Second video in the series on learning options with AI. In the first video we saw what a Call is and how ChatGPT’s theory translated into a real trade in ProRealTime. Today it’s the turn of its mirror sister: the Put. Here we get into how to make money when a stock goes down, with a real example on Tesla.
The prompt and what ChatGPT tells us
We continue the conversation in the same project where we asked it the basics. We simply ask: “What is a Put?”. Its answer is parallel to the Call’s, with a single critical change:
The difference from the Call is in one word: sell. Where the Call gives you the right to buy, the Put gives you the right to sell.
- Call — you bet (or rather, you reasonably expect) that the price will go up
- Put — you expect the price to go down
With this alone we have two directions to make money with options: if we buy a Call and the stock rises, we win; if we buy a Put and the stock falls, we also win. A bit like what happens in stocks when you go long or short.
ChatGPT’s example with Tesla
Tesla trades at $300. You buy a Put with strike 280, expiring in one month. You have the right to sell Tesla at $280 even if the price falls sharply.
- Good case — Tesla drops to $240. Your Put is worth a lot because you could sell at 280 something the market pays 240 for
- Bad case — Tesla stays at 300 or rises. No one would want to sell at 280 something the market pays 300 or more for. The Put can end up worth zero
If the Put costs $5 of premium, the break-even is calculated the opposite way to the Call: strike − premium = 280 − 5 = $275. Below 275, you start to win. The mental idea is simple: Call is bullish, Put is bearish.
The three variables that affect an option’s price
Here ChatGPT closes with something very important:
This is key. An option can lose value even if the price moves in your favor — because time gets used up and because volatility changes. We’ll see this in detail in the next video, together with the concepts of in-the-money, at-the-money and out-of-the-money.
Jumping to ProRealTime: a real Put on Tesla
Just like in the previous video, we’re going to take the theory to a professional platform. Tesla is trading at $446 as we record the video (we wish we’d bought it at 300 like in the example). The absolute price doesn’t matter — what matters is understanding the structure.
Steps in ProRealTime
We open Trading → Options chain
We check in the top left that the underlying is Tesla
We choose an expiration — 29 days (the closest to a month)
The whole column to the right of the strike is the PUTS — that’s where we work
Chosen strike: 420 (about $25 below the current price)
In the green column a premium of $12.10 appears. Remember the key detail we already saw in the Call article: each contract is 100 shares, so we’ll actually pay 12.10 × 100 = $1,210.
The risk graph: mirror of the Call
We move to the Analysis tab and there we see the payoff graph. It’s exactly the mirror image of the Call’s graph:
- The whole left zone (Tesla falls) — profits, which grow the more it falls
- The whole right zone (Tesla rises or stays the same) — limited, flat loss: at most we lose the $1,210 premium
- The blue dot marks the break-even — in this example, $407
If I hover over the graph, ProRealTime tells me: Tesla has to fall 8.76% in the next month to reach the break-even. Is that feasible? Looking at Tesla’s recent history, absolutely: in the last few months it has made moves of 19-21% over similar periods.
A realistic profit example
If Tesla falls 10% in the month, ProRealTime shows me the profit would be approximately $800. With an investment of $1,210 and a 10% drop in a month, almost doubling the premium. It’s feasible — not likely, but feasible.
The new concept: probability of profit (POP)
Here we introduce a metric we didn’t see in the Call video but which is fundamental: the probability of profit (POP), which ProRealTime calculates automatically for you.
In the Tesla example with strike 420, the POP is 26%. That is, according to the mathematical models (derived from the Black-Scholes formula), the trade has approximately a 26% chance of ending in profit.
What we leave for the next video
ChatGPT suggests for the next lesson the concepts of in-the-money, at-the-money and out-of-the-money, and explaining why an option can lose value even if the price moves in your favor. That’s the natural next step — the effect of time (theta) and volatility (vega) on the premium.
Conclusion
In this second video we’ve seen the Put as the opposite side of the Call: same structure, but betting that the price goes down. ChatGPT explains it clearly, but as always the important nuances (the 100 multiplier, the payoff graph, the probability of profit) are truly understood when we see them in ProRealTime with real prices. In the next video we’ll get into the concepts that truly separate knowing the theory from knowing how to trade: how time and volatility affect an option’s price. Don’t forget to comment and like the video to keep unlocking content and giveaways.
