MicroSectors™ Gold -3X Inverse Leveraged ETN

10-Year Study

DULL.US · · US · ETF

Executive Summary: MicroSectors™ Gold -3X Inverse Leveraged ETN has compounded at -64.4% annually over the last 10 years, with a maximum drawdown of 96.9% and an annualized volatility of 87.6%.

1Y CAGR
-79.4%
3Y CAGR
-64.7%
5Y CAGR
-64.4%
10Y CAGR
-64.4%

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 →
96.9%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
-1.41
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
-2.01
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
45.8%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · +-42.6%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · -80.6%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
0%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
2026-35.1-28.132.6-7.2————————-42.6%
2025-17.9-5.5-23.8-17.6-2.6-2.21.7-13.7-28.7-14.3-15.8-7.2-80.6%
20245.1-0.6-21.9-9.5-4.7-0.3-14.7-6.2-13.8-11.98.64.3-51.7%
2023——-21.4-2.64.17.4-6.14.716.5-19.4-6.7-4.1-29.4%

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 87.6%. The dominant macroeconomic risk driver is SHV.US, accounting for 73.6% of variance. Idiosyncratic stock-specific factors contribute 0.3%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2023-02-0110000
2023-03-017862.917537563591
2023-04-017655.085380762708
2023-05-017972.5519580392
2023-06-018560.55527073392
2023-07-018037.22837875143
2023-08-018411.48400836061
2023-09-019800.055211578658
2023-10-017896.438853176638
2023-11-017365.224592814608
2023-12-017063.532752297196
2024-01-017422.013645147297
2024-02-017374.29506645108
2024-03-015757.384548645346
2024-04-015213.156130457074
2024-05-014970.619552786214
2024-06-014957.999763378949
2024-07-014227.6294514335295
2024-08-013967.346294908704
2024-09-013419.9629293686166
2024-10-013012.974720984344
2024-11-013273.2578775091692
2024-12-013412.86429782703
2025-01-012801.19887999369
2025-02-012646.212091335726
2025-03-012015.2226209725127
2025-04-011660.2910438932051
2025-05-011616.9105178057341
2025-06-011581.4173600978036
2025-07-011609.023149426194
2025-08-011388.1768347990694
2025-09-01989.8647316322911
2025-10-01847.892100800568
2025-11-01713.8068383483852
2025-12-01662.538943881374
2026-01-01429.8615766849391
2026-02-01309.03498047876326
2026-03-01409.7487873171117
2026-04-01380.2531845249833
Annual Return Matrix
YearAnnual Return
2024-0.5168332309753783
2025-0.8058701178645713
2026-0.4260666666666667
Total Factor Risk
0.8764367001444043
VTI.US Exposure
-0.0019252739960415237
VEA.US Exposure
-0.0049289103202823994
VWO.US Exposure
0.0015289116482230347
QQQ.US Exposure
0.0029913384819900157
VTV.US Exposure
0.02095960185495851
IJR.US Exposure
0.002894055940693341
QUAL.US Exposure
-0.001968840300136964
SHV.US Exposure
0.7362953490868097
TLT.US Exposure
0.005518732818862916
LQD.US Exposure
-0.0030927985748361005
HYG.US Exposure
-0.0003657751634047747
GLD.US Exposure
0.24344153739065527
USO.US Exposure
-0.000010320287809004457
VNQ.US Exposure
-0.005320741715499441
BTC-USD.CC Exposure
0.00025200458336713114
CPER.US Exposure
-0.0072500202842677225
VIX.INDX Exposure
-0.00005554482484377585
UUP.US Exposure
0.005786050003163633
TIP.US Exposure
0.0027059022562003618
Idiosyncratic Exposure
0.0025447414021980016
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
87.6%

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 →
+0.0%
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 →
-54.9%
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 →
78.9% 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 →
-1.50
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is MicroSectors™ Gold -3X Inverse Leveraged ETN a high-risk investment?

MicroSectors™ Gold -3X Inverse Leveraged ETN (DULL.US) has an annualized volatility of 87.6% and experienced a maximum drawdown of 96.9% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, DULL.US has generated a Compound Annual Growth Rate (CAGR) of -64.4%. It has had a positive return in 0% 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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