---
title: "What Is Historical Volatility (HV)?"
description: "While Implied Volatility measures expected future movement, Historical Volatility (HV) measures how much a stock actually moved in the past."
author: "Adrian Rosebrock"
date: 2026-05-11
lastmod: 2026-05-11
canonical: https://wheelmetrics.io/blog/what-is-historical-volatility/
image: https://wheelmetrics.io/blog/what-is-historical-volatility/header.jpg
categories: ["Options Fundamentals"]
---

> For the complete WheelMetrics content index, see [llms.txt](https://wheelmetrics.io/llms.txt). This is the Markdown edition of https://wheelmetrics.io/blog/what-is-historical-volatility/.

# What Is Historical Volatility (HV)?

By Adrian Rosebrock · Last updated May 11, 2026 · 11 min read

**Historical volatility (HV) measures how much a stock's price _actually moved_ over a past period, expressed as an annualized percentage.**

Let's say you just found a stock with 60% IV and fat premiums. 

You're considering selling a CSP and collecting that premium.

**But is that IV _actually high_ for this stock?**

How do you know?

_Realistically, you can't answer that without historical volatility._

If implied volatility is the weather forecast, historical volatility is the past 30 days of recorded weather. 

One is a prediction. 

The other is the truth.

Essentially, HV is backward-looking, based on real price data, and gives you the baseline for judging whether implied volatility (and the premiums you're collecting) are justified by reality.

My [previous article on implied volatility](https://wheelmetrics.io/blog/what-is-implied-volatility/) covered the market's forecast (i.e., what the market _expects_ to happen).

Now we look at the other side: what the stock actually did.

If you want the full learning path, this article is part of [Options Fundamentals: The Complete Guide](https://wheelmetrics.io/blog/options-fundamentals-complete-guide/).

**Table of Contents**

- [What Is Volatility? A Quick Recap](https://wheelmetrics.io/blog/what-is-historical-volatility/#what-is-volatility-a-quick-recap)
- [What Is Historical Volatility (HV)?](https://wheelmetrics.io/blog/what-is-historical-volatility/#what-is-historical-volatility-hv)
  - [HV Lookback Periods (1 Month, 3 Months, 1 Year)](https://wheelmetrics.io/blog/what-is-historical-volatility/#hv-lookback-periods-1-month-3-months-1-year)
  - [When HV Windows Diverge (A Real-World Example)](https://wheelmetrics.io/blog/what-is-historical-volatility/#when-hv-windows-diverge-a-real-world-example)
  - [What HV Means in Dollar Terms](https://wheelmetrics.io/blog/what-is-historical-volatility/#what-hv-means-in-dollar-terms)
- [How Is Historical Volatility Calculated?](https://wheelmetrics.io/blog/what-is-historical-volatility/#how-is-historical-volatility-calculated)
  - [The Math Behind Historical Volatility](https://wheelmetrics.io/blog/what-is-historical-volatility/#the-math-behind-historical-volatility)
- [Why Historical Volatility Matters for Wheel Traders](https://wheelmetrics.io/blog/what-is-historical-volatility/#why-historical-volatility-matters-for-wheel-traders)
- [Where to Go from Here](https://wheelmetrics.io/blog/what-is-historical-volatility/#where-to-go-from-here)

## What Is Volatility? A Quick Recap

I covered volatility in depth in the [Implied Volatility article](https://wheelmetrics.io/blog/what-is-implied-volatility/), so I'll keep this brief.

**As Wheel traders, volatility is what we get paid for.** It's the size of a stock's price swings, and bigger swings mean fatter premiums.

The key thing to internalize is that volatility isn't inherently good or bad. It's a _measurement_, like a thermometer reading. A high reading doesn't tell you whether to be excited or worried. Context does.

What matters is whether the volatility you're being _compensated_ for (through premium) is justified by the volatility the stock _actually exhibits_.

And that's exactly the question HV answers.

## What Is Historical Volatility (HV)?

**HV measures how much a stock actually moved over a past period, expressed as an annualized percentage.**

It's backward-looking, based on real price data, not market expectations.

HV is on the same scale as IV (annualized percentage), so you can compare them directly. That's the whole point.

### HV Lookback Periods (1 Month, 3 Months, 1 Year)

![ADBE chart with 1-month, 3-month, and 1-year historical volatility overlaid](https://wheelmetrics.io/blog/what-is-historical-volatility/adbe-hv-chart.png)

Not all HV is created equal. The lookback window you choose will tell you a very different story:

- **1 month (20 trading days):** Captures recent, short-term price action; most reactive to sudden moves
- **3 months (60 trading days):** Smooths out short-term noise; shows the medium-term trend
- **1 year (252 trading days):** The long-term baseline; shows what "normal" looks like for this stock

Above is what that looks like in practice with `ADBE` (Adobe).

Three HV lines, same stock, very different stories:

- The **1M HV (pink)** swings wildly, ranging from roughly 18% to 66%. When `ADBE` had a rough week, that pink line shot up. When things calmed down, it plummeted. Reactive, borderline twitchy, like a novice trader attempting to trade 10 minute candles.
- The **3M HV (green)** moderates those swings, settling into a range of about 25% to 44%. Still responsive, but it takes a sustained move (not just a bad Tuesday) to shift meaningfully.
- The **1Y HV (blue)** barely moves, holding steady between 34% and 38%. That's `ADBE`'s "long-term normal." A single volatile week won't budge it. Only a persistent shift in the stock's behavior shows up at this timescale.

**Same stock. Different windows. Different answers to the question _"How volatile is this stock?"_**

This is why experienced traders don't rely on a single lookback period. They check all three.

Think of it this way: 

- 1M HV tells you what's happening _right now_
- 1Y HV tells you what "normal" looks like
- And 3M HV sits in between, smoothing out the noise without losing the recent signal

### When HV Windows Diverge (A Real-World Example)

![SSRM chart with 1-month, 3-month, and 1-year historical volatility from March 2025 to March 2026](https://wheelmetrics.io/blog/what-is-historical-volatility/ssrm-hv-chart.png)

The `ADBE` chart above shows a stock where the three HV lines stay relatively well-behaved. The HV periods tell slightly different stories, but they're in the same neighborhood.

**Now let's look at what happens when a _real shock_ hits.**

At the top of this section is `SSRM` (SSR Mining) with the same three HV lines over the past year.

For most of 2025 (March through December), all three lines tracked close together, hovering in the 50-60% range. Normal behavior for a mining stock.

Then around February/March 2026, something changed.

All three lines began diverging _dramatically upward_. 

Here's where they sit now:

| HV Window | Current Value | What It's Telling You |
|-----------|--------------|----------------------|
| **1M HV (pink)** | ~100% | The last month has been _extreme_; the stock nearly _**doubled**_ its typical volatility |
| **3M HV (green)** | ~83% | The recent chaos is pulling up the medium-term average, but the calmer months before are still dampening the number |
| **1Y HV (blue)** | ~62% | Barely budged — the long-term baseline absorbs the shock like a cruise ship absorbs a wave |

**The 1Y HV went from ~57% to ~62% while the 1M HV went from ~55% to ~100%.** 

Same stock. Same time period. Wildly different readings depending on which window you check.

This is why you need all three.

If you only looked at the 1Y HV, you'd think `SSRM` was behaving mostly normally (a little elevated, nothing dramatic). If you only looked at the 1M HV, you'd think the stock was in full meltdown mode.

**The truth lives in the _relationship_ between the windows.** When 1M HV is dramatically above 1Y HV, something unusual is happening _right now_, but the stock's long-term character hasn't fundamentally changed (yet).

**As Wheel traders, when wee see 1M HV significantly above 1Y HV, _we get curious._**

We're intrigued.

_We see opportunities for fat premiums._

But we have to slow down and keep ourselves in check.

We have to ask ourselves:

_"Why is IV so elevated?"_

The answer to that question is the difference between cashing in on a sweet payday...

...or getting assigned on a stock that tanks 40%.

_(For the curious: `SSRM` is a silver and gold miner, and the mining sector has been dealing with **significant** gold macro volatility, dollar strengthening, and bond yield pressure due to the Iran War. Essentially, similar dynamics to what I discussed in the [IV article](https://wheelmetrics.io/blog/what-is-implied-volatility/) with other mining names.)_

### What HV Means in Dollar Terms

Abstract percentages are hard to feel. Let's convert `SSRM`'s 1Y HV into something tangible:

- `SSRM` is currently trading at $22.72
- From the above chart, we know 1Y HV is ~62%
- Daily standard deviation: 62% / sqrt(252) = ~3.9%
- On a $22.72 stock: 3.9% x $22.72 = ~$0.89 per day

**A 62% annualized HV means `SSRM` typically moves about $0.89 per day based on the past year of data.**

Now you can _feel_ the number.

That daily number is a one-standard-deviation move, meaning `SSRM` stays within that range on roughly two-thirds of trading days.

On the other third, it moves _more_ than $0.89. 

_Some days, much more._

**This is what makes HV practical. It converts a percentage that lives on a chart into a dollar amount that lives in your brokerage account.**

Now here's where it gets interesting for premium sellers.

Let's play out two hypothetical IV scenarios for `SSRM`, given what we know about its HV windows (1M ~100%, 3M ~83%, 1Y ~62%).

#### Scenario A: Current IV at 85%

The current IV is sitting at 85%.

Your first instinct might be to think that's _high_. 

And compared to the 1Y HV of 62%, it is.

**But look at the 1M HV: ~100%.** 

An 85% IV is actually _below_ what the stock has done over the past month. 

The market is saying, _"Yes, we expect elevated volatility, but things are going to calm down from recent levels."_

That's not an "oh shit" signal. That's the market pricing in a _deceleration_.

#### Scenario B: IV (Hypothetical) at 130%

Now let's suppose the current IV is at 130%.

Now the market is pricing in _more_ movement than even the recent frenzy. 

A current IV at 130% would be above every HV window: 1M, 3M, _and_ 1Y.

**The market isn't just saying "things are volatile." It's saying "you haven't seen the worst of it yet."**

Maybe there's an acquisition rumor. Maybe there's a mine disaster. Maybe gold just cratered and `SSRM`'s balance sheet is in question.

Whatever the reason, 130% IV on a stock with 100% 1M HV means the market expects things to get _worse_, not better.

That premium looks fat for a reason. And that reason might eat your account.

**Same stock. Same HV. Two very different IV readings. Two very different risk profiles.**

Without the multi-window HV comparison, both scenarios just look like "high IV."

We'll cover exactly how to use [the gap between IV and HV](https://wheelmetrics.io/blog/implied-vs-historical-volatility/) for trade selection in the next article.

## How Is Historical Volatility Calculated?

![Calculation](https://wheelmetrics.io/blog/what-is-historical-volatility/calculation.jpg)

You don't need to memorize this. But understanding the intuition helps you trust the number.

HV is calculated in three conceptual steps:

1. **Compute daily percentage returns** to determine how much did the stock move today vs. yesterday, in percentage terms
2. **Take the rolling standard deviation** of those daily returns over a lookback window (20, 60, or 252 days) — this captures the spread of daily moves
3. **Annualize by multiplying by the square root of 252 (trading days in a year)**, thereby converting the daily measure to an annual percentage so it's on the same scale as IV

That's it. Daily returns, standard deviation, annualize.

Why sqrt(252)? Standard deviation measures dispersion in whatever time unit you feed it. Feed it daily returns, you get a daily number. Multiplying by sqrt(252) scales that daily dispersion up to an annual number, which puts HV on the same scale as IV.

**The sqrt(252) step is what lets you compare HV and IV apples-to-apples.**

### The Math Behind Historical Volatility

For the formula-curious:

- Daily return = (today's close - yesterday's close) / yesterday's close
- HV = standard deviation of daily returns over N days x sqrt(252)
- Example: 20-day HV = standard deviation of the last 20 daily returns x sqrt(252)

The standard deviation step is doing the heavy lifting. It measures how _spread out_ those daily returns are.

A stock that consistently moves 0.5% per day has a small standard deviation. A stock that swings between -4% and +5% has a large one.

**You don't need to do this yourself.**

Most traders find HV in their brokerage platform or pay for a service that computes it. 

As a quant investor, I compute it myself through code I've written...but you don't need to.

**Understanding the intuition matters. Memorizing the formula doesn't.**

_(Though if you're the type who opens a spreadsheet for fun on a Saturday night...no judgment. I've been there.)_

## Why Historical Volatility Matters for Wheel Traders

![Thinking](https://wheelmetrics.io/blog/what-is-historical-volatility/thinking.jpg)

**HV is the reality check on IV.**

It's like checking last month's actual temperatures before deciding if the weather forecast seems reasonable.

Without HV, you're flying blind on whether premiums are justified.

For example:

Could I have sold a lot more premium before I started checking HV? Absolutely. But I also would have walked into setups where the fat premium existed because the stock was about to implode, not because I found an edge.

HV gives you three practical things as a Wheel trader:

1. **Context for premium levels:** Is IV (and the premium you're collecting) justified by how the stock actually behaves, or is the market pricing in something unusual?
2. **A baseline for spotting anomalies:** When the market is pricing in significantly more (or less) movement than history suggests, that's a signal worth investigating
3. **A multi-timeframe view:** Comparing 1M, 3M, and 1Y HV on the same stock tells you whether recent volatility is a blip or a trend

**The full framework for using HV and IV together to select better trades lives in the next article.**

## Where to Go from Here

HV is backward-looking. It tells you what a stock _actually did_, not what the market expects:

- Without HV, every high-IV stock looks like an opportunity
- With HV, you can distinguish between IV that's slightly elevated (routine) and IV that's double the historical norm (something sketchy is going on)

**That distinction is everything.**

The next step is [IV and HV: Using Volatility to Select Better Wheel Trades](https://wheelmetrics.io/blog/implied-vs-historical-volatility/), which walks through the practical framework for using both together.

For a refresher on how implied volatility drives premium levels and how to interpret the market's forecast, see my guide on [implied volatility](https://wheelmetrics.io/blog/what-is-implied-volatility/).

## Frequently Asked Questions

**What is historical volatility (HV)?**

Historical volatility (HV) measures how much a stock's price actually moved over a past period, expressed as an annualized percentage. It's backward-looking, based on real closing price data, and gives you a baseline for judging whether implied volatility and options premiums you're collecting are justified.

**How is historical volatility calculated?**

HV is calculated in three steps: (1) compute daily percentage returns from closing prices, (2) take the rolling standard deviation of those returns over a lookback window (20, 60, or 252 trading days), (3) annualize by multiplying by the square root of 252. This converts the daily measure to an annual percentage on the same scale as IV.

**What is a good historical volatility number?**

There is no universal 'good' HV number. HV is relative, not absolute. A 40% HV might be normal for a volatile mining stock but extremely elevated for a blue-chip utility. Compare HV to the stock's own history and to its current implied volatility to determine whether conditions are typical or unusual.

**What is the difference between implied volatility and historical volatility?**

Implied volatility (IV) is forward-looking: the market's forecast of how much a stock will move. Historical volatility (HV) is backward-looking: how much the stock actually moved based on real price data. IV is derived from option prices. HV is derived from stock closing prices. Both are expressed as annualized percentages so you can compare them directly.

**What lookback period should I use for historical volatility?**

Most traders check all three standard lookback periods. 1-month (20-day) HV captures recent short-term action and reacts fastest to sudden moves. 3-month (60-day) HV smooths out noise and shows the medium-term trend. 1-year (252-day) HV provides the long-term baseline of what 'normal' looks like for a given stock.

**Does high historical volatility mean a stock is risky?**

Not necessarily. High HV means the stock has made larger price swings historically. For options sellers, higher HV often translates to higher premiums. Risk depends on context — a stock with high HV that you've researched thoroughly and would happily own is very different from a stock with high HV driven by potential bankruptcy.

**Why do Wheel traders care about historical volatility?**

HV provides the reality check on implied volatility. Without HV, you can't tell if a stock's IV (and the premiums you're collecting) are justified by how the stock actually behaves. The same IV number tells a very different story depending on whether HV is close to IV or far below it.


## About the author

**Adrian Rosebrock**, Founder, WheelMetrics. Hi there, I'm Adrian Rosebrock, PhD. I believe trading and investing should be systematic, not speculative. I built WheelMetrics to share the quantitative research and frameworks behind my Wheel Strategy process. My goal is to help you make smarter, more confident trading decisions. [Connect on LinkedIn](https://www.linkedin.com/in/adrian-rosebrock/)


## Disclaimer

WheelMetrics is an educational resource, not financial advice. WheelMetrics is not a registered investment advisor, broker-dealer, or financial planner. Everything here, including articles, newsletters, stock screening results, options setups, market commentary, is for educational and informational purposes only. Options trading carries substantial risk, and you can lose some or all of your capital. You're solely responsible for your own investment decisions. Consult with a qualified financial advisor before making any trades.


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*WheelMetrics content is educational and is not individualized financial advice. Source: https://wheelmetrics.io/blog/what-is-historical-volatility/*