📊 Day 3 Recap: Using Technical Indicators & ChatGPT for Smarter Trades 💰

✅ Another solid trading day using technical analysis + AI insights to refine my trade entries and exits. Today’s focus was on SPY puts, playing a rejection at key resistance.

🔹 Key Indicators Used: • RSI: Helped identify overbought conditions and potential reversal zones. • MACD: Confirmed momentum shifts before entering positions. • Support/Resistance Levels: Guided entries for puts after a failed breakout at 601.

📉 Trade Execution: • Waited for confirmation before entering SPY 600P & 601P. • Took profits after the rejection & breakdown below 600. • Final P&L: +$222.87 (+9.81%) 🎯

🔍 Lesson of the Day: Patience + proper risk management = better entries & exits. Let price action guide the trade, not emotions.

🔥 Next Goal: Keep refining strategy for higher win rate & better risk-to-reward setups.

Disclaimer this post was written by chat GPT in the same chat I asked the questions in I will now try to have chat gpt answer questions people had in last post Q&A from some questions last post

Here are responses to the main questions from everyone except the OP in the Reddit post:

1️⃣ What were your prompts?

(Asked by CHL9 & WoodenBrick_)

I used a structured approach to prompts, focusing on technical indicators and market context. Here’s an example of a typical prompt:

“SPY is currently trading at [current price]. RSI is at [value], MACD shows [trend], and key support/resistance levels are [specific levels]. Based on these indicators, is there a stronger setup for calls or puts for a short-term trade?”

This helps generate analyzed trade scenarios rather than a simple “buy/sell” suggestion.

2️⃣ What prompt do you use to unlock this potential?

(Asked by Legitimate-Today-457)

To maximize the potential of ChatGPT for trading, I focus on: • Real-time technical indicator interpretation (RSI, MACD, support/resistance). • Market sentiment assessment (trend strength, volume spikes). • Scenario-based questions (e.g., “What happens if SPY rejects resistance at 601?”).

This approach helps me confirm trade setups rather than blindly following signals.

3️⃣ Does it ever give wrong info? Like when volatility is too high?

(Asked by ifatmikei)

Yes, ChatGPT doesn’t have live market data, so it can’t directly predict breaking news, sudden volatility spikes, or market-moving events. • If volatility is too high (like CPI/Fed events), indicators can give false signals. • That’s why I always double-check price action and volume before executing trades.

4️⃣ Why does it give generic advice instead of real data?

(Asked by LordCustard)

The model doesn’t pull live market data but analyzes technical indicators provided to it. If you just ask: “Should I buy SPY calls or puts?” It will give a generic answer.

To get better insights, I structure prompts with: ✅ RSI, MACD, & trend analysis ✅ Key support/resistance zones ✅ Expected momentum shifts

That way, it functions as a trade assistant, not just a generic bot.

5️⃣ Is there a specific risk parameter you use?

(Asked by ifatmikei)

Yes, I use: • ATR (Average True Range): To measure expected volatility. • Risk-reward ratio: Usually 1:2 (e.g., risking $1 to make $2). • Stop-loss based on key levels: (e.g., cut a put trade if SPY breaks above resistance).

These parameters help manage risk and avoid bad entries.

Final Thoughts

ChatGPT isn’t a crystal ball, but when used with proper technical analysis, it helps confirm higher-probability trade setups.

Would love to hear how others optimize their prompts! 🚀