NVDA vs GOOG: Stock Returns, Risk & Volatility (2025)

Written by Gale Finance Team

Reviewed by Sid Kalla CFA Charterholder

Analysis period: 2025-01-01 to 2025-12-31

NVDA Total Return

↑ +34.9%

GOOG Total Return

↑ +65.3%

Relative Performance of NVDA vs GOOG (Normalized to 100)

NVDA GOOG

Normalized to 100 at start date for comparison

Key Takeaways

Total Return: NVDA delivered a +34.9% total return, while GOOG returned +65.3% over the same period. GOOG outperformed on total returns.
Risk-Adjusted Return (Sharpe Ratio): GOOG had a higher Sharpe (1.62 vs 0.77), indicating better risk-adjusted performance.
Volatility (Annualized): NVDA was more volatile, with 49.6% annualized volatility, versus 32.0% for GOOG.
Maximum Drawdown: GOOG's maximum drawdown was -29.3%, while NVDA experienced a deeper drawdown of -36.9%.
Tail Risk (VaR & Expected Shortfall): At the 5% level (daily log returns), NVDA's VaR was -4.62% and its Expected Shortfall (CVaR) was -7.58%; GOOG's were -2.93% and -4.29%. VaR is the cutoff; Expected Shortfall is the average move on the worst days.
Skew & Kurtosis: Skew: NVDA -0.53 vs GOOG 0.16. Excess kurtosis: NVDA 7.83 vs GOOG 3.62. Negative skew leans downside; higher excess kurtosis means fatter tails.
Tail Days & Extremes: 2σ tail days (down/up): NVDA 7/2, GOOG 6/4. Worst day: NVDA -16.97% (2025-01-27) vs GOOG -7.51% (2025-05-07). Best day: NVDA +18.72% (2025-04-09) vs GOOG +9.88% (2025-04-09).
Risk ratios: Sortino - NVDA: 1.10 vs. GOOG: 2.54 , Calmar - NVDA: N/A vs. GOOG: N/A , Sterling - NVDA: N/A vs. GOOG: N/A , Treynor - NVDA: N/A vs. GOOG: N/A , Ulcer Index - NVDA: N/A vs. GOOG: N/A

Nvidia vs Google Correlation

0.39 Average Correlation

Nvidia and Google were moderately correlated in 2025. With a correlation of 0.39, these assets showed moderate co-movement, offering some diversification when held together.

For portfolio construction, this moderate correlation offers some diversification benefit, though the assets still tend to move together during major market moves.

Metric	Value
Current (30-day)	0.36
Average (full period)	0.39
Minimum	-0.09
Maximum	0.91

Correlation measures how closely two assets move together. Values near +1 indicate strong co-movement, near 0 indicates independence, and negative values indicate inverse movement.

Investment Comparison

If you invested $10,000 in each asset on January 1, 2025:

NVDA $13,487.808 +34.9%

GOOG $16,526.138 +65.3%

Difference: $3,038.33 (GOOG ahead)

Nvidia and Google: Risk Analysis

Nvidia experienced its maximum drawdown of -36.9% from 2025-01-06 to 2025-04-04. It has not yet recovered to its previous peak.

Google experienced its maximum drawdown of -29.3% from 2025-02-04 to 2025-04-08. It has not yet recovered to its previous peak.

Smaller drawdowns and faster recoveries indicate lower downside risk and greater resilience during market stress.

Sharpe Ratio of NVDA and GOOG

NVDA Sharpe Ratio

↑ 0.77

GOOG Sharpe Ratio

↑ 1.62

Sharpe ratio measures return per unit of risk (volatility). A higher Sharpe indicates better risk-adjusted performance. GOOG had a higher Sharpe (1.62 vs 0.77), indicating better risk-adjusted performance.

A Sharpe above 1.0 is generally considered good, above 2.0 is excellent. Negative Sharpe means the asset underperformed the risk-free rate. Calculated on each asset's full 365-day lookback of available prices and annualized using the asset calendar (365 for crypto, 252 trading days for equities/ETFs/metals).

Sortino Ratio of NVDA and GOOG

NVDA Sortino Ratio

↑ 1.10

GOOG Sortino Ratio

↑ 2.54

Sortino ratio measures return per unit of downside risk. Unlike Sharpe, it only counts downside deviation (returns below the target return). GOOG had better downside-adjusted returns.

A higher Sortino is better. It's useful when upside volatility is common (crypto is the obvious example). Downside deviation: NVDA 34.9% vs GOOG 20.4%. Calculated on each asset's full 365-day lookback of available prices, using the daily risk-free rate as the target return, and annualized using the asset calendar (365 for crypto, 252 trading days for equities/ETFs/metals).

Tail Risk & Distribution Shape (2025): Nvidia vs. Google

This section looks at the shape of daily returns, not just the average. Tail stats are computed per asset on its own daily series (crypto includes weekends). We use daily log returns $\ln\left(\frac{P_t}{P_{t-1}}\right)$ so multi-day moves add cleanly.

Definitions: Value at Risk (VaR), Expected Shortfall, skew, kurtosis, and fat tails.

Metric (2025)	NVDA	GOOG
5% VaR (daily log return)	-4.62%	-2.93%
5% Expected Shortfall (CVaR)	-7.58% (worst 13 days)	-4.29% (worst 13 days)
Skew	-0.53	0.16
Excess kurtosis	7.83	3.62
2σ tail days (down / up)	7 / 2	6 / 4
Worst day	-16.97% (2025-01-27)	-7.51% (2025-05-07)
Best day	+18.72% (2025-04-09)	+9.88% (2025-04-09)

Downside co-moves (2σ) — 2025

Computed on shared dates only (n=249). A “2σ downside move” means a shared-close log return more than 2 standard deviations below that asset’s own mean on this shared-date series. Dates below show simple returns (%) for readability.

When GOOG has a big down day, NVDA also does

33.3%

2 / 6 days

When NVDA has a big down day, GOOG also does

28.6%

2 / 7 days

Show downside tail dates

Dates below are shared-date observations. The “Date” is the period end (close). Tail thresholds are computed on log returns, but the table shows simple returns (%) for readability. Returns are computed from the previous shared close to this one (for example, Friday → Monday includes weekend moves).

Days when both NVDA and GOOG had a big down day (2σ)

Date (interval)	NVDA	GOOG
2025-01-24 → 2025-01-27	-16.97%	-4.03%
2025-04-03	-7.81%	-3.92%

Days when NVDA had a big down day

Date (interval)	NVDA	GOOG
2025-01-07	-6.22%	-0.63%
2025-01-24 → 2025-01-27	-16.97%	-4.03%
2025-02-27	-8.48%	-2.57%
2025-02-28 → 2025-03-03	-8.69%	-2.07%
2025-04-03	-7.81%	-3.92%
2025-04-04	-7.36%	-3.20%
2025-04-16	-6.87%	-2.00%

Days when GOOG had a big down day

Date (interval)	NVDA	GOOG
2025-01-24 → 2025-01-27	-16.97%	-4.03%
2025-02-05	+5.21%	-6.94%
2025-03-07 → 2025-03-10	-5.07%	-4.40%
2025-03-28	-1.58%	-4.89%
2025-04-03	-7.81%	-3.92%
2025-05-07	+3.10%	-7.51%

Read this as “how ugly the ugly days get”, not as a precise forecast. One-year samples are small, so tail estimates are inherently noisy.

Full Comparison of Nvidia vs. Google (2025)

Metric	NVDA	GOOG
Total Return	+34.9%	+65.3%
Annualized Volatility	49.6%	32.0%
Sharpe Ratio	0.77	1.62
Sortino Ratio	1.10	2.54
Calmar Ratio	N/A	N/A
Sterling Ratio	N/A	N/A
Treynor Ratio	N/A	N/A
Ulcer Index	N/A	N/A
Max Drawdown	-36.9%	-29.3%
Avg Correlation to S&P 500	N/A	N/A
5% VaR (daily log return)	-4.62%	-2.93%
5% Expected Shortfall (CVaR)	-7.58%	-4.29%
Skew	-0.53	0.16
Excess kurtosis	7.83	3.62
2σ tail days (down / up)	7 / 2	6 / 4

Audit this calculation

Formulas, inputs, and conventions used to compute the metrics on this page.

Inputs & conventions

Shared window for pair metrics: 2025-01-01 → 2025-12-31 (last shared close).
Rolling correlation sample (shared closes): N/A
Annualization (days/year): NVDA: 252 days/year; GOOG: 252 days/year.
Risk-free rate: Uses the 3-month U.S. Treasury yield (FRED: DGS3MO), averaged over each asset’s window:

NVDA: 4.22%.

GOOG: 4.22%.
Volatility drag (rule of thumb): Estimated from annualized volatility (simple returns). For the log-return framing, see Log returns.

NVDA: ≈ -12.3%/yr

GOOG: ≈ -5.1%/yr
Data alignment: No forward fill. Correlation and tail co-moves are computed on shared closes only.
For cross-calendar pairs (e.g., crypto vs stocks), weekend/holiday moves roll into the next shared close.
Return conventions: Volatility/Sharpe/Sortino use simple daily returns. Tail-risk uses daily log returns for distribution stats (but tables show simple returns). Log returns.

Formulas

Daily simple return

r_t = \frac{P_t}{P_{t-1}} - 1

Volatility

\sigma_{ann} = \sigma(r_t)\sqrt{A}

Volatility drag (approx.)

\text{drag} \approx \tfrac{1}{2}\sigma_{ann}^2

Sharpe Ratio

S = \frac{A\,\bar{r} - r_f}{\sigma(r_t)\sqrt{A}}

Sortino Ratio

So = \frac{A\,\bar{r} - r_f}{\sqrt{\mathbb{E}[\min(0,\,r_t - r_f/A)^2]}\,\sqrt{A}}

Maximum Drawdown

MDD = \min_t\left(\frac{P_t}{\max_{s \le t} P_s} - 1\right)

Average Correlation

\rho = \frac{\operatorname{cov}(r^A,\,r^B)}{\sigma_A\,\sigma_B}

Log returns

\ell_t = \ln\left(\frac{P_t}{P_{t-1}}\right)

Notation

$P_t$: Price on day t.
$r_t$: Simple daily return.
$\ell_t$: Log daily return.
$\bar{r}$: Average daily return.
$\sigma(r_t)$: Standard deviation of daily returns.
$A$: Annualization factor (days/year).
$r_f$: Annual risk-free rate.

Nvidia vs Google: Frequently Asked Questions

Which had higher volatility: NVDA or GOOG?

NVDA showed higher volatility at 49.6% annualized, compared to 32.0% for GOOG During 2025. Higher volatility meant larger price swings in both directions.

Did NVDA provide diversification when held with GOOG?

NVDA and GOOG were moderately correlated in 2025, with an average correlation of 0.39. This offered some diversification benefit, though they still tended to move together during major market moves.

How bad are the worst 5% days for NVDA vs GOOG?

During 2025, NVDA's 5% VaR was -4.62% and its 5% Expected Shortfall was -7.58% (worst 13 days). GOOG's were -2.93% and -4.29% (worst 13 days).

Do NVDA and GOOG crash together on bad days?

On shared dates (n=249), when GOOG has a 2σ down day, NVDA also does 33.3% (2/6 days). In the other direction, when NVDA has one, GOOG also does 28.6% (2/7 days).

Which had better risk-adjusted returns: NVDA or GOOG?

GOOG showed better risk-adjusted performance with a Sharpe ratio of 1.62 versus NVDA's 0.77 During 2025.

Could NVDA and GOOG have been combined in a portfolio?

Yes, though allocation sizing mattered. Their moderate correlation offered some diversification benefits. NVDA's higher volatility (49.6%) meant even small allocations can materially impact overall portfolio risk.

Share This Comparison of NVDA vs GOOG