Daily monitoring of stock data like price, volume, and price patterns (HH, HL, LL, LH) is vital for serious traders. This is especially true for those using Price Action strategies. We don’t have to manually collect this data for each stock. Instead, we can use Power Automate to streamline the process. This saves hours of effort.

🎯 Objective

We want to automate the extraction and storage of the following for 40 stocks daily:

• 📅 Date
• 📌 Stock Name
• 💵 Closing Price
• 🔺 HH (Higher High)
• 🔻 HL (Higher Low)
• 📉 LL (Lower Low)
• 🔼 LH (Lower High)
• 🔁 Volume
• 🧠 (Optional): RSI, 50/200 EMA, or other indicators

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🔧 Tools Required

Tool	Purpose
Power Automate	To schedule & automate flows
Screener.in or TradingView	Source for stock data
Excel Online or Dataverse	Data storage
Power BI	Data visualization & insights

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🧭 Automation Architecture

Option 1: Excel Storage (One Sheet Per Stock)

• Excel file named: Daily_Stock_Tracking.xlsx
• Each worksheet = 1 stock (e.g., TATAMOTORS, RELIANCE)
• Power Automate appends data row daily

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Option 2: Microsoft Dataverse Storage

• One central table for all stocks
• Fields: Date, Stock, Price, HH, HL, LL, LH, Volume, Other Indicators

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🔄 Step-by-Step Setup

🔹 Step 1: Prepare Data Source

Use Screener.in or TradingView APIs or scraping methods:

• Screener: Basic HTML scraping (if allowed)
• TradingView: Alerts + webhook (for specific stock alerts)
• For bulk: Use websites like nseindia.com or [Yahoo Finance API] via third-party connector

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🔹 Step 2: Create Power Automate Flow

• Trigger: Recurrence (daily at 4 PM)
• Loop: For each of the 40 stocks:
  • Fetch stock page using HTTP (or API)
  • Parse the page to extract:
    • Price
    • Volume
    • Day’s High/Low
    • Previous Highs/Lows for HH, HL, LL, LH
  • Append row to Excel table (or Dataverse)

📌 Excel Example Table Columns:

Date	Stock	Price	HH	HL	LL	LH	Volume

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📁 Option A: Excel Storage (OneDrive)

1. Create a workbook with 40 sheets (stock names).
2. In Power Automate:
   • Use “Add row to table” action.
   • Dynamically select the right sheet using the stock name.
3. Store file on OneDrive or SharePoint for Power BI access.

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📦 Option B: Dataverse Storage (Recommended)

1. Create a custom table in Dataverse:
   • Fields: Date, Stock, Price, HH, HL, LL, LH, Volume, RSI, EMA_50, etc.
2. Power Automate uses “Add new row” action per stock daily.
3. Centralized, scalable, ideal for filtering and reporting in Power BI.

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📊 Power BI Dashboard Ideas

• Stock Overview: Price movement & volume trends
• Pattern Insights: Identify HH/LL formations
• Watchlist Alerts: Highlight when HH > previous HH or LL < previous LL
• Indicators Heatmap: RSI, EMA crossovers, Volume surge
• Filter by Sector: Compare FMCG vs. IT vs. Banking, etc.

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🧠 Best Practices

• ⏱ Schedule flows after market close (post 3:30 PM IST).
• 💾 Use Dataverse if you plan long-term storage & deeper analytics.
• 📉 Ensure accuracy by cross-verifying a few stock values weekly.
• 🔐 Comply with source site’s terms of use when scraping data.

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🔚 Final Thoughts

This system transforms daily tracking into a hands-free automation process. You are a price action trader. You’re an investor building long-term charts. You are an analyst looking to draw insights. This setup powered by Power Automate, Excel/Dataverse, and Power BI gives you the edge.