The Exact ChatGPT Prompt to Screen Your Portfolio for Covered Calls

The Short Answer: Here Is the Prompt

Copy this into ChatGPT right now and you will get a structured covered-call screen for any stock you already own:

"I own [NUMBER] shares of [TICKER] with a cost basis of $[PRICE]. The stock is currently trading at $[CURRENT PRICE]. I want to sell covered calls to generate monthly income without getting my shares called away unless the stock rises more than [X]% from today. Using standard covered-call strategy logic, suggest 2-3 strike prices and expiration dates I should consider, explain the trade-off between premium collected and assignment risk for each, and flag any upcoming earnings dates or ex-dividend dates I should watch out for. Format the output as a comparison table."

That single prompt does the heavy lifting. The rest of this article explains why each piece of that prompt matters, how to adapt it for your real holdings, and where AI-generated output can steer you wrong if you are not careful.

Why a Well-Built Prompt Beats a Vague One

ChatGPT is a language model, not a live brokerage terminal. It does not pull real-time options chains. What it does extremely well is apply structured reasoning to the inputs you give it. A vague prompt like "help me sell covered calls on AAPL" produces generic advice. A prompt with specific numbers produces a specific, actionable comparison you can then verify against your broker's live chain.

Think of the prompt as a checklist you hand to a knowledgeable assistant. The more context you provide — cost basis, how much upside you are willing to give up, income goal, time horizon — the more useful the output. The Options Industry Council (OIC) describes covered calls as a strategy that trades away upside potential in exchange for immediate premium income. Your prompt needs to encode that trade-off explicitly so ChatGPT can reason about it correctly.

The five inputs that matter most are: current stock price, your cost basis, your maximum acceptable assignment price, your target income per month, and any near-term catalysts like earnings or dividends. Leave any of those out and the model will either guess or give you a generic answer.

A Worked Example: Screening AAPL With the Prompt

Let's say you own 100 shares of Apple (AAPL) with a cost basis of $158 per share. AAPL is trading at $213.50 today. You are comfortable being assigned (having your shares called away) at $225 or higher, but not below. You want to target roughly $150–$200 in monthly premium income on the position.

Here is the filled-in prompt:

"I own 100 shares of AAPL with a cost basis of $158. The stock is currently trading at $213.50. I want to sell covered calls to generate monthly income without getting my shares called away unless the stock rises above $225. Using standard covered-call strategy logic, suggest 2-3 strike prices and expiration dates I should consider, explain the trade-off between premium collected and assignment risk for each, and flag any upcoming earnings dates or ex-dividend dates I should watch out for. Format the output as a comparison table."

ChatGPT will typically return something like this comparison (these numbers are illustrative — always verify against your live chain):

Strike $215, 21-day expiry: estimated premium ~$1.80/share ($180 total), delta ~0.45, moderate assignment risk if stock moves up 0.7%. Strike $220, 21-day expiry: estimated premium ~$1.10/share ($110 total), delta ~0.30, lower assignment risk, stock needs to rise 3%. Strike $225, 21-day expiry: estimated premium ~$0.65/share ($65 total), delta ~0.18, lowest assignment risk, stock needs to rise 5.4%.

The model will also flag that AAPL typically reports earnings in late January, late April, late July, and late October — a critical warning because selling a call that expires after an earnings date dramatically increases the chance of a large move that either wipes out your premium gain or triggers assignment at an unfavorable price. FINRA has noted that earnings announcements are among the most common catalysts for sharp single-day moves in individual stocks.

From this output you can see the classic covered-call trade-off in plain numbers: the $215 strike pays nearly three times the premium of the $225 strike, but it puts your shares at risk of being called away if AAPL moves even slightly. Most income-focused covered-call writers targeting 1–2% monthly yield on a stock they want to keep will lean toward the $220–$225 range in this scenario.

How to Adapt the Prompt for a Multi-Stock Portfolio

If you hold several positions, run the prompt once per ticker rather than dumping all your holdings in at once. ChatGPT handles single-stock analysis more accurately than portfolio-wide analysis because it can focus its reasoning on one set of trade-offs at a time.

For a portfolio screen, build a simple spreadsheet with five columns: Ticker, Shares Owned, Cost Basis, Max Acceptable Assignment Price, Monthly Income Target. Fill in one row per stock. Then cycle through each row using the template prompt above, pasting the results into adjacent columns. Within 20–30 minutes you will have a side-by-side view of every covered-call opportunity in your portfolio.

A useful add-on line to include in each prompt: "Also tell me the approximate implied volatility rank (IVR) context for this stock — is this a high-IV or low-IV environment for selling premium?" ChatGPT cannot pull live IVR data, but it can explain the general volatility character of a stock like NVDA (historically high IV, which means richer premiums but bigger risk of large moves) versus a stock like SPY (lower IV, thinner premiums, more predictable range). That context helps you prioritize which positions to write calls on first.

For Canadian investors: the CRA treats premiums received from writing covered calls as either capital gains or business income depending on your trading frequency and intent. If you are running a systematic monthly screen like this, discuss the tax treatment with your accountant before scaling up. The CRA's interpretation bulletins on options income are worth reviewing with a tax professional.

What Are the Real Risks of Using AI for Options Screening?

This is the section most AI-generated investing content buries or skips. We are not going to do that.

First, ChatGPT's training data has a knowledge cutoff. It does not know today's options prices, today's implied volatility, or whether an earnings date was just rescheduled. Every number it gives you is an estimate based on historical patterns and general options math. You must verify every strike price, premium estimate, and expiration date against your broker's live options chain before placing any trade.

Second, the model can hallucinate specific numbers with apparent confidence. It might tell you a $220 AAPL call is trading at $1.40 when the actual bid-ask is $0.95–$1.05. Treat every premium figure as a ballpark, not a quote.

Third, covered calls are not risk-free. The SEC has published investor guidance noting that while covered calls reduce downside by the amount of premium collected, they do not protect against a large drop in the underlying stock. If AAPL falls from $213.50 to $180, your $1.80 premium on the $215 call offsets only $1.80 of that $33.50 loss. The OIC makes the same point in its covered-call strategy documentation: the premium is a partial hedge, not a floor.

Fourth, do not use ChatGPT output as a substitute for understanding the strategy yourself. The FINRA BrokerCheck system and your brokerage's options agreement both require you to confirm you understand the risks of options trading before you are approved to trade them. AI can help you think through a trade, but the responsibility for the decision is yours.

Three Prompt Tweaks That Improve the Output

After testing dozens of variations, three small additions consistently improve the quality of ChatGPT's covered-call analysis:

1. Add your brokerage commission. "My broker charges $0.65 per contract" forces the model to factor transaction costs into the net premium calculation. A $65 gross premium on one contract becomes $64.35 net — small on one trade, but meaningful if you are writing calls on 10 positions monthly.

2. Specify your tax situation in broad terms. "I have held these shares for more than one year" or "these shares are in a tax-deferred account" gives the model context to flag relevant tax considerations. The IRS treats premiums received from covered calls as short-term capital gains in most cases, and writing deep in-the-money calls can affect the holding period of your underlying shares under IRS qualified covered call rules (see IRS Publication 550). In Canada, the CRA has similar holding-period considerations.

3. Ask for a "what could go wrong" section. Appending "End your analysis with a brief list of the two or three biggest risks specific to this trade" reliably produces a more balanced output. It forces the model to surface earnings risk, dividend capture risk, and liquidity risk rather than just presenting the income upside.

None of these tweaks require technical options knowledge to use. They just give the model more signal to work with.

Can ChatGPT pull live options prices for my covered call screen?

No. ChatGPT does not have access to real-time market data or live options chains. It can apply options strategy logic to the numbers you provide, but every premium estimate it generates must be verified against your broker's live quote before you place a trade.

Is it safe to make covered call trades based on ChatGPT output?

ChatGPT output is a starting point for analysis, not a trade recommendation. The SEC and FINRA both require investors to understand the risks of options before trading them. Use the AI output to narrow your choices, then confirm every number — strike, premium, expiration, earnings date — against your brokerage platform.

What information do I need to give ChatGPT to get a useful covered call suggestion?

At minimum: the ticker, number of shares you own, your cost basis, the current stock price, and the highest price at which you are comfortable being assigned. Adding your monthly income target and any known upcoming events like earnings dates makes the output significantly more useful.

How does writing covered calls affect my taxes in the US and Canada?

In the US, the IRS generally treats premiums received from covered calls as short-term capital gains, and writing deep in-the-money calls can reset the holding period of your underlying shares under qualified covered call rules outlined in IRS Publication 550. In Canada, the CRA may treat premiums as capital gains or business income depending on your trading frequency and intent, so Canadian investors should consult a tax professional before running a systematic covered-call program.

Which stocks work best for a ChatGPT-assisted covered call screen?

Liquid, widely-traded stocks with active options markets — like AAPL, MSFT, NVDA, and SPY — give you the tightest bid-ask spreads and the most reliable premium data to verify against ChatGPT's estimates. Thinly traded stocks with wide spreads are harder to execute efficiently regardless of what the AI suggests.

How often should I run this ChatGPT covered call screen on my portfolio?

Most covered-call writers on a monthly income strategy run a screen once per month, roughly one to two weeks before their existing calls expire, to plan the next round of writes. Running it more frequently than weekly rarely adds value and increases the risk of overtrading, which erodes net returns through commissions and bid-ask spread costs.