Understanding Stock Data

The first time I looked at a stock quote

I remember the first time I seriously opened a stock page, probably an aggregator screen or NSE's own site. There were so many numbers. A big price in the centre. A green percentage. Open, High, Low, Close, Volume. 52-week range. Circuit limits. Market cap. P/E. P/B. EPS.

I had no idea what any of it meant. I assumed I needed to understand all of it before I could do anything. So I closed the tab and went back to my Fixed Deposit.

Here's what I wish someone had told me then: most of those numbers are noise. Only five tell you what a stock did on any given day. They're called OHLCV. And if you're building a systematic strategy, you only need to deeply understand one of the five.

Reading a stock quote, the five numbers

Every stock listed on NSE or BSE generates five pieces of data every trading day. Here is a real one. Infosys on Friday, 9 October 2026, straight from the NSE end of day file.

These five numbers are called OHLCV: Open, High, Low, Close, Volume. Read the card like a story. The stock opened at ₹1,007.30, which was also the low, so buyers were in charge from the first minute. It touched ₹1,030.90, gave a little back and closed at ₹1,023.40, up 2.65%. And 1.41 crore shares changed hands, about 43% more than its 30 day average of 98 lakh. A rise with heavy volume. Hold on to that, we come back to it below.

Every systematic strategy, every factor model, every back test runs on these five numbers going back years. That's the raw material.

O, Open: where the day began

The opening price is not whoever shows up first at 9:15 AM. NSE runs a pre-open session from 9:00 AM. For about eight minutes buyers and sellers submit orders but nothing trades. The order window then closes at a random moment in the last minute, so nobody can game the final second, and the system runs a call auction: it finds the single price at which the most shares can change hands. That's the open.

H and L, High and Low: the day's range

During 9:15 AM to 3:30 PM, every trade gets recorded. The highest price any trade occurred at is the High. The lowest is the Low. Together they show how much the stock swung during the day.

Two separate safety systems sit on top of this. Most single stocks carry a daily price band of 2%, 5%, 10% or 20%; the stock keeps trading, but no order can execute beyond the band. Stocks with F&O contracts have no fixed band and a wider, dynamic one instead. The market wide circuit breaker is different: if the Nifty 50 or Sensex falls 10%, 15% or 20% in a day, all trading halts for a set time.

For a systematic investor, High and Low are mainly useful for understanding volatility, how much a stock tends to swing. The Low Volatility factor (stocks that move less tend to deliver better risk-adjusted returns) is built entirely on this idea. We go deep on that in Path 3. On 9 October 2026 the Nifty100 Low Volatility 30 index had moved with an annualised volatility of 12.0% over two years, against 18.9% for the Nifty200 Momentum 30. Same market, very different rides.

C, Close: the only number that really matters

Here's my honest view after years of building systematic strategies: the closing price is the most important number in all of stock market data.

For years the closing price on NSE was the volume weighted average price (VWAP) of all trades in the last 30 minutes, 3:00 PM to 3:30 PM. Not the last trade. Not the average of High and Low. That still holds for most stocks. Since 3 August 2026, stocks with F&O contracts get their close from a closing auction instead: continuous trading stops at 3:15 PM, orders pool for a few minutes, and one price that matches the most buying and selling becomes the close.

Both methods have the same purpose. They make the close hard to push around. One large order can briefly spike the High or Low. Moving a 30 minute average, or an auction that pools the whole order book, takes far more money and leaves a trail. The closing price is what the market, as a whole, thought about this stock at the end of a full day.

This is also why RupeeCase updates after market hours, not during the day. In the evening NSE publishes the end of day files, every closing price gets loaded and every ranking is recalculated. That's the rhythm systematic investing runs on, day by day, not second by second.

1. 3:00 PMThe reference window opens: trades from here feed the closing calculation.
2. 3:15 PMF&O stocks stop continuous trading and enter the closing auction.
3. AuctionBuy and sell orders pool; one price that matches the most shares is found.
4. CloseThat price, or the volume weighted average for other stocks, becomes the official close.

V, Volume: how many shares changed hands

Volume is the total shares traded in a day. If 1.41 crore shares of INFYInfosys traded today, that's the volume. It signals two things: conviction and liquidity. Read it against the stock's own average, never in isolation. 1.41 crore is a quiet day for some stocks and a frenzy for others.

Reading a real stock quote: what to ignore

When you open any stock page, on NSE's own site or any broker app, you'll see more than OHLCV. Here's what else shows up and whether it matters right now:

What historical data actually looks like

A single day's OHLCV is one data point. String together 10 years of daily OHLCV for 500 stocks, and you have the raw material to build and test almost any systematic strategy.

This is the raw material behind every RupeeCase strategy. A rule like "hold the top 50 momentum stocks of the Nifty Total Market, rebalance every two weeks" is tested by looping through years of daily closing prices, simulating every buy and sell, and charging costs on every trade. The output is a model, back tested record, and Module 2.4 shows you how to read one without fooling yourself.

This is the moment that changed how I thought about investing. You don't have to guess. You don't have to trust tips or follow your gut. You can test a strategy on real historical data. That's the difference between systematic investing and gut-feel investing, one uses evidence, the other uses hope.

Adjusted vs unadjusted prices

This trips up a lot of people building their first strategies. Companies occasionally do things that change their share price without any real change in value: stock splits, bonus shares, rights issues. If INFYInfosys did a 2-for-1 split, the price would halve overnight. But you'd own twice as many shares, so nothing actually changed.

If you don't account for this in historical data, your backtest shows a 50% crash in one day. That's an unadjusted price series.

Adjusted prices retroactively scale all historical prices as if the split had always been in effect. BSE and NSE both publish corporate action data so this adjustment can be done cleanly.

A worked example: the HDFC Bank bonus of August 2025

Here is a real one. HDFC Bank issued a 1:1 bonus, one new share for every share held, with an ex date of 26 August 2025. Pull the raw NSE closing prices and this is what you get.

Source: NSE bhavcopy closing prices and NSE corporate action data (bonus 1:1, ex date 26 Aug 2025, adjustment factor 0.5).

The adjustment is simple. Every price before the ex date is multiplied by 0.5. A shareholder with 100 shares worth ₹1,96,410 on 25 August woke up with 200 shares worth ₹1,94,680. Nothing happened to their wealth except a normal 0.9% move. A momentum model fed the raw series would have screamed sell. A low volatility model would have flagged HDFC Bank as the most volatile stock in the Nifty that week. Both wrong, both because of one missing multiplication.

Dividends are the quieter version of the same problem. On an ex dividend date the price drops by roughly the dividend. HDFC Bank went ex dividend at ₹22 a share on 27 June 2025. Ignore dividends for long enough and a high dividend stock looks worse than it was. That is why serious comparisons use total return indices, which put dividends back in. Module 1.3 covers those.

Common mistakes when reading stock data

How this shows up in RupeeCase

Every RupeeCase strategy page shows a model, back tested history built from adjusted NSE closing prices, with costs charged at each rebalance. The Nifty 50 Equal Weight page is the easiest place to see it: one line, built from the closes of 50 stocks, rebalanced every four weeks. When a rebalance runs, the order list is worked out from end of day data, never from a mid day quote.