What is ProfitVision LAB's core investment methodology?

ProfitVision LAB uses 'The Discipline of Options' as its core framework, combined with the CANSLIM/SEPA stock-selection method, focusing on growth stocks with a moat, and building stable cash flow under controlled risk through options-selling strategies like Bull Put Spreads, PMCC, and Covered Calls. The core philosophy: Think with me, not just trade with me.

How do I get started learning options-selling strategies?

A recommended learning path: (1) Read the 'Start Here' series to understand the basic concepts of selling options; (2) Learn the Four-Layer Defensive Screen stock-selection method; (3) Start with Bull Put Spreads (the clearest, most controllable risk); (4) Once proficient, move on to PMCC and Covered Calls. ProfitVision LAB provides systematic SOP materials, replacing pure theory with real case studies.

Which type of investor benefits most from ProfitVision LAB's content?

ProfitVision LAB is best suited for: (1) investors with basic investing knowledge who want to go further into options strategies; (2) investors who want to replace gut-feel trading with a systematic method; (3) people who want their portfolio to generate monthly cash flow under controlled risk. The core philosophy is using a transparent methodology to help readers think independently, not providing signals to copy.

The AI Deep Stock Research SOP: Four Stages + a Hybrid Entry Structure + Real...

ProfitVision LAB | Practical AI Investing

📌 The Core of This Article

The biggest time-sink in researching a company isn't thinking — it's gathering and organizing data, which is exactly what AI is best at
ProfitVision's stock-research process has four stages: macro positioning → moat analysis → financial checkup → options entry structure, each with its own AI-acceleration method
The right role for AI is research assistant, not decision-maker — it helps you draw the map, you decide which road to take
This article includes real prompt templates for each stage that you can copy directly and use with Claude or ChatGPT
The single most important point: never rely on AI alone to generate financial figures — always cross-check against the original filings or SEC data, since AI is prone to hallucinating numbers

Why the Research Process Matters More Than the Research Tool

A lot of people ask me which AI tool I use for investment research. The question itself is aimed in the wrong direction.

Tools are the means; process is the skeleton. Hand the same question to Claude, and someone with a process gets structured research output, while someone without one just gets a pile of pretty but unactionable text. A tool's value depends on whether you're asking the right question at the right time.

ProfitVision's stock-research SOP doesn't start from "which stock has a hot narrative" — it starts from "where does this company sit on the industry map." That difference in sequencing determines whether your research is chasing heat or building a genuine foundation for judgment.

AI's biggest value isn't picking stocks for you — it's helping you see a company's outline more clearly in less time, so your judgment rests on more complete information.

The full SOP has four stages, each with a clear input, output, and way AI assists:

Stage
One

Macro Positioning: What Battlefield Is This Company On?

Industry map → competitive landscape → the company's role within it

▼

Stage
Two

Moat Analysis: How Long Can Its Edge Last?

Sources of competitive barriers → customer stickiness → pricing power → replicability

▼

Stage
Three

Financial Checkup: Clearing the Four-Layer Defensive Screen One by One

Chip flow → moat metrics → volatility → technicals

▼

Stage
Four

Entry Structure: Direct and Indirect Combined — a Hybrid Deployment of Shares and Options

Pure direct force / a direct-indirect blend / pure indirect force → strike design → confirming max loss → a pre-entry checklist

Stage One: Macro Positioning — Look at the Map Before Looking at the Stock

The most common mistake at this stage is asking directly, "how's stock XXX doing?" That question is too narrow, and the answer you get is usually just surface description, unable to build a real framework for judgment.

The correct starting point is: first understand the industry map the company sits within, then ask about its position on that map.

PROMPT 1-A

Industry Map Positioning (Claude / ChatGPT)

You are a senior industry analyst. Help me analyze the industry [Company Name/Ticker] operates in, using a three-layer framework:

1. [Industry Definition] What is the core value proposition of this industry? What problem does it solve?

2. [Competitive Landscape] List the industry's major players (at least 5), and explain how their market positioning differs

3. [Industry Drivers] What are the 2–3 core catalysts currently driving this industry's growth? What is the biggest structural risk over the next 3 years?

4. [[Company]'s Position] Where does it sit in this competitive landscape? Challenger, leader, or niche player?

Please output this in bullet points, avoid excessive praise, and keep an analyst's neutral tone.

💡 Once you have the output, the point isn't to memorize every detail — it's to confirm: is this company competing in an expanding market, or fighting for share in a shrinking one?

PROMPT 1-B

Recent Major-Event Scan (paired with web search)

Help me summarize [Company]'s major events over the past 90 days, sorted into these categories:

· Earnings events: the most recent quarter's revenue/EPS vs. market expectations

· Management developments: any executive changes, major statements, or key points from the earnings call

· Products/contracts: any major product launches, partnership agreements, or customer changes

· Regulatory: any regulatory changes affecting the business

· Competitive dynamics: the latest moves from major competitors

For each category, explain in 1–2 sentences, note the event date, and tag it as "positive," "negative," or "neutral/watch" for the company.

💡 This prompt requires AI's web-search capability (Claude's web search, ChatGPT's Browse). Relying purely on AI's training data introduces a time lag — this step must have live search enabled.

Stage One's output should let you summarize in a single paragraph: "what this company does, what market it competes in, and what important things are happening right now." If you can't summarize it clearly, keep asking — don't move on to Stage Two.

Stage Two: Moat Analysis — Can the Edge Survive Three Years?

Moat analysis is the part of the whole research process that demands the most critical thinking. AI's answers tend to skew optimistic — it's inclined to list strengths rather than proactively challenge weaknesses. So at this stage, you need to explicitly instruct the AI in the prompt to argue the other side.

[Core of ProfitVision Screen Two] ROE ≥ 17%, EPS growth > 25%, SMR Rating A/B+

PROMPT 2-A

In-Depth Moat Analysis

Use the "Five-Factor Moat Framework" to analyze [Company]'s competitive advantage:

1. [Network Effects] Does its product/service become more valuable as more users join? How strong or weak is this?

2. [Switching Costs] How costly is it for a customer to leave? What specific frictions exist in switching?

3. [Economies of Scale] Does its cost structure improve as scale grows?

4. [Intangible Assets] Patents, brand, regulatory licenses, exclusive data — which of these does it hold?

5. [Cost Advantage] Does it have a structural cost advantage that's hard for competitors to replicate?

For each factor, give a rating (strong / medium / weak / none) and explain your reasoning.

Then, play the role of an analyst who is bearish on this company, and point out where the moat is weakest and what is most likely to erode it.

💡 The instruction "play the role of a bearish analyst" is critical. Without it, AI's moat analysis is almost always positive; with it, you finally get a genuinely useful risk perspective.

✅ A Good Output Example (Using Cloudflare / NET)

Switching costs: strong — once an enterprise runs zero-trust security, CDN, and DNS entirely on Cloudflare's network, migrating requires reconfiguring the entire IT architecture, a process that takes roughly 3–6 months and carries business-interruption risk. Customer stickiness is high.

The bearish view: AWS, Azure, and Google Cloud are all strengthening their own network-security product lines, and have deeper enterprise relationships and greater sales force. While Cloudflare's small-and-mid-size customer base is broad, replacement risk in the large-enterprise market is rising, especially as customers want to fold security products into their existing cloud ecosystem.

The purpose of moat analysis isn't to convince yourself "this company is great" — it's to answer one question: can its competitive advantage keep converting into financial performance over the next three years? If the answer is fuzzy, keep pushing — don't skip it just because the story sounds good.

Stage Three: Financial Checkup — Clearing the Four-Layer Defensive Screen One by One

This stage is where AI's role is most limited in the whole SOP, and also where most people make mistakes.

⚠️ Important Warning

Don't rely on AI alone to generate financial figures, especially specific numbers like ROE, EPS growth rate, or cash-flow figures. AI carries hallucination risk on financial data — it can give you a number that sounds reasonable but is actually wrong.

The right approach: use AI to frame the question and interpret meaning, and pull the actual numbers from SEC EDGAR, company filings, IBD MarketSmith, or Stockanalysis.com before having AI help interpret them.

How to Apply AI Across the Four-Layer Defensive Screen

PROMPT 3-A

Interpreting Financial Metrics (you supply the numbers, AI interprets them)

Here are the numbers I pulled from [Company]'s latest filing — please help me interpret them:

· EPS over the last four quarters (YoY growth): [fill in]

· ROE over the past three years: [fill in]

· Most recent quarter's free cash flow vs. net income: [fill in]

· Debt-to-equity ratio: [fill in]

Please answer:

1. What overall financial health picture do these numbers paint?

2. Which number concerns you the most, and why?

3. If I want to collect premium on this company with an options-selling strategy, what's the biggest tail risk from a financial perspective?

💡 The key to this prompt is "you supply the numbers." That shifts AI's role from "generating numbers" to "interpreting numbers," dramatically reducing hallucination risk while still giving you a genuinely useful analytical perspective.

Stage Four: Designing the Entry Structure — Direct and Indirect Combined, a Hybrid Deployment of Shares and Options

The first three stages answer "is this company worth acting on"; the fourth stage answers "how do you act on it." These two things must be strictly separated — a good conclusion from the first three stages is no excuse to rush into designing an entry, and "it just feels right" is no excuse to skip structure design.

ProfitVision's entry structure isn't either/or — it's not "buy shares" or "trade options" — it's about deciding how to combine the two based on the research conclusion, account status, and IV environment. In the language of military strategy: owning shares is the direct force (zhèng), options are the indirect force (qí) — only by combining direct and indirect can you maximize the value of a piece of research.

The Direct Force: Buying Shares

Establishes core exposure and fully captures the trunk of the trend. Suited to names with a strong moat, a clear trend, and a willingness to hold long-term.

The upside of holding shares is that it's direct, carries no time-decay pressure, and doesn't require weekly monitoring of a structure. The downside is lower capital efficiency, and unrealized losses can more easily shake your resolve to keep holding.

The Indirect Force: Options

Layered on top of a share position to add leverage efficiency (LEAP / PMCC) or cash-flow income (Bull Put / Covered Call).

The upside of options is higher capital efficiency, a definable maximum loss, and the ability to collect income during consolidation. The downside is that the structure needs managing and comes with a time limit.

Three Hybrid Entry Modes

Depending on the research conclusion and account status, the entry structure generally falls into one of three modes — you don't need all three every time:

Mode A: Pure Direct Force (Building a Share Position)

Suited when: the moat assessment is extremely strong, the long-term trend is clear, and IV is low enough that options offer poor value. Buy shares outright, use the 50MA as the trend-defense line, and don't layer on an options structure. You can later roll a Covered Call on the position for income.

Mode B: A Direct-Indirect Blend (Shares + Options, Two Lines)

Suited when: the research conclusion is strong, but you want a more capital-efficient deployment. For example, use 60–70% of your budget to buy shares as a core position, and the remaining 30–40% for a LEAP or a Bull Put Spread, letting the shares ride the trend while the options collect income or extend exposure.

Mode C: Pure Indirect Force (Options in Place of Shares)

Suited when: IV is high, the name is highly volatile (e.g. IBIT), or your account doesn't have enough capital to buy a sufficient number of shares outright. Use a LEAP (Delta 0.80+) to replicate the directional exposure of shares, while selling a Short Call for income to lower your cost basis.

PROMPT 4-A

Choosing an Entry Structure: Direct, Indirect, or a Blend?

I've completed the three-stage research on [Company/Ticker], summarized below:

· Moat assessment: [strong/medium/weak, one sentence on the most critical source of the moat]

· Four-Layer Screen results: [e.g.: Screen One passed, Screen Two passed, Screen Three IV Rank 28% (near the threshold), Screen Four passed]

· Current share price: $X, 50MA: $Y, recent support: $A–$B

· IV Rank: [value]

· Risk budget for this trade: $Z (the maximum I can afford to lose)

Please help me assess:

1. Given the current IV environment, is it better to use options (high IV makes the indirect force more attractive) or buy shares directly (low IV means thin options premium)?

2. If deploying a blend, how should the ratio between shares and options be designed?

3. For a PMCC, where should the LEAP's Delta and the Short Call's Delta be set, and why?

4. If buying shares outright, how should the cadence of rolling Covered Calls be designed? (DTE and Delta recommendations)

💡 IV Rank is the key variable in choosing the direct-indirect ratio. When IV is above 40%, options offer far better value than shares; when IV is below 20%, holding shares outright is actually more efficient.

PROMPT 4-B

Options Structure Math: Strikes, DTE, Max Loss

I've decided to use a [Bull Put Spread / PMCC / Covered Call] strategy on [Company] — help me design the specific structure:

· Current share price: $X

· Recent support range: $A–$B

· My Delta target: Short Put Delta < 30

· DTE target: 30–45 days

· Maximum loss my account can bear: $Z

Please calculate and output:

1. A recommended strike combination (Short Put / Long Put, or LEAP / Short Call)

2. The expected maximum premium collectible

3. Maximum loss amount and the breakeven point

4. The buy-back target at 50% max profit (the corresponding remaining premium value)

5. Any known major events to watch for within the DTE window?

💡 Always have AI explicitly output the maximum-loss calculation, and verify it yourself by hand — this is the single most important number to confirm before entry, to make sure it's within your 5% risk budget.

PROMPT 4-C

Pre-Entry Checklist: Direct-Indirect Blend Version

Here is my entry plan — please help me do a final check:

· Share position: [buy X shares, total $Y] or None

· Options position: [strategy name, strike, DTE, expected premium received/paid] or None

· Combined maximum loss: $Z

Please confirm each item:

□ Is the combined maximum loss of shares + options within 5% of the account?

□ After adding this position, is the account's total exposure within 15%?

□ What is the stop-loss trigger for the shares? (Break below the 50MA? Break below support?)

□ Is the options DTE within the 30–45 day range?

□ Is the strike below recent support? (For the Short Put leg of a Bull Put)

□ Are there any earnings or major events within the DTE window? If so, has that been factored into the risk assessment?

□ If both the shares and the options move against me at the same time, can I psychologically accept that loss and keep executing the system?

If any answer is "no," please explain what needs to be adjusted.

💡 The last question is the most important one on the whole checklist — it's not asking about numbers, it's asking about your psychological limits. Only if you can genuinely accept the maximum loss can you keep following the rules when you're underwater, instead of panic-selling.

Choosing AI Tools: Different Tools for Different Tasks

Claude (First Choice for Deep Analysis)

Moat analysis, interpreting financial metrics, working through strategy logic. Strong at long-context comprehension, and performs best on tasks like "play a bearish analyst" that need an adversarial perspective.

ChatGPT + Browse (Real-Time Information)

Scanning recent major events, summarizing earnings calls, confirming the latest earnings figures. Use this first for anything that needs live search, to ensure the information is current.

Claude + Python (Data Processing)

If you have the original SEC filing as a PDF or CSV, have Claude write a Python script to extract specific numbers for you, saving the time of flipping through the report by hand.

Things Not to Use AI For

Don't have AI generate specific numbers like A/D Rating, RS, or IV Rank — these must be pulled directly from IBD, IBKR, or Tastytrade. AI's hallucination risk is highest on this kind of real-time market data.

A Time Budget for a Complete Research Cycle

How long does researching one company take with this SOP?

Stage One (Macro Positioning): 20–30 minutes. Run two prompts, read the output, condense it into one paragraph
Stage Two (Moat): 30–45 minutes. This stage needs the most critical reading — don't accept it at face value
Stage Three (Financial Checkup): 30–40 minutes. Pulling numbers from SEC/filings (20 minutes), having AI interpret them (10–20 minutes)
Stage Four (Options Structure): 15–20 minutes. Confirm IV and technicals, run the prompts to design the structure

All told: roughly 1.5–2 hours to complete a full research cycle on one company. That's already much faster than the traditional approach, but shouldn't be compressed further — the time you save should go toward thinking and verification.

AI doesn't make you research faster — it lets you see deeper in the same amount of time. Spend the time you save on critically reading AI's output, not on going even faster.

Finally: The End Point of Research Isn't a Report — It's a Clear Decision

After finishing all four stages, you should be able to answer the following questions:

Is this company's position on the industry map favorable?
Can its moat keep generating financial value over the next three years?
Did it clear the Four-Layer Defensive Screen? Which layer was the weakest link?
Is the maximum loss in the entry structure within a range I can bear and keep executing the system?

If you have a clear answer to all four questions, you're qualified to enter. If any answer is "uncertain," that uncertainty is itself the answer — wait for the next opportunity.

The goal of research isn't finding the perfect stock — it's converting your understanding of a company into an entry decision that's structured, bounded, and able to absorb being wrong.

Disclaimer: All content in this article is for research and educational reference only and does not constitute investment advice. The strategies, tools, and prompt examples mentioned are for illustrative purposes only and do not represent any buy or sell recommendation. Options trading carries significant risk and can result in the total loss of principal. Investors should judge and bear the corresponding risk according to their own risk tolerance.

The AI Deep Stock Research SOP: A Four-Stage Process From Macro Positioning to Options Entry