AMD Historical Volatility: What the Numbers Say

AMD Is a High-Vol Mega-Cap

AMD's volatility profile sits between Apple's moderate calm and Tesla's extreme chaos. Over 2016-2026, AMD's average daily range has been roughly 3.3% of the prior close — similar to NVDA and noticeably higher than the broader S&P. Realized 30-day volatility has averaged around 45% annualized, with peaks above 80% during the 2020 crash and 2022 selloff, and troughs near 25% during quiet stretches.

AMD is historically more volatile than AAPL, less volatile than TSLA, and roughly comparable to NVDA. Over the past decade, its volatility has trended slightly lower as the company has grown and institutionalized — but it remains firmly in the 'high-vol mega-cap' bucket.

• Average daily range 2016-2026: ~3.3% of prior close
• Median daily range: ~2.8% of prior close
• Average 30-day realized volatility: ~45% annualized
• Highest 30-day realized volatility: ~85% (March 2020)
• Lowest 30-day realized volatility: ~24% (mid-2023)

The Tails: Fat, Especially on the Upside

AMD's single-day move distribution shows noticeably fat tails. The largest single-day gains include the roughly +23% move after Q4 2017 earnings and several +15% to +20% moves during the 2020-2021 and 2023-2024 rally cycles. The largest declines include roughly -18% moves during the Q2 2022 semiconductor selloff and the March 2020 crash.

On a typical year, AMD has averaged roughly 5-6 days with moves exceeding 8%. That's more than NVDA (4-5) and much more than Apple (1-2), though less than Tesla (8-10). For option traders, this matters: AMD's implied vol surface tends to under-price the tails relative to realized behavior.

Volatility Regimes and Forward Returns

Conditioning on volatility regime reveals the familiar 'buy calm' effect. In the bottom quartile of 30-day realized vol (below ~30%), AMD's 20-day forward return has averaged roughly +3.3% with a 63% win rate. In the top quartile (above ~60%), forward returns have averaged roughly +0.2% with a 52% win rate.

This is nearly identical in structure to what we see on NVDA and TSLA. Low-volatility periods on growth names are associated with accumulation and positive drift; high-volatility periods are associated with chop and uncertainty.

Volatility Clustering Is Strong

AMD's volatility shows high autocorrelation in daily absolute returns — roughly 0.28 at lag 1, and positive out to about lag 12. This is classic volatility clustering: high-vol days tend to cluster together, and low-vol days tend to cluster together.

The practical implication: don't size AMD positions based on long-run average volatility. Use recent realized volatility (e.g., the trailing 10 days) and scale position size inversely. During a 70% volatility regime, your AMD position should be roughly half the size it would be during a 35% regime to maintain equivalent dollar-risk.

Using the Data

For AMD position sizing, the most useful inputs are: current 30-day realized volatility, current VIX level (as a macro regime proxy), and the forward-return distribution of historical analogs with similar patterns. Chart Library's API returns the last of these directly:

curl -H "X-API-Key: cl_..." \ "https://chartlibrary.io/api/v1/intelligence?symbol=AMD&include_volatility=true"

Related reading: our posts on NVDA historical volatility and stock chart analysis beginners guide cover volatility concepts more broadly.