₹47,000 every month. That's what my friend Rohit was paying a fund advisory service to tell him which stocks matched his criteria. Six filters — RSI below 40, volume spike above 200% of 20-day average, 200-DMA crossover, sector rotation signals, delivery percentage above 60%, and promoter holding changes in the last quarter.
One Sunday afternoon, a Python script, and a free broker API later — Rohit doesn't pay that ₹47,000 anymore. "Bhai, pehle 2 ghante screening mein jaate the. Ab chai peete peete list aa jaati hai."
This is the story of how a retail trader replaced an expensive advisory with a script that costs literally nothing to run — and why this pattern applies to far more than just stock screening.
The Problem: 2 Hours Every Morning, Staring at Screens
Rohit is a swing trader based in Pune. He's been trading for seven years, and his edge has always been discipline — he never enters a trade without all six of his filters confirming. The problem was execution speed. Every morning before market open, he'd manually check 150+ stocks across three different screening tools, cross-reference the results, and build his watchlist.
Two hours. Every single trading day. That's roughly 500 hours a year spent on a task that follows the exact same logic every time.
The advisory service he subscribed to ran similar filters, but their shortlist arrived at 9:30 AM — 15 minutes after market open. By then, the best entry prices on momentum stocks were already gone.
The Solution: A Python Script That Runs Before You Wake Up
The script connects to Rohit's broker API at 9:15 AM — one minute before market opens. It pulls the previous day's closing data for all NSE-listed stocks (roughly 2,000 symbols). Then it runs six filters in sequence.
The entire filtering process takes about 12 seconds. By 9:16 AM, Rohit receives a WhatsApp message with a shortlist of 5-12 stocks that passed all six filters.
The numbers that matter: 2 hours/day reduced to 0 active time. ₹47,000/month advisory cancelled. Total recurring cost: ₹0.
Why This Works Better Than an Advisory Service
Speed. An automated script delivers results in seconds. A team of analysts takes 30-45 minutes. In momentum trading, those minutes are the difference between a 2% gain and a missed entry.
Customisation. Rohit's six filters are specific to his trading style. The advisory service overlapped about 70% with what he wanted. That remaining 30% mismatch meant he was still doing manual screening on top of the advisory's shortlist.
Adaptability. When Rohit wanted to add a seventh filter last month (institutional buying from bulk deal data), it was live by Saturday evening. Try asking an advisory service to customise their methodology for one subscriber.
The Cost Breakdown: ₹5.64L/Year Saved
| Item | Advisory Service | Python Script |
|---|---|---|
| Monthly cost | ₹47,000 | ₹0 |
| Annual cost | ₹5,64,000 | ₹2,000 (one-time API fee) |
| Delivery time | 9:30 AM (15 min after open) | 9:16 AM (before open) |
| Customisation | Fixed filters | Fully custom |
| Manual screening still needed | Yes | No |
What You Actually Need to Build This
You need Python 3.x with Pandas, a broker API account (Kite Connect from Zerodha at ₹2,000 one-time, or Fyers API v3 which is completely free), a server or always-on machine, and the WhatsApp Business API for notifications.
If you've ever written an IF statement in Excel, you can understand the logic behind a stock screener script.
The Bigger Lesson
Rohit's story isn't really about stock screening. It's about a pattern: the most expensive services are often the ones running the simplest logic on publicly available data.
The sweet spot for automation is repetitive tasks with clear rules and expensive human execution. Before you automate anything, ask yourself: Is the logic explicit enough to explain to a 10-year-old? Does the task repeat on a predictable schedule? Is the current cost of doing it manually more than the one-time cost of building the script?
If all three answers are yes, you've found your next automation project.
What Happened After
Six months in, Rohit's trading performance improved — not because the script picked better stocks, but because it freed his morning for what actually matters: reading quarterly results, analysing management commentary, and making judgment calls.
That's what good automation does. It doesn't replace your expertise. It removes the mechanical layer so you can spend 100% of your time on the work that actually moves the needle.
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