Workflow: Use RSI to Spot Overbought and Oversold Levels with Figma

Workflow: Use RSI to Spot Overbought and Oversold Levels with Figma

In technical trading, the Relative Strength Index (RSI) is one of the most trusted indicators to identify overbought and oversold market conditions. But what if you could visualize this workflow more clearly — not just on trading charts, but as a designed, explainable concept using Figma?

This step-by-step guide from AI Computer Classes – Indore shows you how to analyze RSI trends, spot trade signals, and design your own RSI-based trading workflow in Figma for clarity, presentation, or teaching purposes.

Whether you’re a trading enthusiast or a data design learner, this is the perfect mix of finance + visualization + AI tools.

💡 What is RSI (Relative Strength Index)?

The RSI is a momentum oscillator that measures the speed and change of price movements.

It ranges from 0 to 100, helping traders identify potential reversal points.

⚙️ RSI Levels to Remember:

• Above 70 → Overbought (potential sell zone)
• Below 30 → Oversold (potential buy zone)
• 50 → Neutral (trend confirmation point)

💬 In simple terms:

When the RSI crosses 70, the market may be overheated.

When it drops below 30, the asset may be undervalued.

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🧠 Step 1: Understand the RSI Calculation

The RSI is calculated using the formula:

RSI=100−1001+RSRSI = 100 - \frac{100}{1 + RS}RSI=100−1+RS100​where:

RS=AverageGainAverageLossRS = \frac{Average Gain}{Average Loss}RS=AverageLossAverageGain​While traders usually use charting platforms like TradingView or MetaTrader, learning how RSI is derived helps you trust your strategy better.

You can use Excel or Python to calculate it manually for better understanding.

Example (in Excel):

PeriodCloseChangeGainLossAvg GainAvg LossRSRSI1120-------2123+330----...........................

🧩 Step 2: Visualize RSI Workflow in Figma

Once you understand RSI, the next step is to visualize the logic flow.

Figma helps you create a simple visual that explains RSI behavior — perfect for presentations or team discussions.

Create this flow:

1. Price Data Input (from TradingView/Excel)
2. → RSI Calculation Node
3. → Compare RSI with Thresholds (30 & 70)
4. → Generate Signal: Buy / Hold / Sell
5. → Plot on Chart / Dashboard Visualization

🎨 In Figma:

• Use arrows and shapes to represent data movement.
• Color-code signals:
• 🟢 Buy Zone (RSI < 30)
• 🔴 Sell Zone (RSI > 70)
• 🟡 Neutral (30 < RSI < 70)

You can even use AI plugins in Figma to auto-generate icons or annotate signals visually.

💡 Bonus Tip:

Ask ChatGPT to generate “RSI-based trading flow text” to copy directly into your Figma labels or notes.

Example Prompt:

“Write a short description for each RSI stage in a trading flow diagram for Figma.”

🧮 Step 3: Combine RSI Data with Power BI

Once your Figma design explains the logic, connect it with real market data using Power BI.

• Import RSI data from Excel or TradingView CSVs.
• Create dynamic visuals showing RSI trends.
• Add filters for timeframes (1D, 1W, 1M).
• Highlight when RSI crosses 30 or 70 using conditional formatting.

This allows you to present live RSI dashboards — a great skill for analysts or educators.

📈 Step 4: Spot Overbought and Oversold Levels in Practice

Here’s how to interpret RSI in real charts:

RSI RangeMarket ConditionAction0–30OversoldConsider Buying30–50RecoveryWait for confirmation50–70UptrendHold or partial profit70–100OverboughtConsider Selling

Example:

If RSI = 28 on Reliance stock — it might be undervalued.

If RSI = 75 — the stock could be overheated.

💬 Combine RSI with support/resistance zones for better accuracy.

🧰 Step 5: Build an RSI Cheat Sheet in Figma

Figma isn’t just for UI — it’s also perfect for visual cheat sheets!

Create a small “RSI Decision Dashboard” that shows:

• RSI gauge meter (0–100)
• Label for current market mood
• Signal text (Buy, Hold, Sell)
• Last 3 RSI readings

💡 Use Figma widgets like progress bars and gradients to make it visually appealing.

You can even export your design as a PDF handout for training sessions.

⚙️ Step 6: Automate RSI Alerts with ChatGPT + Python

To take your workflow a step further, use Python scripts to calculate RSI automatically.

Example prompt for ChatGPT:

“Write Python code to calculate RSI from historical stock data in a CSV file.”

Once generated, you can:

• Run it in Google Colab or VS Code.
• Export output to Excel or Power BI.
• Sync alerts via email or Telegram when RSI crosses thresholds.

This bridges the gap between trading logic, design visualization, and AI-driven automation.

💡 AI + Trading = Smart Decisions!

At AI Computer Classes – Indore, students explore how AI tools like ChatGPT and Power BI enhance real-world trading workflows.

🧭 Step 7: Present and Share Your RSI Workflow

Use your Figma RSI diagram and Power BI dashboard together to present:

• How RSI signals are generated.
• How traders can act based on those signals.
• Real examples of RSI effectiveness in different market conditions.

Perfect for presentations, trading workshops, or educational videos.

🎯 Conclusion

The RSI is a simple yet powerful indicator that helps traders make smarter decisions. By using Figma for visualization, Power BI for analysis, and ChatGPT for automation, you can create a complete, modern RSI workflow — both practical and visually stunning.

At AI Computer Classes – Indore, you’ll learn to combine technical analysis and design thinking to create professional-grade trading insights that stand out.

Start designing your RSI dashboard today and elevate your market analysis game! 🚀

📞 Contact AI Computer Classes – Indore ✉ Email: hello@aicomputerclasses.com 📱 Phone: +91 91113 33255 📍 Address: 208, Captain CS Naidu Building, near Greater Kailash Road, Opp. School of Excellence For Eye, Opp. Grotto Arcade, Old Palasia, Indore, Madhya Pradesh 452018 🌐 Website: www.aicomputerclasses.com