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Compare · BONK vs PEPE · 2026

Bonk vs Pepe

A year of returns, risk, and volatility, compared.

Bonk (BONK) and Pepe (PEPE) are compared across trailing return, volatility, drawdown, and risk-adjusted metrics.

Gale Finance Team
Written by Gale Finance Team
Sid Kalla
Reviewed by Sid Kalla CFA Charterholder
Quick answer

Which is a better investment: BONK or PEPE?

Over the past year, PEPE outperformed BONK. PEPE returned -56.2% compared with BONK’s -59.2%. BONK had the better risk-adjusted return, with a Sharpe ratio of -0.21 versus PEPE’s -0.24. PEPE was less volatile than BONK, and PEPE had a smaller max drawdown than BONK.

Total Return
BONK -59.2%
PEPE -56.2%
Sharpe Ratio
BONK -0.21
PEPE -0.24
Annualized Volatility
BONK 118.3%
PEPE 111.1%
Max Drawdown
BONK -85.7%
PEPE -78.8%

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

BONK Total Return
-59.2%
PEPE Total Return
-56.2%

Relative Performance of BONK vs PEPE (Normalized to 100)

BONK PEPE

Normalized to 100 at start date for comparison

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Key Takeaways

  • Total Return: BONK delivered a -59.2% total return, while PEPE returned -56.2% over the same period. PEPE outperformed on total returns.
  • Risk-Adjusted Return (Sharpe Ratio): Both Sharpe ratios were negative (BONK -0.21 vs PEPE -0.24), meaning both underperformed the risk-free rate; BONK was less negative.
  • Volatility (Annualized): BONK was more volatile, with 118.3% annualized volatility, versus 111.1% for PEPE.
  • Maximum Drawdown: PEPE's maximum drawdown was -78.8%, while BONK experienced a deeper drawdown of -85.7%.
  • Tail Risk (VaR & Expected Shortfall): At the 5% level (daily log returns), BONK's VaR was -8.30% and its Expected Shortfall (CVaR) was -12.50%; PEPE's were -8.05% and -11.99%. VaR is the cutoff; Expected Shortfall is the average move on the worst days.
  • Skew & Kurtosis: Skew: BONK 0.23 vs PEPE 0.52. Excess kurtosis: BONK 4.81 vs PEPE 5.65. Negative skew leans downside; higher excess kurtosis means fatter tails.
  • Tail Days & Extremes: 2σ tail days (down/up): BONK 5/12, PEPE 7/10. Worst day: BONK -29.91% (2025-10-10) vs PEPE -26.46% (2025-10-10). Best day: BONK +31.20% (2025-07-16) vs PEPE +34.55% (2025-05-08).
  • Risk ratios: Sortino - BONK: -0.34 vs. PEPE: -0.39 , Calmar - BONK: -0.69 vs. PEPE: -0.72 , Sterling - BONK: -1.24 vs. PEPE: -1.67 , Treynor - BONK: -0.07 vs. PEPE: -0.11 , Ulcer Index - BONK: 61.19% vs. PEPE: 54.01%

Investment Comparison

If you invested $10,000 in each asset on April 24, 2025:

BONK $4,084.78 -59.2%
PEPE $4,378.56 -56.2%

Difference: $293.78 (PEPE ahead)

Bonk vs Pepe Performance Over Time

Metric BONK PEPE
30 Days 3.1% 8.8%
90 Days -29.6% -23.4%
180 Days -57.3% -46.4%
1 Year -59.2% -56.2%

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

Bonk vs Pepe Correlation

Average Correlation
strongly correlated
0.64
Current (30-day) 0.84
30-day rolling range -0.41 to +0.98

Bonk and Pepe are strongly correlated over the past year. With a correlation of 0.64, these assets tend to move together, limiting diversification benefits.

For portfolio construction, this strong correlation means holding both BONK and PEPE provides limited risk reduction — they're likely to decline together in downturns.

Metric Value
Current (30-day) 0.84
Average (full period) 0.64
Minimum (30-day rolling) -0.41
Maximum (30-day rolling) 0.98

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
BONK
-85.7%
PEPE
-78.8%

Bonk experienced its maximum drawdown of -85.7% from 2025-07-16 to 2026-04-04. It has not yet recovered to its previous peak.

Pepe experienced its maximum drawdown of -78.8% from 2025-05-22 to 2026-03-07. It has not yet recovered to its previous peak.

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

Bonk vs Pepe Volatility (BONK vs PEPE)

BONK Volatility
118.3%
±6.19% 1-day vol
PEPE Volatility
111.1%
±5.82% 1-day vol
1-day volatility (1σ)
BONK
±6.19%
PEPE
±5.82%

Bonk's 118.3% annualized volatility translates to about ±6.19% one-standard-deviation daily volatility.

Pepe's 111.1% annualized volatility translates to about ±5.82% one-standard-deviation daily volatility.

BONK had the wider volatility profile over this window. That means its day-to-day return distribution was broader; PEPE 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 BONK and PEPE

Sharpe Ratio: BONK vs. PEPE

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 Annualized volatility 0 125% vol 118.3% · excess -25.4% vol 111.1% · excess -27.1%
excess return / total volatility
Formula Sharpe=E[R]RfσR\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. Both Sharpe ratios were negative (BONK -0.21 vs PEPE -0.24), meaning both underperformed the risk-free rate; BONK was less negative.

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 BONK and PEPE

Sortino Ratio: BONK vs. PEPE

Return per downside volatility

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

Higher is better
Frequency (days) Daily return (%) target -32.5% +37.1% 68 0
excess return / downside volatility
Formula Sortino=E[R]Rfσdown\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). BONK 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: BONK 75.9% vs PEPE 70.5%. 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 BONK and PEPE

Calmar Ratio: BONK vs. PEPE

CAGR per worst drawdown

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

Higher is better
0% BONK -59.3% -85.7% PEPE -56.3% -78.8%
CAGR / max drawdown
Formula Calmar=CAGRMaxDD\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. BONK 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 BONK and PEPE

Sterling Ratio: BONK vs. PEPE

Return per average drawdown

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

Higher is better
0% -22% -45% -67% -90% 10% drawdown threshold
excess annual return / average deep drawdown
Formula Sterling=CAGRRfD>10%\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%). BONK 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 BONK and PEPE

Treynor Ratio: BONK vs. PEPE

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
Asset return Market return 0 0 β 3.06 β 2.46
excess return / market beta
Formula Treynor=E[R]Rfβ\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. BONK 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 BONK and PEPE

Ulcer Index: BONK vs. PEPE

Drawdown pain

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

Lower is better
0% -22% -45% -67% -90%
root-mean-square drawdown
Formula UI=E[Dt2]\displaystyle \mathrm{UI} = \sqrt{\mathbb{E}[D_t^2]}

Ulcer Index captures drawdown depth and duration. Lower Ulcer Index means less drawdown pain. PEPE 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): Bonk vs. Pepe

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(PtPt1)\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: BONK vs. PEPE (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
BONK VaR 5% ES 5% PEPE VaR 5% ES 5% -41.2% 0% +41.2% Daily log return
VaR marks the 5th percentile loss cutoff; Expected Shortfall averages the observations beyond that cutoff.
Formula VaR5%=Q0.05(rt),ES5%=E[rtrtVaR5%]\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) BONK PEPE
5% VaR (daily log return) -8.30% -8.05%
5% Expected Shortfall (CVaR) -12.50% (worst 19 days) -11.99% (worst 19 days)
Skew 0.23 0.52
Excess kurtosis 4.81 5.65
2σ tail days (down / up) 5 / 12 7 / 10
Worst day -29.91% (2025-10-10) -26.46% (2025-10-10)
Best day +31.20% (2025-07-16) +34.55% (2025-05-08)

Downside co-moves (2σ) — 1-Year

Computed on shared dates only (n=364). 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: BONK vs. PEPE (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 BONK and PEPE crossed their own 2σ downside threshold.

-2σ PEPE -2σ BONK Joint downside zone -35.0% 0% +35.0% +40.5% 0% -40.5% PEPE daily log return BONK daily log return
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 BONK and PEPE had a big down day (2σ)

Date (interval) BONK PEPE
2025-05-30 -13.35% -13.49%
2025-10-10 -29.91% -26.46%
2025-11-03 -16.64% -14.90%

Days when BONK had a big down day

Date (interval) BONK PEPE
2025-05-30 -13.35% -13.49%
2025-08-14 -13.00% -9.85%
2025-10-10 -29.91% -26.46%
2025-11-03 -16.64% -14.90%
2026-02-05 -15.90% +11.58%

Days when PEPE had a big down day

Date (interval) BONK PEPE
2025-05-30 -13.35% -13.49%
2025-10-10 -29.91% -26.46%
2025-11-03 -16.64% -14.90%
2025-12-01 -6.77% -10.96%
2026-01-30 -3.03% -12.28%
2026-02-04 -0.71% -15.31%
2026-02-14 +14.33% -11.11%

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 Bonk vs. Pepe (1-Year)

Metric BONK PEPE
Total Return -59.2% -56.2%
Annualized Volatility 118.3% 111.1%
Sharpe Ratio -0.21 -0.24
Sortino Ratio -0.34 -0.39
Calmar Ratio -0.69 -0.72
Sterling Ratio -1.24 -1.67
Treynor Ratio -0.07 -0.11
Ulcer Index 61.19% 54.01%
Max Drawdown -85.7% -78.8%
Avg Correlation to S&P 500 0.38 0.35
5% VaR (daily log return) -8.30% -8.05%
5% Expected Shortfall (CVaR) -12.50% -11.99%
Skew 0.23 0.52
Excess kurtosis 4.81 5.65
2σ tail days (down / up) 5 / 12 7 / 10
Audit this calculation

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

Inputs & conventions

Shared window for pair metrics
2025-04-24 → 2026-04-23 (last shared close).
Rolling correlation sample (shared closes)
335 rolling 30-day values (from 364 shared daily returns).
Annualization (days/year)
BONK: 365 days/year; PEPE: 365 days/year.
Risk-free rate
Uses the 3-month U.S. Treasury yield (FRED: DGS3MO), averaged over each asset’s window:
  • BONK: 4.17% over 2025-04-24 → 2026-04-23.
  • PEPE: 4.17% over 2025-04-24 → 2026-04-23.
Volatility drag (rule of thumb)
Estimated from annualized volatility (simple returns). For the log-return framing, see Log returns.
  • BONK: ≈ -70.0%/yr
  • PEPE: ≈ -61.7%/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
rt=PtPt11r_t = \frac{P_t}{P_{t-1}} - 1
σann=σ(rt)A\sigma_{ann} = \sigma(r_t)\sqrt{A}
drag12σann2\text{drag} \approx \tfrac{1}{2}\sigma_{ann}^2
S=Arˉrfσ(rt)AS = \frac{A\,\bar{r} - r_f}{\sigma(r_t)\sqrt{A}}
So=ArˉrfE[min(0,rtrf/A)2]ASo = \frac{A\,\bar{r} - r_f}{\sqrt{\mathbb{E}[\min(0,\,r_t - r_f/A)^2]}\,\sqrt{A}}
MDD=mint(PtmaxstPs1)MDD = \min_t\left(\frac{P_t}{\max_{s \le t} P_s} - 1\right)
ρ=cov(rA,rB)σAσB\rho = \frac{\operatorname{cov}(r^A,\,r^B)}{\sigma_A\,\sigma_B}
t=ln(PtPt1)\ell_t = \ln\left(\frac{P_t}{P_{t-1}}\right)
Notation
PtP_t
Price on day t.
rtr_t
Simple daily return.
t\ell_t
Log daily return.
rˉ\bar{r}
Average daily return.
σ(rt)\sigma(r_t)
Standard deviation of daily returns.
AA
Annualization factor (days/year).
rfr_f
Annual risk-free rate.

Bonk vs Pepe: Frequently Asked Questions

Which has higher volatility: BONK or PEPE?

BONK showed higher volatility at 118.3% annualized, compared to 111.1% for PEPE Over the past year. Higher volatility means larger price swings in both directions.

Does BONK provide diversification when held with PEPE?

BONK and PEPE are strongly correlated over the past year, with an average correlation of 0.64. This strong correlation limits diversification benefits.

How bad are the worst 5% days for BONK vs PEPE?

Over the past year, BONK's 5% VaR was -8.30% and its 5% Expected Shortfall was -12.50% (worst 19 days). PEPE's were -8.05% and -11.99% (worst 19 days).

Do BONK and PEPE crash together on bad days?

On shared dates (n=364), when PEPE has a 2σ down day, BONK also does 42.9% (3/7 days). In the other direction, when BONK has one, PEPE also does 60.0% (3/5 days).

Which has better risk-adjusted returns: BONK or PEPE?

Both assets posted negative Sharpe ratios Over the past year (BONK -0.21 vs PEPE -0.24), meaning both underperformed the risk-free rate; BONK was less negative.

Can BONK and PEPE be combined in a portfolio?

Yes, though allocation sizing matters. Their strong correlation provides limited risk reduction since they tend to move together. BONK's higher volatility (118.3%) means even small allocations can materially impact overall portfolio risk.

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