JPMorgan BetaBuilders MSCI US REIT

10-Year Study

BBRE.US · · US · ETF

Executive Summary: JPMorgan BetaBuilders MSCI US REIT has compounded at 6.6% annually over the last 10 years, with a maximum drawdown of 29.4% and an annualized volatility of 15.7%.

1Y CAGR
+14.3%
3Y CAGR
+11.9%
5Y CAGR
+4.9%
10Y CAGR
+6.6%

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 →
29.4%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.22
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.31
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
19.1%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2021 · +43.0%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -24.7%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
75%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20262.77.5-6.47.3————————10.9%
20251.03.5-3.5-2.82.1-0.5-1.04.50.9-1.82.1-2.22.1%
2024-4.21.82.1-7.14.72.96.36.32.6-3.04.4-7.58.2%
202310.6-4.7-2.70.9-3.05.12.8-3.0-6.7-4.410.410.113.9%
2022-7.0-3.26.6-4.6-6.1-7.48.9-6.0-12.14.85.7-5.2-24.7%
20210.34.04.38.11.02.54.91.8-5.57.8-0.88.843.0%
20201.1-7.8-21.47.90.23.14.10.9-3.2-2.710.83.3-7.5%
201912.00.93.2-0.20.21.11.53.42.71.5-1.5-0.726.1%
2018——————1.62.6-3.8-0.92.7-7.5-5.6%

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 15.7%. The dominant macroeconomic risk driver is VNQ.US, accounting for 93.2% of variance. Idiosyncratic stock-specific factors contribute 1.4%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2018-06-0110000
2018-07-0110156.37229166734
2018-08-0110424.701346637596
2018-09-0110025.782908234749
2018-10-019938.755527784668
2018-11-0110206.343787140433
2018-12-019440.473851525234
2019-01-0110575.839756246034
2019-02-0110668.27816553239
2019-03-0111004.647687268302
2019-04-0110979.895451192842
2019-05-0111003.955204411277
2019-06-0111124.608264058206
2019-07-0111286.133916521996
2019-08-0111670.075400110154
2019-09-0111983.480257796875
2019-10-0112167.084840422964
2019-11-0111982.143604840294
2019-12-0111900.221272429199
2020-01-0112037.010793070018
2020-02-0111095.507879810742
2020-03-018716.764848926008
2020-04-019402.661066681268
2020-05-019425.609626477968
2020-06-019715.228503238566
2020-07-0110111.570261243185
2020-08-0110204.18581730692
2020-09-019876.899093974756
2020-10-019610.599174818102
2020-11-0110648.389413708583
2020-12-0111001.765026072784
2021-01-0111032.347001549228
2021-02-0111475.74538532645
2021-03-0111966.747939460896
2021-04-0112933.341278097896
2021-05-0113057.295709505051
2021-06-0113386.225066591085
2021-07-0114044.164302025594
2021-08-0114303.974207429215
2021-09-0113522.692502182128
2021-10-0114575.234236352453
2021-11-0114452.890230194187
2021-12-0115731.745024591193
2022-01-0114636.784689365075
2022-02-0114167.925482402883
2022-03-0115105.14466450011
2022-04-0114410.938652460567
2022-05-0113530.744628426582
2022-06-0112533.037873981004
2022-07-0113651.768085880758
2022-08-0112836.973431204244
2022-09-0111282.510459711992
2022-10-0111821.004454436239
2022-11-0112493.405308605792
2022-12-0111849.71833662397
2023-01-0113102.935161058631
2023-02-0112487.221275650048
2023-03-0112150.594085874318
2023-04-0112260.747172898476
2023-05-0111898.465908907907
2023-06-0112506.59469139421
2023-07-0112851.934281766442
2023-08-0112464.868573195437
2023-09-0111623.518006164708
2023-10-0111107.98867548965
2023-11-0112261.616802532877
2023-12-0113494.300705044176
2024-01-0112934.001552449941
2024-02-0113171.104461844196
2024-03-0113446.471075152105
2024-04-0112486.01345671338
2024-05-0113069.583254154091
2024-06-0113452.542378340424
2024-07-0114294.472698460757
2024-08-0115188.548588140186
2024-09-0115585.470099234404
2024-10-0115123.664554862356
2024-11-0115783.149798535802
2024-12-0114606.057775616231
2025-01-0114751.12488203635
2025-02-0115273.659562544086
2025-03-0114742.798983499586
2025-04-0114333.493302241392
2025-05-0114634.578406774093
2025-06-0114559.033358348604
2025-07-0114419.940929601871
2025-08-0115067.992154008187
2025-09-0115208.018629399277
2025-10-0114930.816131307634
2025-11-0115243.061482815152
2025-12-0114910.927379483826
2026-01-0115313.533691706634
2026-02-0116455.325193170513
2026-03-0115410.159206640106
2026-04-0116540.677731361742
Annual Return Matrix
YearAnnual Return
20190.26055338530560723
2020-0.0754991210489494
20210.42992919657063733
2022-0.2467638956707603
20230.13878662105725237
20240.08238715698372423
20250.020872819247405472
20260.1092990603736903
Total Factor Risk
0.15713020514473455
VTI.US Exposure
-0.06468313342461185
VEA.US Exposure
0.012449507685695601
VWO.US Exposure
0.004125394576733824
QQQ.US Exposure
0.06751684979771451
VTV.US Exposure
0.0502457648612395
IJR.US Exposure
0.010035115688554962
QUAL.US Exposure
-0.02491403029419849
SHV.US Exposure
0.03132353173623435
TLT.US Exposure
0.03141895446449587
LQD.US Exposure
-0.06507437047529394
HYG.US Exposure
0.009103653837882083
GLD.US Exposure
-0.0037109686371311662
USO.US Exposure
-0.001320324774725556
VNQ.US Exposure
0.9321938800309103
BTC-USD.CC Exposure
-0.006639858934698365
CPER.US Exposure
0.0011648749950280539
VIX.INDX Exposure
-0.0026807921512819544
UUP.US Exposure
-0.0021078179354815556
TIP.US Exposure
0.007457914817099899
Idiosyncratic Exposure
0.014095854135834014
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
15.7%

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
$65
Avg Yield on Cost
0.65%
Annual Income Simulation Table
Historical Realised Yields
YearAnnual PayoutYield on CostQuality
2026$65.220.65%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 →
+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 →
+8.8%
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 →
0.0% 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 →
1.10
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is JPMorgan BetaBuilders MSCI US REIT a high-risk investment?

JPMorgan BetaBuilders MSCI US REIT (BBRE.US) has an annualized volatility of 15.7% and experienced a maximum drawdown of 29.4% over the last 10 years. Its primary macro risk driver is VNQ.US.

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

Over the past 10 years, BBRE.US has generated a Compound Annual Growth Rate (CAGR) of 6.6%. It has had a positive return in 75% 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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