Doubleline Etf Trust - Commercial Real Estate ETF

10-Year Study

DCMB.US · · US · ETF

Executive Summary: Doubleline Etf Trust - Commercial Real Estate ETF has compounded at 6.1% annually over the last 10 years, with a maximum drawdown of 0.8% and an annualized volatility of 7.8%.

1Y CAGR
+4.2%
3Y CAGR
+6.0%
5Y CAGR
+6.1%
10Y CAGR
+6.1%

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 →
0.8%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
1.11
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
1.17
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
1.4%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +6.9%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · 0.5%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
100%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20260.50.4-0.80.3————————0.5%
20250.50.70.40.70.10.70.20.90.30.50.60.25.9%
20240.9-0.00.70.10.90.70.90.90.8-0.61.00.56.9%
2023———0.60.40.40.50.80.20.31.20.95.4%

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 7.8%. The dominant macroeconomic risk driver is SHV.US, accounting for 93.5% of variance. Idiosyncratic stock-specific factors contribute 0.4%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2023-03-0110000
2023-04-0110061.020500949693
2023-05-0110101.43158157107
2023-06-0110146.08917209212
2023-07-0110195.454849675858
2023-08-0110275.053831436635
2023-09-0110290.724376120766
2023-10-0110324.46566673667
2023-11-0110447.291349813177
2023-12-0110540.645331031601
2024-01-0110637.48421983074
2024-02-0110632.891527058808
2024-03-0110708.082446912855
2024-04-0110714.659921485723
2024-05-0110816.4146070709
2024-06-0110891.5824480668
2024-07-0110988.167469426282
2024-08-0111087.84505777792
2024-09-0111176.329399926608
2024-10-0111107.969822085082
2024-11-0111214.29412158404
2024-12-0111269.129488549423
2025-01-0111328.257523130786
2025-02-0111404.002335580446
2025-03-0111452.398701121861
2025-04-0111527.935803848168
2025-05-0111539.890652370084
2025-06-0111625.143954377712
2025-07-0111650.969196648026
2025-08-0111752.12383192129
2025-09-0111783.788025303658
2025-10-0111838.854180850549
2025-11-0111908.736963330002
2025-12-0111929.623329956126
2026-01-0111991.68237952259
2026-02-0112043.863677800675
2026-03-0111949.748094263288
2026-04-0111987.158923325107
Annual Return Matrix
YearAnnual Return
20240.06911191247211113
20250.05861090176289396
20260.004822917855629605
Total Factor Risk
0.07779142410414895
VTI.US Exposure
0.026531636840024863
VEA.US Exposure
0.004069230025612187
VWO.US Exposure
-0.001196462013320248
QQQ.US Exposure
-0.0036220966669123903
VTV.US Exposure
-0.0004027213181350435
IJR.US Exposure
0.0003305731035178953
QUAL.US Exposure
-0.00029960814889672317
SHV.US Exposure
0.9351559096955138
TLT.US Exposure
-0.003378448478255726
LQD.US Exposure
0.016472523803224157
HYG.US Exposure
0.00009551657706264027
GLD.US Exposure
-0.0010132517976968894
USO.US Exposure
0.0011857418415014318
VNQ.US Exposure
-0.00013435441072331595
BTC-USD.CC Exposure
-0.0003082015403928967
CPER.US Exposure
0.000325302732425131
VIX.INDX Exposure
-0.0000014940194651892928
UUP.US Exposure
-0.0006067216214864763
TIP.US Exposure
0.02297827879930165
Idiosyncratic Exposure
0.0038186465971011157
Value Score
50
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
65.2
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
7.8%

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 →5.43%
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
$87
Avg Yield on Cost
0.87%
Annual Income Simulation Table
Historical Realised Yields
YearAnnual PayoutYield on CostQuality
2026$86.90.87%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 →
-0.1%
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 →
+1.1%
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 →
0.7% 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 Doubleline Etf Trust - Commercial Real Estate ETF a high-risk investment?

Doubleline Etf Trust - Commercial Real Estate ETF (DCMB.US) has an annualized volatility of 7.8% and experienced a maximum drawdown of 0.8% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, DCMB.US has generated a Compound Annual Growth Rate (CAGR) of 6.1%. It has had a positive return in 100% 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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