Volatility Shares Trust - 2x Bitcoin Strategy ETF

10-Year Study

BITX.US · · US · ETF

Executive Summary: Volatility Shares Trust - 2x Bitcoin Strategy ETF has compounded at 18.1% annually over the last 10 years, with a maximum drawdown of 74.9% and an annualized volatility of 113.0%.

1Y CAGR
-65.3%
3Y CAGR
+18.1%
5Y CAGR
+18.1%
10Y CAGR
+18.1%

History & Riski10-year historical performance analysis including CAGR, Max Drawdown, Sharpe & Sortino ratios, annual returns, and rolling volatility — all computed from daily market data.

10-Year Growth of $10,000

Max DrawdownMax DrawdownThe largest peak-to-trough decline in the asset's value over the measurement period.Click for full definition →
74.9%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.78
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
2.04
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
107.9%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +163.4%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · -38.7%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
33%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
2026-10.6-42.43.422.7————————-34.6%
202514.0-33.1-8.725.820.83.315.0-16.39.4-10.8-33.8-9.9-38.7%
2024-2.998.721.3-34.726.4-24.313.0-25.513.618.084.1-13.3163.4%
2023——————-11.1-23.64.460.512.618.351.7%

Risk X-RayiA 19-factor macroeconomic risk decomposition showing exactly which market forces (equity beta, rates, inflation, credit, commodity, crypto) drive this asset's volatility. Powered by multivariate regression against daily factor returns.

Risk Profile Insight: This asset has an estimated annualized volatility of 113.0%. The dominant macroeconomic risk driver is BTC-USD.CC, accounting for 72.8% of variance. Idiosyncratic stock-specific factors contribute 0.9%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2023-06-0110000
2023-07-018886.665597933716
2023-08-016793.332625909784
2023-09-017093.333394114354
2023-10-0111386.668341521467
2023-11-0112826.666119637477
2023-12-0115173.335231051877
2024-01-0114726.66901517778
2024-02-0129266.672761652375
2024-03-0135500.006204729216
2024-04-0123166.665864694864
2024-05-0129278.406875414017
2024-06-0122155.717092374405
2024-07-0125042.359728589105
2024-08-0118664.97864264668
2024-09-0121200.393084369207
2024-10-0125025.95054130142
2024-11-0146079.226541248405
2024-12-0139968.17438209972
2025-01-0145553.669936938844
2025-02-0130495.067324688753
2025-03-0127854.10326340899
2025-04-0135049.6728672594
2025-05-0142326.44084997868
2025-06-0143728.26392605044
2025-07-0150306.64109474047
2025-08-0142128.73369580771
2025-09-0146090.21777586543
2025-10-0141093.37965522473
2025-11-0127194.992184151637
2025-12-0124496.608630077673
2026-01-0121897.607110298897
2026-02-0112613.925792958064
2026-03-0113047.667802680831
2026-04-0116013.046848744656
Annual Return Matrix
YearAnnual Return
20241.6341060665624645
2025-0.38709713393742584
2026-0.3463157659675652
Total Factor Risk
1.1299959872402576
VTI.US Exposure
-0.09819765579546642
VEA.US Exposure
-0.015356705168962266
VWO.US Exposure
0.005558303877484106
QQQ.US Exposure
0.07726742331888191
VTV.US Exposure
0.060150323950270077
IJR.US Exposure
-0.0024694189658651996
QUAL.US Exposure
-0.011545684789103082
SHV.US Exposure
0.21542306327667565
TLT.US Exposure
-0.0013068014937583242
LQD.US Exposure
0.010470173814806832
HYG.US Exposure
0.015885854870759327
GLD.US Exposure
0.001506437211213043
USO.US Exposure
0.0005565081768912509
VNQ.US Exposure
-0.005732795103295861
BTC-USD.CC Exposure
0.7282726423629831
CPER.US Exposure
-0.0005885195997523898
VIX.INDX Exposure
0.008433441652209784
UUP.US Exposure
0.0033069561355049738
TIP.US Exposure
-0.0008200042629322171
Idiosyncratic Exposure
0.00918645653145567
Value Score
50
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
100
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
113.0%

FundamentalsiCompany financial health metrics: P/E valuation, dividend yield, Piotroski F-Score (9-point profitability signal), Altman Z-Score (bankruptcy risk proxy), and a radar chart across 6 fundamental dimensions. Note: ETFs may show N/A for some metrics.

Fundamental Dimensions

Core Valuation

P/E Ratio (TTM)P/E RatioPrice-to-Earnings ratio — the market price of a stock divided by its earnings per share, a key valuation measure.Click for full definition →N/A
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →41.53%
Market Cap$0
Piotroski F-ScorePiotroski F-ScoreA 9-point scoring system evaluating a company's financial strength across profitability, leverage, and operating efficiency.Click for full definition →
9-point profitability signal
0.0/ 9
Weak
Altman Z-ScoreAltman Z-ScoreA bankruptcy prediction model that combines 5 financial ratios into a single score indicating financial distress risk.Click for full definition →
Bankruptcy risk proxy
1.18
Distress Zone
Income Simulation

Based on $10,000 initial investment.

Total Income Generated
$32
Avg Yield on Cost
0.32%
Annual Income Simulation Table
Historical Realised Yields
YearAnnual PayoutYield on CostQuality
2026$32.40.32%Solid

Momentum & MacroiPrice momentum indicators relative to key technical levels: distance from 50-Day SMA (intermediate trend), 200-Day SMA (long-term trend), 52-Week High (bullish proximity), and Beta (market sensitivity coefficient).

vs 50-Day SMAMoving Averages (SMA)A rolling average of an asset's price over a defined window — used to identify trends and momentum signals.Click for full definition →
+14.1%
Above/below 50-day moving average
vs 200-Day SMAMoving Averages (SMA)A rolling average of an asset's price over a defined window — used to identify trends and momentum signals.Click for full definition →
-50.9%
Above/below 200-day moving average
vs 52-Week High52-Week HighThe highest price an asset reached in the past 52 weeks — a key reference for momentum and valuation context.Click for full definition →
71.1% from high
Distance from 52-week high
BetaBetaA measure of an asset's sensitivity to broad market movements relative to a benchmark (e.g. S&P 500).Click for full definition →
1.00
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Volatility Shares Trust - 2x Bitcoin Strategy ETF a high-risk investment?

Volatility Shares Trust - 2x Bitcoin Strategy ETF (BITX.US) has an annualized volatility of 113.0% and experienced a maximum drawdown of 74.9% over the last 10 years. Its primary macro risk driver is BTC-USD.CC.

What is the 10-year return of BITX.US?

Over the past 10 years, BITX.US has generated a Compound Annual Growth Rate (CAGR) of 18.1%. It has had a positive return in 33% of the years measured.

Data Methodology & Trust

The risk and return information on this page is pre-calculated mathematically using daily market data spanning a 10-year period. Fundamentals (such as P/E Ratio, Market Cap, and Dividend Yield) represent trailing averages and may not immediately reflect real-time live market fluctuations. Advanced scoring models like the Piotroski F-Score and Altman Z-Score are proxies applied to publicly available trailing-twelve-month financial statements and may not account for recent off-balance-sheet events, qualitative company shifts, or sector-specific capital structures. Macroeconomic factor exposures are estimated via multivariate regression against standard market indices. This data is provided for quantitative insight and backtesting research, and should not be misconstrued as tailored financial advice.

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