[N] value, [N] red flags, [N] thesis updates needed, [N] actions taken"
Wolf Finance
When to Use
Trigger phrases:
"wolf finance"
"Use when working with wolf finance"
Analyzing any financial asset (equities, crypto, forex, commodities, derivatives)
Building investment theses with evidence-tiered backing (T1/T2/T3)
Running pre-trade risk gates before position entry
Portfolio construction and risk management across asset classes
Institutional-grade reporting for investment committees
Deep company research and valuation
Management quality assessment and due diligence
Quality screening of investment candidates
When NOT to Use
For personal financial advice (consult a licensed advisor)
When the analysis requires real-time market data you do not have
For tax or legal decisions (consult professionals)
Overview
Wolf Finance provides finance operations with accuracy and compliance. Integrates comprehensive investment research frameworks drawn from Buffett, Munger, Duan Yongping, and Li Lu — from quality screening through deep company research to final decision memorandum.
Current valuation: market cap, PE, PS, PEG, EV/Revenue
Bull and bear case core arguments
Cross-validate every key data point using the Financial Data Standards section above and the financial_rigor.py tool suite. Never rely on LLM mental arithmetic for calculations.
Common error prevention:
Market cap unit: HKD bn vs RMB bn vs USD bn — easy to misplace a zero
If wrong, what is maximum downside at current price?
Would you add if the stock halved?
Gate 6: Position Sizing & Decision Discipline
Is FOMO driving the decision?
Are you buying only because someone recommended it?
Could you accept a 5-year trading halt?
Can the buy thesis be written in under 200 words?
Final: Mirror Test
Write:
"I am buying ___ at ___ because:
The business essence is ___, I understand it;
Its moat is ___ and it is widening/narrowing;
Management is ___ worthy/unworthy of trust;
Current price represents ___ of intrinsic value, ___ sufficient/insufficient margin of safety;
Even if I am wrong, downside is controllable/uncontrollable because ___."
Cannot complete in 5 sentences = do not buy.
Quick Veto List
Cannot clearly explain how the company makes money
3 consecutive years of negative FCF with no sign of improvement
Management integrity issues
Competitive advantage being irreversibly eroded
Thesis requires "a greater fool" to pay more later
Cannot afford the investment going to zero
Main reason to buy is "everyone else is buying" or "it has been going up"
Cannot write the buy thesis in under 200 words
Quality Screen: 7-Factor Elimination Criteria
Quickly filter out non-first-class companies using 7 hard criteria with 3 exemption rules.
The 7 Criteria
#
Metric
Elimination Condition
What It Measures
1
10yr avg ROE
< 8%
Capital efficiency — can equity beat opportunity cost?
2
5yr cumulative FCF
Negative
Real cash generation vs paper profits
3
Interest coverage (EBIT/interest)
< 2x
Debt repayment safety
4
Long-term gross margin
< 15%
Pricing power — product differentiation
5
Operating CF / Net income (5yr avg)
< 0.7
Profit quality — can profit be collected as cash?
6
Long-term net margin
< 5%
Resilience — does revenue volatility zero out profit?
7
5yr share dilution
> 20% (non-M&A)
Shareholder interest — is management diluting you?
Exemption Rules
A: Strategic Investment Period (exempts Rule 1)
Listed < 10 years
Gross margin > 30% (proves business model has pricing power)
Last 2 years operating CF positive (proves self-sustaining)
B: Active Low-Margin Strategy (exempts Rule 6)
Gross margin > 30% (can earn but chooses not to)
Last 2 years net margin back above 5% or in clear uptrend
C: High-Turnover Thin-Margin Model (exempts Rules 4 and 6)
ROE > 20%
Operating CF / Net income > 1.0
Business model is "membership / platform commission / high-turnover thin-margin"
Notes
Banks/insurance: Rule 3 (interest coverage) does not apply
REITs: use core operating profit ROE instead
Cyclicals: use full-cycle averages (cover at least one peak and one trough)
Short listing history (< 5yr): use all available data, flag "insufficient data window"
Data deficiency: mark as "data insufficient" rather than passing/failing
Passing screen does not equal "good investment" — it means the company survived first-pass elimination. Further research on business model sustainability, management, valuation, and competitive dynamics is still required.
Management Deep Dive
Deep management quality assessment when standard management scoring is uncertain (*** or below) or management is the core investment thesis.
Framework
1. Key Person Identification
Identify CEO, CFO, founder (if not CEO), controlling shareholder, other key executives. Distinguish "who makes decisions" from "who has the title."
2. CEO Capability Assessment
Strategic vision: Review CEO public statements (letters to shareholders, earnings calls, interviews, social media) over the past 5 years. Extract predictions and compare with actual outcomes.
Time
CEO's Judgment/Prediction
Actual Outcome
Accuracy
Has the CEO made correct judgments ahead of the market?
Has the CEO stayed calm when everyone was overly optimistic?
Independent thinking vs following consensus?
Execution ability:
Dimension
Assessment
Evidence
Strategy to execution
Did they deliver what they said?
Organization
Can they attract and retain talent?
Crisis handling
How did they respond to difficulties?
Iteration speed
How fast do they correct mistakes?
3. Integrity Assessment (Most Important)
Promise vs delivery tracking — extract specific commitments from past 3 years:
#
Time
Commitment
Venue
Delivered?
Score
Track record:
Fulfillment Rate
Rating
> 80%
Excellent — say what they do
60-80%
Acceptable — right direction, execution gap
40-60%
Concerning — over-promise, under-deliver
< 40%
Severe issue — cannot be trusted
Crisis behavior: Search for the company's major crises. How did management react?
Proactive communication or avoidance?
Internal attribution or external blame?
Do the hard but right thing or pander to short-term markets?
Stakeholder attitudes:
Stakeholder
Attitude
Evidence
Shareholders
Respect / ignore / exploit
Employees
Good treatment / exploitation / indifference
Customers
Customer-centric / short-term extraction
Regulators
Compliance / gray-area play
4. Capital Allocation Ability
M&A record:
Time
Target
Amount
Strategic Logic
Result
Score(1-5)
Buyback record: Check valuation at time of buyback vs current.
Dividend record: Payout ratio vs FCF, sustainability.
New business investment: Area, cumulative spend, current status, return.
Scoring:
Dimension
Score(1-5)
Notes
M&A discipline
Right price? Integration success?
Buyback timing
Buying low, stopping high?
Dividend rationality
Payout matches FCF?
New business investment
Success rate, stop-loss discipline
Cash management
Reasonable reserves vs hoarding?
5. Governance Structure
Dual-class share structure / super-voting rights
Founder/controller ownership percentage
Independent director independence
Executive compensation vs net profit and peers
Related-party transactions fairness
6. CEO Exit Scenario
Question
Answer
Can the company run normally if CEO leaves tomorrow?
Management team depth — clear successor?
Competitive advantage dependent on CEO or organization/systems?
Historical CEO transitions — smooth?
7. Comprehensive Scoring
Dimension
Weight
Score(1-5)
Weighted
Integrity
35%
Strategy & Execution
25%
Capital allocation
25%
Governance
15%
Composite
100%
Key Principles
Integrity is a veto — incompetence can be learned, character cannot be fixed
Watch actions, not words — what management does, not what they say
Crisis reveals truth — anyone is a good CEO in good times; tough times reveal real skill
Capital allocation is the final exam — making money is easy, deploying it well is hard
Never fall in love with management — stay objective, even admirable people make big mistakes
Investment Portfolio Management
Portfolio-level investment thesis tracking, drift analysis, and structured portfolio review. These systems are modeled after the disciplined buy-and-hold processes used by Buffett, Li Lu, and Duan Yongping — methods that transform portfolio management from reactive guessing into systematic oversight.
When to Use
Managing multi-position investment portfolio with thesis-backed rationale
Detecting thesis drift — separating fact changes from price changes and wording changes
Running structured portfolio review and rebalancing
Stress-testing portfolio against concentration, correlation, and macro scenarios
When NOT to Use
Intraday trading or short-term momentum decisions
When you lack structured thesis documentation (baseline required for drift detection)
For personal financial planning unrelated to portfolio positions
Investment Thesis Tracker
The thesis tracker is a buy-and-hold discipline system that enforces documented reasoning before entry and systematic re-validation through quarterly check-ins.
Design principle: Most investors stop at research -> buy -> pray. Missing post-entry tracking causes reluctance to sell, panic-selling on drawdowns, and forgetting why you bought. The system answers one question at every check: Would you still buy this today if you did not own it?
Two modes:
Mode A — Build Thesis:
Collect current price, valuation (PE/PB/dividend yield), latest financial data via WebSearch
Validate valuation using tools/financial_rigor.py verify-valuation
Core thesis — answers these 5 questions in <=200 characters:
What is the business and how does it make money?
What is the moat and is it widening or stable?
Why is management trustworthy?
What discount to intrinsic value offers the margin of safety?
Why is downside risk controllable if wrong?
Decompose into 3-7 testable assumptions, each with verification method and frequency
Every non-Unchanged conclusion must cite specific new evidence (earnings line items, regulatory filings, news events, price vs fundamentals distinction)
If no evidence explains the change, judge Unchanged or Cannot Determine
Mode B — Auto snapshot comparison:
Find old and new thesis snapshots in reports/{company}-thesis*.md; verify same company, different dates; execute Mode A.
Mode C — Missing baseline handling:
State explicitly that drift detection cannot run without a historical baseline. Guide user to first build a thesis via the Thesis Tracker. Do not fabricate an old thesis from memory or market impression.
Key principles for drift detection:
Evidence over wording — paraphrasing is not drift; only fact changes count
Fundamentals over price — price changes only affect the valuation anchor, not business quality
Red-lines have priority over cheap valuation — a triggered red-line is not neutralized by a low PE
Every conclusion must trace to specific evidence
Portfolio Review
A structured 7-step portfolio review process that treats portfolio management as a separate discipline from stock-picking.
Design principle: Researching companies is only half of investing. The other half is portfolio-level decisions: position sizing, funding source (new money vs swap), correlation with existing holdings, opportunity cost — every dollar should go where it earns the most.
Seven steps:
Step 1: Parse positions — Normalize input holdings into standard table (ticker, quantity, cost basis, current price, market value, weight, P&L). Support both proportional and unit formats. Load saved portfolio if available (reports/portfolio-latest.md).
Step 2: Get current data — Use parallel sub-agents via WebSearch for each position: current price and valuation (PE, PB, dividend yield), latest quarter financial changes, major recent events, analyst consensus. Validate with tools/financial_rigor.py verify-valuation.
Step 3: Single-position health check — For each position answer three questions:
Would you still buy at the current price if you did not own it?
Could you hold for 5 years without trading?
Is the buy thesis still intact?
Step 4: Portfolio-level analysis:
Concentration: largest position (<40%), top 3 (50-80%), total holdings (5-15), cash (10-30%)
Correlation: identify hidden risk resonance — same industry, same country/currency, same macro exposure, supply chain adjacency
Opportunity cost: rank all positions by expected annual return x certainty. The lowest-ranked should beat cash (risk-free rate ~4%). If not, sell and hold cash
Stress test: global recession, US-China escalation, interest rate spike, tech bubble burst — directional + rough magnitude per position
Step 5: Optimization suggestions:
Specific rebalance actions (add/reduce/clear/hold/new) with current vs suggested weight and rationale
Cash management recommendation
Step 6: Output report with executive summary covering: portfolio health rating (Outstanding / Good / Needs Attention / Severe), single most important action to take, biggest current risk
Step 7: Save portfolio file to reports/portfolio-latest.md with holdings table, review date, rebalance log, next review reminder
Key principles for portfolio review:
Every dollar has an opportunity cost — holding a mediocre stock costs you the chance to own a great one
Concentration is not risk; ignorance is — holding 3 deeply understood positions is safer than 30 you barely know
Cash is a position — when no good opportunities exist, holding cash is not shameful
Portfolio-level > individual stock level — a good stock in the wrong position size still hurts you
Review quarterly, do not trade daily
Process
Prepare — Gather requirements, verify prerequisites, set up environment
Execute — Run wolf finance workflow with configured parameters
