Rebalancing - AI Analysis Prompt

Use this Benjamin Graham rule prompt to apply “Rebalancing” to a specific company. It turns a vague opinion into a repeatable checklist: what facts you must verify, which assumptions matter most, what would invalidate the thesis, and the common misreads that create false certainty. Expect a written output you can save: a thesis summary, key risks, and next-step questions for filings and earnings calls. If a claim matters, require primary-source citations before you act. Educational only — not investment advice.

Full Prompt

You are an investment analyst trained in Benjamin Graham's principle of "Rebalancing." Your core philosophy: margin of safety, Mr. Market, defensive investing. Your task is to analyze {Company Name} through the specific lens of this principle.

## Context
Benjamin Graham teaches: "The investor should periodically rebalance his portfolio to maintain the desired asset allocation."

## Analysis Framework

### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Rebalancing"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Benjamin Graham focus on first when evaluating this company?

### 2. Quantitative Evidence
- Identify 3-5 key financial metrics most relevant to this principle
- Analyze these metrics over the past 5-10 years for {Company Name}
- Compare with industry peers and historical benchmarks
- Are the numbers improving, stable, or deteriorating?
- What story do the numbers tell through the lens of "Rebalancing"?

### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Benjamin Graham would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Benjamin Graham want to know that isn't in the financial statements?

### 4. Risk Assessment Through This Lens
- What risks does this principle specifically highlight for {Company Name}?
- What could go wrong that this principle is designed to protect against?
- Are there warning signs that Benjamin Graham would flag?
- Stress-test: How would this company perform under adverse conditions?
- What is the worst-case scenario from this principle's perspective?

### 5. Opportunity Identification
- What opportunities does analyzing through this lens reveal?
- Are there hidden strengths the market may be undervaluing?
- How does this company compare to Benjamin Graham's ideal investment?
- What catalysts could unlock value related to this principle?

### 6. Graham Verdict
- Summarize: Does {Company Name} pass the "Rebalancing" test?
- Rate the investment opportunity: 1-10 from this principle's perspective
- Clear recommendation: Buy / Hold / Avoid (based on this principle alone)
- What conditions would change your assessment?
- One-paragraph summary capturing Benjamin Graham's likely assessment

## Output Format
Present your analysis with specific data points in each section. Use Benjamin Graham's analytical style: quantitative value analysis with strict margin of safety requirements. End with a decisive verdict.

Related reading (close the loop)

Pick one path below to turn the output into a checkable, repeatable decision policy.

Educational only. Verify facts with primary sources and apply your own constraints.

Basic Questions

What is rebalancing and how does it force buy-low sell-high?
Rebalancing is periodically adjusting your portfolio back to target allocations:

📊 Example: You set 60% stocks, 40% bonds
📈 Stocks rise, ratio becomes 70%/30%
🔄 Rebalance: Sell some stocks, buy bonds, restore 60/40

Why Graham valued rebalancing:
1. Forces 'buy low, sell high' — sell what's risen too much
2. Controls risk exposure — prevents portfolio from becoming too aggressive
3. Reduces emotional interference — rule-driven, not emotion-driven

Usage Tips

Is the AI's 1-10 rating reliable?
⚠️ AI's "rebalancing score" reflects how urgently your portfolio has drifted from target allocation, not market prediction.

How to interpret:
- **8-10 (healthy allocation)**: Current allocation deviates less than 5% from target — no immediate action needed
- **5-7 (attention needed)**: 5-15% deviation — consider rebalancing at next regular review
- **1-4 (act now)**: Over 15% deviation — risk exposure significantly misaligned with your tolerance, rebalance soon

Graham recommended actively adjusting when the stock/bond ratio swings between 25/75 and 75/25. AI quantifies the drift so you don't make allocation decisions by feel.

Getting started

Does this prompt give investment advice or buy/sell calls?
No. It is a research helper that turns your thinking into checkable inputs and constraints: what evidence you must verify, what would prove the thesis wrong, and what common misreads to avoid. Treat the output as a draft, not a signal. Validate every material number against primary sources (filings, earnings releases, investor presentations, transcripts), and do not act unless you can write down (1) position-size limits and (2) explicit invalidation triggers.
What inputs should I provide for a reliable result?
At minimum: a 1-sentence business model summary, your current thesis (why it wins/loses), time horizon, and risk constraints; a valuation/price range; and the latest financial statements (profit quality, cash flow, debt/liquidity). Add context that reduces hallucinations: the exact filing period, known one-offs, key competitors, and what you do NOT know yet. If an input is missing, label it as missing evidence instead of letting the model guess.

Validation and boundaries

How do I validate the output?
Validate falsifiable claims one by one. Rewrite each key statement into something you can check: the metric, the period, and the source. Numbers must match filings; management claims must be traceable to transcripts/guidance; and “moat” claims need observable evidence (pricing power, retention, switching costs, cost structure). Anything you cannot verify becomes a follow-up task, not a decision trigger. If the model cites dates, confirm they are not beyond its knowledge cutoff.
When should I NOT act on the output?
If you cannot write down invalidation triggers, a position-size cap, or primary-source evidence for the key claims behind “Rebalancing”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

More Rule Prompts

Explore other investment principles from this master.