---
title: "Historical vs implied volatility: what each measures"
description: "What historical, realised and implied volatility each measure, how India VIX and the option chain fit in, and why they differ, on dated NSE Nifty data."
source_url: "https://www.rupeecase.com/learn/path-16/module-16-1-historical-vs-implied-volatility"
---

[Path 16 1 of 16](/learn/path-16/)Volatility: historical against implied[Next 16.2](/learn/path-16/module-16-2-india-vix-explained)

Wednesday 10 Jun 2026. India VIX closed at 15.63. The at the money implied volatility of the 30 Jun Nifty options read 15.03, and a constant 30 day version of it read 14.88. The index had realised 10.30 over the twenty sessions before, and went on to realise 13.65 over the twenty after. All five are percent a year. Three agreed. One sat far below them. One arrived later and landed in between. I use "historical" for a number measured on past returns, and "realised" for the window that follows the day an option was priced. Every figure here comes from NSE end of day files, so nothing is live and nothing is a view on where the index goes next.

3By the end you can

1. Say what historical, realised and implied volatility each measure, and over what window.
2. Read implied volatility as an option price in volatility units, by strike and by expiry.
3. Explain why a high or low implied volatility needs a named yardstick.

Watch in the terminal: how bumpy was the ride? A short tutorial on sample data.

## The idea, plainly

Volatility is how far and how fast the index moves, quoted as a yearly percentage. It is the standard deviation of the index's returns, scaled to a year. Fifteen percent a year means the index lands within fifteen percent of where it started, up or down, in about two years out of three.

Read 6 more paragraphs, 425 words
**Historical volatility looks back.** Take the daily returns of the last few sessions, find their standard deviation, and multiply by the square root of the trading days in a year, about 252. The window is a choice. A ten session figure and a sixty session figure for the same index on the same day differ, because they hold different days. The realised series in this lesson uses twenty sessions, close to close. The [question page](/learn/questions/historical-implied-realised-volatility) sets the three names side by side.

**Implied volatility looks forward, or seems to.** The [question page](/learn/questions/what-is-implied-volatility) has the two line version. Put an option's price into the pricing model and solve for the volatility that returns it. That number is the implied volatility. It is a price written in volatility units. It holds the market's guess at movement and a premium for the risk of being wrong, and the price alone cannot separate the two.

The rule of sixteen turns a yearly figure into a day. Divide by sixteen, which is close to the square root of the trading days, and you have a rough one standard deviation move per session. At 15.0% on a Nifty of 23,214.95, that is about 220 points.

Why do the two differ? Historical volatility is a fact about the past. Implied volatility is a price about the future, and a price carries a margin, much as an insurance premium does. Studies of equity index options find that the price tends to sit a little above the volatility that follows, and the chart below shows the same shape on most days. That describes an average. The average hides the days it fails, and one of them is in the example.

Each has a job. Historical volatility is the yardstick that says how the index behaved. Implied volatility puts every option on one scale, because it divides out the index level, the strike and the days left. That is how you can compare a weekly with a monthly, or one strike with another, without comparing rupees.

Implied volatility also changes with the strike and the expiry, not only with the day. A chain prints one for every option. A broker's screen may add an IV percentile, the share of days in a past window when implied volatility was lower than today's, and an IV rank, which says where today sits between the window's low and high. Check the window and the series before comparing two screens. The [question page](/learn/questions/iv-and-ivp-in-option-chain) covers the chain screen, and the [IV rank and percentile module](/learn/path-16/module-16-4-iv-rank-and-iv-percentile) takes both apart.

## Worked example: one evening and one shock

Back to 10 Jun 2026, with the five numbers side by side.

Three numbers priced the move, two measured it

The first three read option prices on 10 Jun 2026. The last two are the realised volatility of the twenty sessions before and the twenty after, close to close. Source: NSE end of day data, computed by RupeeCase. As of 9 Jul 2026.
Implied sat above realised on most sessions, and below it after the big moves of early 2026

Percent a year. Implied is computed by RupeeCase from NSE settlement prices of the two nearest monthly expiries, blended to thirty days. Realised is the close to close volatility of the last twenty sessions. Source: NSE end of day data, computed by RupeeCase. As of 30 Jun 2026.
After a sharp fall, near expiries priced far more movement than far ones

At the money implied volatility by expiry on 7 Apr 2025, for every Nifty expiry out to the June monthly. At the money is read at the future for monthlies and at the parity forward for weeklies. Source: NSE end of day data, computed by RupeeCase. As of 7 Apr 2025.
Read 3 more paragraphs, 257 words
The three that agree are built differently. India VIX comes from a strip of out of the money options on the near and next month. The other two read the at the money strikes. That is why they differ by a little. Now the gap that matters. Implied sat 4.58 points above the twenty sessions behind it. The twenty sessions ahead came in at 13.65, closer to implied but still 1.23 points under it. The backward number said calm. The forward number said less calm. Neither was wrong. They hold different days, and the index had been quiet for a month before it moved more.

Over a longer stretch, the implied line sits above the realised line on most sessions and dips below it after big moves. Look at 8 Apr 2026. The index rose 3.8% in a day, from 23,123.65 to 23,997.35. India VIX fell from 24.70 to 19.70. The twenty day realised volatility rose from 26.04 to 29.46, because the big day had just entered the window. One measure read the scare fading. The other averaged it in.

Expiry matters as much as the day. The close of 7 Apr 2025 followed a sharp fall, and India VIX closed at 22.79. The two day weekly options priced 46.7% a year and the monthly with fifty two days to run priced 19.7%. Same index, same evening, two different prices of movement. The near dated options carried the fear. The [India VIX module](/learn/path-16/module-16-2-india-vix-explained) and its [question page](/learn/questions/what-is-india-vix) cover the index itself.

## The common mistake

The claim: When implied volatility is high, options are expensive, and when it is low, they are cheap. High against what? Against the index's own history, which is what rank and percentile say. Against the volatility that follows, which only hindsight can grade. The two yardsticks disagree. On 8 Apr 2026 the 30 day implied volatility was 17.56, far below the twenty session realised figure of 29.46, which looks cheap. But that realised number was carrying a shock that was over. Name the yardstick before you use the word.

## Key takeaways

* Historical volatility looks back at returns. Implied volatility reads an option price.
* Implied volatility is a price in volatility units, not a forecast.
* Divide a yearly volatility by sixteen for a rough one day move.
* Different windows give different historical figures. Say which window.
* Implied volatility changes with the expiry as well as the strike.
* High or low needs a yardstick: the past, or what follows.

**Before you trade.** Derivatives trading carries a high risk of loss. SEBI's study "Profitability of Individual Traders in the Equity Derivatives Segment (FY25 to FY26)" (August 2026) found that 87.7% of individual traders in equity F&O made net losses in FY26, with aggregate net losses of Rs 91,685 crore. [Read the SEBI study](https://www.sebi.gov.in/reports-and-statistics/research/aug-2026/study-profitability-of-individual-traders-in-the-equity-derivatives-segment-fy25-fy26-_103835.html)

What does Volatility: historical against implied cover?Two numbers called volatility, one from past returns and one from a price. What each measures, and why they differ. It works through The idea, plainly, Worked example: one evening and one shock, The common mistake, Key takeaways. It is module 16.1 of Path 16, Volatility, about 7 minutes of reading, free.

TTry it

## IV rank and percentile, on the same example.
Both definitions side by side on a dated series. Dated NSE end of day data, nothing live, no orders.

**IV rank and percentile**.

[Open the iv rank and percentile](/learn/tools/iv-rank-percentile?series=nifty-atm-iv-30d)

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QQuick check

## 10 questions, 7 to pass.
Each attempt draws 10 of the 15 questions in this module's bank, and a retake draws a fresh set. A pass gives this module's Certificate of Completion. Your result stays on this device and counts towards the Path 16 certificate.

7 of 10 correct passes module 16.1

Every answer is explained when you check; a retake is always free. Source: RupeeCase Learn quiz rules (70% to pass).

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CCheck yourself

## Path 16 so far.
Your quick check results on this device, stop by stop.

Stop 1 of 16 on Path 16

Volatility: every live stop, this module ringed. Source: RupeeCase Learn, Path 16.

1. [16.1Volatility: historical against impliedNot yet](/learn/path-16/module-16-1-historical-vs-implied-volatility#quiz)
2. [16.2India VIX for beginners: what it measures and what it does notNot yet](/learn/path-16/module-16-2-india-vix-explained)
3. [16.3Solving for implied volatilityNot yet](/learn/path-16/module-16-3-solving-for-implied-volatility)
4. [16.4IV rank and IV percentile, done properlyNot yet](/learn/path-16/module-16-4-iv-rank-and-iv-percentile)
5. [16.5Measuring realised volatility: four estimatorsNot yet](/learn/path-16/module-16-5-realised-volatility-estimators)
6. [16.6Events and IV crush: results, Budget, RBI and electionsNot yet](/learn/path-16/module-16-6-iv-crush-around-events)
7. [16.7Smile and skew: a first look at Nifty and stocksNot yet](/learn/path-16/module-16-7-volatility-smile-and-skew)
8. [16.8Skew measures: risk reversal, butterfly and slopeNot yet](/learn/path-16/module-16-8-skew-measures)
9. [16.9Term structure and event varianceNot yet](/learn/path-16/module-16-9-term-structure-and-event-variance)
10. [16.10Forward volatility from two expiriesNot yet](/learn/path-16/module-16-10-forward-volatility)
11. [16.11India VIX rebuilt step by stepNot yet](/learn/path-16/module-16-11-india-vix-rebuilt)
12. [16.12Forecasting volatility: EWMA, GARCH and HARNot yet](/learn/path-16/module-16-12-forecasting-volatility)
13. [16.13The variance risk premium in NiftyNot yet](/learn/path-16/module-16-13-variance-risk-premium)
14. [16.14Variance swaps and replicationNot yet](/learn/path-16/module-16-14-variance-swaps)
15. [16.15Volatility surface models: SVI, SABR, local and stochastic volNot yet](/learn/path-16/module-16-15-volatility-surface-models)
16. [16.16Skew dynamics: sticky strike against sticky deltaNot yet](/learn/path-16/module-16-16-skew-dynamics)
17. [TPath test, 30 questionsNot yet](/learn/path-16/module-16-16-skew-dynamics#pathTestSection)

Path 16 in reading time: 159 minutes over 16 modules

Minutes of reading per module, this one in amber. Source: RupeeCase Learn, Path 16.

    Explore next

## Put the module to work.

* [ToolOption payoff builderLegs on a dated Nifty chain, breakevens and charges](/learn/tools/payoff-builder)
* [TutorialSharpe and volatility: how bumpy was the ride?0:54 video, Advanced](/learn/terminal/sharpe-and-volatility)
* [Free module 16.2India VIX for beginners: what it measures and what it does not8 min read](/learn/path-16/module-16-2-india-vix-explained)
* [Free module 16.3Solving for implied volatility9 min read](/learn/path-16/module-16-3-solving-for-implied-volatility)
* [Free module 16.4IV rank and IV percentile, done properly9 min read](/learn/path-16/module-16-4-iv-rank-and-iv-percentile)
* [Free module 16.5Measuring realised volatility: four estimators9 min read](/learn/path-16/module-16-5-realised-volatility-estimators)

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SSources

## Go to the source.
5 sources, NSE the most cited

The publisher of each source listed below. Source: Module 16.1 source list.
1. [NSE, India VIX: what it measures and how it is computed](https://www.nseindia.com/static/products-services/indices-indiavix-index) NSE
2. [NSE, India VIX white paper (PDF)](https://nsearchives.nseindia.com/web/sites/default/files/inline-files/white_paper_IndiaVIX.pdf) NSE
3. [NSE, option chain (Nifty 50 index options)](https://www.nseindia.com/option-chain) NSE
4. [Carr, P. and Wu, L. (2009), Variance Risk Premiums, Review of Financial Studies](https://ideas.repec.org/a/oup/rfinst/v22y2009i3p1311-1341.html) Paper
5. Hull, J., Options, Futures, and Other Derivatives, Pearson (volatility and implied volatility) Book

GTerms

## 5 terms from this module.
Historical volatilityThe annualised standard deviation of past daily returns over a stated window, such as twenty sessions.
Realised volatilityVolatility measured on returns that have happened. This school keeps the word for the window after an option was priced.
Implied volatilityThe volatility that, put into an option pricing model, returns the option's market price. A price in volatility units.
India VIXNSE's volatility index, built from Nifty option prices. It shows the volatility priced for the next thirty calendar days, as a yearly percentage.
IV percentileThe share of days in a past window when implied volatility was lower than today's. It counts days and does not use the high or the low.
[All 230 terms in the glossary](/learn/glossary)

[Question people askWhat do IV and IVP mean in the option chain?A short answer with a dated chart](/learn/questions/iv-and-ivp-in-option-chain)[Question people askWhat is implied volatility?A short answer with a dated chart](/learn/questions/what-is-implied-volatility)[Related module16.2 India VIX for beginners: what it measures and what it does not8 min, Beginner](/learn/path-16/module-16-2-india-vix-explained)[Related module16.3 Solving for implied volatility9 min, Intermediate](/learn/path-16/module-16-3-solving-for-implied-volatility)[Pillar guideDerivatives and Quant115 modules across paths 12 to 19](/learn/derivatives)

Education only, not investment advice, a research report or a recommendation to buy, sell or hold any security. RupeeCase (QC Alpha Technologies Pvt Ltd) is not registered with SEBI as an investment adviser or research analyst. Contracts and prices shown are for illustration only, come from NSE end of day files at least 30 days old, and are not recommendatory. Derivatives trading carries a high risk of loss.