TSLA Historical Volatility: The Real Numbers

Tesla Is One of the Most Volatile Mega-Caps Ever

Even after years in the S&P 500, Tesla has a volatility profile closer to a small-cap biotech than a large-cap staple. Over 2016-2026, Tesla's average daily range has been roughly 4.1% of the prior close — about 2.5x the SPY range and notably wider than NVDA. Realized 30-day volatility has averaged around 55% annualized, with peaks above 120% during the 2020 rally and troughs near 30% during quieter stretches of 2023.

For perspective, a 55% annualized volatility means a typical daily move around 3.5%, and a 1-standard-deviation monthly move around 16%. That's a lot of motion for a trillion-dollar company.

• Average daily range 2016-2026: ~4.1% of prior close
• Median daily range: ~3.4% of prior close
• Average 30-day realized volatility: ~55% annualized
• Highest 30-day realized volatility: ~120%+ (2020)
• Lowest 30-day realized volatility: ~28% (mid-2023)

The Tails Are Enormous

Tesla's single-day move distribution is one of the most fat-tailed in the S&P 500. The largest single-day gains include the roughly +20% moves tied to Q3 2019 earnings, the inclusion in the S&P 500 in 2020, and multiple +10% to +15% days during the 2020-2021 rally. The largest single-day losses include roughly -18% moves tied to Q1 2022 selling and a series of -12% days during the 2022 drawdown.

On a 55% annualized volatility, a normal distribution would predict roughly 0-1 days per year with moves exceeding 9%. Tesla has averaged about 8-10 such days per year. The tails are roughly 10x fatter than a normal distribution would suggest — a reminder that option pricing models assuming lognormal returns will systematically mis-price Tesla tail events.

Volatility Regimes and Forward Returns

Splitting Tesla's history by volatility quartile reveals a clear pattern. When 30-day realized volatility is in the bottom quartile (below ~35%), Tesla's forward 20-day return has averaged roughly +3.8% with a 62% win rate. When volatility is in the top quartile (above ~75%), forward returns have averaged roughly -0.5% with a 49% win rate.

This is a classic 'buy calm' effect. Periods of low realized volatility are often periods of accumulation or consolidation, and they tend to precede positive drift. High-volatility periods, by contrast, are often chaotic and mean-reverting, with no reliable directional edge.

Volatility Autocorrelation Is High

Like NVDA and most other stocks, Tesla exhibits strong volatility clustering. The autocorrelation of daily absolute returns is roughly 0.32 at lag 1 — even higher than NVDA's 0.25 — and stays positive out to about lag 15. This means today's volatility is a meaningful predictor of tomorrow's, and position sizing should reflect that.

Traders running risk-parity or volatility-scaled strategies on Tesla should update their sizing at least weekly, if not daily. Using a static volatility estimate (such as the long-run 55% number) will lead to dramatic over-sizing during calm periods and under-sizing during stress periods.

How to Use This in Practice

If you're trading Tesla, the single most useful adjustment you can make is scaling position size by realized volatility. A $10,000 position in Tesla during a 30% volatility regime is roughly equivalent in dollar-risk to a $5,500 position during a 55% regime, and a $3,600 position during an 85% regime.

Chart Library's API makes it easy to check the current volatility regime alongside the pattern intelligence:

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

For broader context, see our post on market regime tracking — Tesla's volatility is heavily regime-dependent, and knowing the macro context helps calibrate expectations.