Apple vs Google (AAPL vs GOOG) 2026: Stock Returns, Risk & Volatility

Q: Which is a better investment: AAPL or GOOG?

Over the past year, GOOG looks like the better investment: it had higher total return (GOOG +106.7% vs AAPL +31.1%) and a higher Sharpe ratio (GOOG 2.63 vs AAPL 1.11). On risk, AAPL was less volatile (AAPL 23.4% vs GOOG 27.8%), AAPL had a smaller max drawdown (AAPL -13.8% vs GOOG -20.8%), and AAPL had less severe losses on the worst 5% of days (Expected Shortfall of AAPL -3.13% vs GOOG -3.14%).

Written by Gale Finance Team

Reviewed by Sid Kalla CFA Charterholder

An old rivalry, one for the history books starting with Steve Jobs and his feelings about Android. See how they compare now.

Quick answer

Which is a better investment: AAPL or GOOG?

Over the past year, GOOG outperformed AAPL. GOOG returned +106.7% compared with AAPL’s +31.1%. GOOG had the better risk-adjusted return, with a Sharpe ratio of 2.63 versus AAPL’s 1.11. AAPL was less volatile than GOOG, and AAPL had a smaller max drawdown than GOOG.

Total Return

AAPL +31.1%

GOOG +106.7%

Sharpe Ratio

AAPL 1.11

GOOG 2.63

Annualized Volatility

AAPL 23.4%

GOOG 27.8%

Max Drawdown

AAPL -13.8%

GOOG -20.8%

Metric winners: Total Return: GOOG; Sharpe Ratio: GOOG; Annualized Volatility: AAPL (less volatile); Max Drawdown: AAPL (smaller drawdown).

AAPL Total Return

↑ +31.1%

GOOG Total Return

↑ +106.7%

Relative Performance of AAPL vs GOOG (Normalized to 100)

AAPL GOOG

Normalized to 100 at start date for comparison

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Key Takeaways

Total Return: AAPL delivered a +31.1% total return, while GOOG returned +106.7% over the same period. GOOG outperformed on total returns.
Risk-Adjusted Return (Sharpe Ratio): GOOG had a higher Sharpe (2.63 vs 1.11), indicating better risk-adjusted performance.
Volatility (Annualized): GOOG was more volatile, with 27.8% annualized volatility, versus 23.4% for AAPL.
Maximum Drawdown: AAPL's maximum drawdown was -13.8%, while GOOG experienced a deeper drawdown of -20.8%.
Tail Risk (VaR & Expected Shortfall): At the 5% level (daily log returns), AAPL's VaR was -2.23% and its Expected Shortfall (CVaR) was -3.13%; GOOG's were -2.30% and -3.14%. VaR is the cutoff; Expected Shortfall is the average move on the worst days.
Skew & Kurtosis: Skew: AAPL 0.36 vs GOOG 0.30. Excess kurtosis: AAPL 2.22 vs GOOG 3.29. Negative skew leans downside; higher excess kurtosis means fatter tails.
Tail Days & Extremes: 2σ tail days (down/up): AAPL 8/10, GOOG 4/5. Worst day: AAPL -5.00% (2026-02-12) vs GOOG -7.51% (2025-05-07). Best day: AAPL +6.31% (2025-05-12) vs GOOG +9.01% (2025-09-03).
Risk ratios: Sortino - AAPL: 1.75 vs. GOOG: 4.54 , Calmar - AAPL: 2.27 vs. GOOG: 5.17 , Sterling - AAPL: 1.96 vs. GOOG: 4.97 , Treynor - AAPL: 0.26 vs. GOOG: 0.63 , Ulcer Index - AAPL: 5.88% vs. GOOG: 5.66%

Investment Comparison

If you invested $10,000 in each asset on April 25, 2025:

AAPL $13,109 +31.1%

GOOG $20,670.04 +106.7%

Difference: $7,561.04 (GOOG ahead)

Apple vs Google Performance Over Time

Metric	AAPL	GOOG
30 Days	8.7%	16.8%
90 Days	10.2%	2.8%
180 Days	4.1%	29.7%
1 Year	31.1%	106.7%

Shorter time frames can show different leaders as market conditions change. Consider your investment horizon when comparing performance.

Apple vs Google Correlation

Average Correlation

moderately correlated

0.32

Current (30-day) 0.55

30-day rolling range -0.15 to +0.59

Apple and Google are moderately correlated over the past year. With a correlation of 0.32, these assets show 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)	0.55
Average (full period)	0.32
Minimum (30-day rolling)	-0.15
Maximum (30-day rolling)	0.59

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. Current, minimum, and maximum figures are 30-day rolling correlations on shared daily returns.

Drawdown

Maximum Drawdown

AAPL

-13.8%

GOOG

-20.8%

Apple experienced its maximum drawdown of -13.8% from 2025-12-02 to 2026-03-30. It has not yet recovered to its previous peak.

Google experienced its maximum drawdown of -20.8% from 2026-02-02 to 2026-03-30. It has not yet recovered to its previous peak.

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

Apple vs Google Volatility (AAPL vs GOOG)

AAPL Volatility

23.4%

±1.48% 1-day vol

GOOG Volatility

27.8%

±1.75% 1-day vol

1-day volatility (1σ)

AAPL

±1.48%

GOOG

±1.75%

Apple's 23.4% annualized volatility translates to about ±1.48% one-standard-deviation daily volatility.

Google's 27.8% annualized volatility translates to about ±1.75% one-standard-deviation daily volatility.

GOOG had the wider volatility profile over this window. That means its day-to-day return distribution was broader; AAPL was calmer, but lower volatility does not by itself mean better returns.

Treat the ± daily figure as a one-standard-deviation estimate from historical returns, not a forecast or expected absolute daily move. For context, 15-18% annualized volatility is roughly ±1% one-standard-deviation daily volatility.

Risk-adjusted ratios

Sharpe Ratio of AAPL and GOOG

Sharpe Ratio: AAPL vs. GOOG

Return per total volatility

Sharpe gives us excess return per unit of risk. Upside and downside volatility both count as risk.

Higher is better

excess return / total volatility

Formula

\displaystyle \mathrm{Sharpe} = \frac{\mathbb{E}[R] - R_f}{\sigma_R}

Sharpe ratio measures return per unit of risk (volatility). A higher Sharpe indicates better risk-adjusted performance. GOOG had a higher Sharpe (2.63 vs 1.11), 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 AAPL and GOOG

Sortino Ratio: AAPL vs. GOOG

Return per downside volatility

Sortino keeps the return-over-risk idea, but only returns below the target rate count as volatility.

Higher is better

excess return / downside volatility

Formula

\displaystyle \mathrm{Sortino} = \frac{\mathbb{E}[R] - R_f}{\sigma_{\mathrm{down}}}

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: AAPL 14.8% vs GOOG 16.1%. 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).

Calmar Ratio of AAPL and GOOG

Calmar Ratio: AAPL vs. GOOG

CAGR per worst drawdown

Calmar compares CAGR against the single deepest peak-to-trough loss over the period.

Higher is better

CAGR / max drawdown

Formula

\displaystyle \mathrm{Calmar} = \frac{\mathrm{CAGR}}{|\mathrm{MaxDD}|}

Calmar ratio compares CAGR to maximum drawdown. Higher Calmar means more return per unit of worst drawdown. GOOG posted the higher Calmar ratio.

Calmar is computed on each asset's full 365-day lookback and uses the max drawdown over that same window.

Sterling Ratio of AAPL and GOOG

Sterling Ratio: AAPL vs. GOOG

Return per average drawdown

Sterling smooths the drawdown penalty by using average drawdown events instead of only the worst one.

Higher is better

excess annual return / average deep drawdown

Formula

\displaystyle \mathrm{Sterling} = \frac{\mathrm{CAGR} - R_f}{\overline{D}_{>10\%}}

Sterling ratio measures excess return per unit of average drawdown (typically drawdowns worse than 10%). GOOG posted the higher Sterling ratio.

Sterling uses average drawdown events deeper than 10% and subtracts the risk-free rate to report excess return.

Treynor Ratio of AAPL and GOOG

Treynor Ratio: AAPL vs. GOOG

Excess return per market beta

Treynor divides excess annualized return by beta — the sensitivity of the asset to broad-market moves. The slope shown is each asset’s beta vs SPY.

Higher is better

excess return / market beta

Formula

\displaystyle \mathrm{Treynor} = \frac{\mathbb{E}[R] - R_f}{\beta}

Treynor ratio measures excess return per unit of market risk (beta) instead of total volatility. GOOG posted the higher Treynor ratio.

Treynor uses beta vs the S&P 500 (SPY) on shared dates and the average 3-month Treasury rate as the risk-free rate.

Ulcer Index of AAPL and GOOG

Ulcer Index: AAPL vs. GOOG

Drawdown pain

Ulcer Index is a risk index, not a return-over-risk ratio. Lower means smaller and shorter drawdowns.

Lower is better

root-mean-square drawdown

Formula

\displaystyle \mathrm{UI} = \sqrt{\mathbb{E}[D_t^2]}

Ulcer Index captures drawdown depth and duration. Lower Ulcer Index means less drawdown pain. GOOG had the lower Ulcer Index (less drawdown pain).

Ulcer Index is computed from each asset's drawdown series over the full lookback window.

Tail Risk & Distribution Shape (1-Year): Apple 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.

Tail Risk & Distribution Shape: AAPL vs. GOOG (1-Year)

Actual daily return tails

The bars are real daily log-return observations from the article window. Darker bars are observations at or beyond each asset’s 5% VaR cutoff.

Observed returns

VaR marks the 5th percentile loss cutoff; Expected Shortfall averages the observations beyond that cutoff.

Formula

\displaystyle \mathrm{VaR}_{5\%}=Q_{0.05}(r_t),\quad \mathrm{ES}_{5\%}=\mathbb{E}[r_t\mid r_t\le \mathrm{VaR}_{5\%}]

Metric (1-Year)	AAPL	GOOG
5% VaR (daily log return)	-2.23%	-2.30%
5% Expected Shortfall (CVaR)	-3.13% (worst 13 days)	-3.14% (worst 13 days)
Skew	0.36	0.30
Excess kurtosis	2.22	3.29
2σ tail days (down / up)	8 / 10	4 / 5
Worst day	-5.00% (2026-02-12)	-7.51% (2025-05-07)
Best day	+6.31% (2025-05-12)	+9.01% (2025-09-03)

Downside co-moves (2σ) — 1-Year

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.

Downside co-move map: AAPL vs. GOOG (2σ)

Shared-close daily returns

Dots mark actual downside days: asset-colored dots are one-sided downside moves, and red dots are joint downside days. Grey dots add sampled shared-return context when available. The shaded lower-left zone shows where both AAPL and GOOG crossed their own 2σ downside threshold.

2σ

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 AAPL and GOOG had a big down day (2σ)

None in this window.

Days when AAPL had a big down day

Date (interval)	AAPL	GOOG
2025-05-02	-3.74%	+1.86%
2025-05-02 → 2025-05-05	-3.15%	+0.14%
2025-05-23	-3.02%	-1.39%
2025-09-10	-3.23%	-0.16%
2025-10-10	-3.45%	-1.95%
2026-01-16 → 2026-01-20	-3.46%	-2.48%
2026-02-12	-5.00%	-0.63%
2026-02-27	-3.21%	+1.39%

Days when GOOG had a big down day

Date (interval)	AAPL	GOOG
2025-05-07	-1.14%	-7.51%
2025-06-18 → 2025-06-20	+2.25%	-3.59%
2025-12-17	-1.01%	-3.14%
2026-03-24	+0.06%	-3.28%

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 Apple vs. Google (1-Year)

Metric	AAPL	GOOG
Total Return	+31.1%	+106.7%
Annualized Volatility	23.4%	27.8%
Sharpe Ratio	1.11	2.63
Sortino Ratio	1.75	4.54
Calmar Ratio	2.27	5.17
Sterling Ratio	1.96	4.97
Treynor Ratio	0.26	0.63
Ulcer Index	5.88%	5.66%
Max Drawdown	-13.8%	-20.8%
Avg Correlation to S&P 500	0.50	0.51
5% VaR (daily log return)	-2.23%	-2.30%
5% Expected Shortfall (CVaR)	-3.13%	-3.14%
Skew	0.36	0.30
Excess kurtosis	2.22	3.29
2σ tail days (down / up)	8 / 10	4 / 5

Audit this calculation

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

Inputs & conventions

Shared window for pair metrics: 2025-04-25 → 2026-04-23 (last shared close).
Rolling correlation sample (shared closes): 220 rolling 30-day values (from 249 shared daily returns).
Annualization (days/year): AAPL: 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:

AAPL: 4.17% over 2025-04-25 → 2026-04-23.

GOOG: 4.17% over 2025-04-25 → 2026-04-23.
Volatility drag (rule of thumb): Estimated from annualized volatility (simple returns). For the log-return framing, see Log returns.

AAPL: ≈ -2.7%/yr

GOOG: ≈ -3.9%/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.

Apple vs Google: Frequently Asked Questions

Which has higher volatility: AAPL or GOOG?

GOOG showed higher volatility at 27.8% annualized, compared to 23.4% for AAPL Over the past year. Higher volatility means larger price swings in both directions.

Does AAPL provide diversification when held with GOOG?

AAPL and GOOG are moderately correlated over the past year, with an average correlation of 0.32. This offers some diversification benefit, though they still tend to move together during major market moves.

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

Over the past year, AAPL's 5% VaR was -2.23% and its 5% Expected Shortfall was -3.13% (worst 13 days). GOOG's were -2.30% and -3.14% (worst 13 days).

Do AAPL and GOOG crash together on bad days?

On shared dates (n=249), when GOOG has a 2σ down day, AAPL also does 0.0% (0/4 days). In the other direction, when AAPL has one, GOOG also does 0.0% (0/8 days).

Which has better risk-adjusted returns: AAPL or GOOG?

GOOG showed better risk-adjusted performance with a Sharpe ratio of 2.63 versus AAPL's 1.11 Over the past year.

Can AAPL and GOOG be combined in a portfolio?

Yes, though allocation sizing matters. Their moderate correlation offers some diversification benefits. GOOG's higher volatility (27.8%) means even small allocations can materially impact overall portfolio risk.

Explore our financial glossary

Which is a better investment: AAPL or GOOG?

Share This Comparison of AAPL vs GOOG

Relative Performance of AAPL vs GOOG (Normalized to 100)

Trade AAPL or GOOG

Key Takeaways

Investment Comparison

Apple vs Google Performance Over Time

Apple vs Google Correlation

Drawdown

Apple vs Google Volatility (AAPL vs GOOG)

Risk-adjusted ratios

Sharpe Ratio of AAPL and GOOG

Sharpe Ratio: AAPL vs. GOOG

Sortino Ratio of AAPL and GOOG

Sortino Ratio: AAPL vs. GOOG

Calmar Ratio of AAPL and GOOG

Calmar Ratio: AAPL vs. GOOG

Sterling Ratio of AAPL and GOOG

Sterling Ratio: AAPL vs. GOOG

Treynor Ratio of AAPL and GOOG

Treynor Ratio: AAPL vs. GOOG

Ulcer Index of AAPL and GOOG

Ulcer Index: AAPL vs. GOOG

Tail Risk & Distribution Shape (1-Year): Apple vs. Google

Tail Risk & Distribution Shape: AAPL vs. GOOG (1-Year)

Downside co-moves (2σ) — 1-Year

Downside co-move map: AAPL vs. GOOG (2σ)

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

Days when AAPL had a big down day

Days when GOOG had a big down day

Full Comparison of Apple vs. Google (1-Year)

Inputs & conventions

Formulas

Apple vs Google: Frequently Asked Questions

Which has higher volatility: AAPL or GOOG?

Does AAPL provide diversification when held with GOOG?

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

Do AAPL and GOOG crash together on bad days?

Which has better risk-adjusted returns: AAPL or GOOG?

Can AAPL and GOOG be combined in a portfolio?