GraniteShares 1.75x Long BABA Daily ETF

10-Year Study

BABX.US · · US · ETF

Executive Summary: GraniteShares 1.75x Long BABA Daily ETF has compounded at 6.7% annually over the last 10 years, with a maximum drawdown of 62.5% and an annualized volatility of 127.6%.

1Y CAGR
+23.2%
3Y CAGR
+18.6%
5Y CAGR
+6.7%
10Y CAGR
+6.7%

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 →
62.5%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.52
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
1.70
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
92.4%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · +123.9%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2023 · -33.9%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
50%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
202629.7-28.7-25.920.9————————-17.2%
202532.971.7-3.0-22.2-11.00.810.821.870.0-11.9-16.2-14.3123.9%
2024-12.62.7-6.05.16.4-13.218.29.758.1-16.8-21.9-7.41.2%
202344.6-33.726.4-29.2-12.06.640.8-16.8-12.5-9.7-17.47.5-33.9%

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 127.6%. The dominant macroeconomic risk driver is VWO.US, accounting for 36.4% of variance. Idiosyncratic stock-specific factors contribute 13.9%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2022-12-0110000
2023-01-0114455.527847049045
2023-02-019576.89110556941
2023-03-0112107.231920199501
2023-04-018571.072319201996
2023-05-017539.484621778887
2023-06-018034.081463009144
2023-07-0111309.22693266833
2023-08-019409.80881130507
2023-09-018237.738985868662
2023-10-017439.7339983374895
2023-11-016147.13216957606
2023-12-016610.556940980881
2024-01-015777.223607647548
2024-02-015935.162094763093
2024-03-015581.87863674148
2024-04-015868.661679135495
2024-05-016242.726517040732
2024-06-015419.783873649209
2024-07-016404.821280133002
2024-08-017028.26267664173
2024-09-0111113.881961762261
2024-10-019243.557772236076
2024-11-017223.607647547798
2024-12-016691.604322527017
2025-01-018890.274314214465
2025-02-0115266.00166251039
2025-03-0114804.655029093932
2025-04-0111512.884455527848
2025-05-0110249.376558603492
2025-06-0110328.345802161266
2025-07-0111442.227763923525
2025-08-0113931.837073981715
2025-09-0123678.3042394015
2025-10-0120864.50540315877
2025-11-0117485.453034081464
2025-12-0114979.218620116377
2026-01-0119434.74646716542
2026-02-0113848.711554447218
2026-03-0110257.689110556943
2026-04-0112406.483790523693
Annual Return Matrix
YearAnnual Return
2023-0.3389443059019118
20240.012260295504558538
20251.2385093167701862
2026-0.17175360710321863
Total Factor Risk
1.2758577506767794
VTI.US Exposure
-0.06964147306425911
VEA.US Exposure
-0.08735508540305996
VWO.US Exposure
0.36385636484168177
QQQ.US Exposure
0.04741453273795309
VTV.US Exposure
0.0660514939231709
IJR.US Exposure
-0.01748564790974987
QUAL.US Exposure
0.06714942169795722
SHV.US Exposure
0.2893868509576318
TLT.US Exposure
0.054059149341960176
LQD.US Exposure
-0.021952769580684928
HYG.US Exposure
0.18114251686561644
GLD.US Exposure
-0.0027786667268576903
USO.US Exposure
0.0026419809266095356
VNQ.US Exposure
-0.012070094588886313
BTC-USD.CC Exposure
0.0033462618615591887
CPER.US Exposure
0.01623850479233633
VIX.INDX Exposure
-0.018725967265289318
UUP.US Exposure
-0.004897707372033445
TIP.US Exposure
0.004790081539613944
Idiosyncratic Exposure
0.1388302524247303
Value Score
50
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
0
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
127.6%

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 →0.00%
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
$0
Avg Yield on Cost
0.00%

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 →
-3.6%
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 →
-21.0%
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 →
53.2% 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 →
0.81
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is GraniteShares 1.75x Long BABA Daily ETF a high-risk investment?

GraniteShares 1.75x Long BABA Daily ETF (BABX.US) has an annualized volatility of 127.6% and experienced a maximum drawdown of 62.5% over the last 10 years. Its primary macro risk driver is VWO.US.

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

Over the past 10 years, BABX.US has generated a Compound Annual Growth Rate (CAGR) of 6.7%. It has had a positive return in 50% 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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