Ea Bridgeway Blue Chip ETF

10-Year Study

BBLU.US · · US · ETF

Executive Summary: Ea Bridgeway Blue Chip ETF has compounded at 22.6% annually over the last 10 years, with a maximum drawdown of 7.3% and an annualized volatility of 12.7%.

1Y CAGR
+23.7%
3Y CAGR
+21.7%
5Y CAGR
+22.6%
10Y CAGR
+22.6%

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 →
7.3%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
1.60
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
3.03
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
11.8%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2023 · +31.1%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · 2.5%
% 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.
20260.6-0.5-3.35.9————————2.5%
20252.70.2-4.9-2.54.75.62.12.24.73.1-0.1-0.218.4%
20242.56.13.4-3.84.33.01.22.12.0-0.35.7-1.227.5%
20236.5-1.44.92.21.76.82.8-0.7-4.6-1.88.33.631.1%
2022——————————5.7-4.80.7%

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 12.7%. The dominant macroeconomic risk driver is VTI.US, accounting for 66.8% of variance. Idiosyncratic stock-specific factors contribute 2.9%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2022-10-0110000
2022-11-0110572.21021640422
2022-12-0110069.468325841864
2023-01-0110723.670942248851
2023-02-0110576.069429472196
2023-03-0111095.17779558985
2023-04-0111334.092847386306
2023-05-0111521.724822915483
2023-06-0112307.267082512752
2023-07-0112646.251441990169
2023-08-0112558.69126476026
2023-09-0111983.292434267445
2023-10-0111770.64468845447
2023-11-0112746.32074967113
2023-12-0113202.140013968632
2024-01-0113532.83061448099
2024-02-0114359.554002489
2024-03-0114842.86844759574
2024-04-0114283.238966918923
2024-05-0114893.74430776969
2024-06-0115338.902480400548
2024-07-0115516.96674570021
2024-08-0115847.656100903416
2024-09-0116165.625868408555
2024-10-0116114.750008234607
2024-11-0117030.506774201604
2024-12-0116829.35821311586
2025-01-0117280.719270642352
2025-02-0117319.408535436112
2025-03-0116468.268370847338
2025-04-0116055.594087496293
2025-05-0116803.565369920016
2025-06-0117737.23964399351
2025-07-0118106.067837344443
2025-08-0118512.292664587374
2025-09-0119381.488566598728
2025-10-0119982.44487685729
2025-11-0119966.96942000162
2025-12-0119926.528005228305
2026-01-0120044.050320701353
2026-02-0119939.58571926784
2026-03-0119273.62706066754
2026-04-0120418.814793201782
Annual Return Matrix
YearAnnual Return
20230.3111059677388537
20240.27474471527414623
20250.18403374346733492
20260.024705096033002416
Total Factor Risk
0.1265869515072093
VTI.US Exposure
0.6682008028356177
VEA.US Exposure
-0.04107950924297015
VWO.US Exposure
0.006736569466122907
QQQ.US Exposure
0.2085490719714675
VTV.US Exposure
0.25255564905659317
IJR.US Exposure
-0.12335758870394425
QUAL.US Exposure
-0.11160747399859484
SHV.US Exposure
0.15236264906485247
TLT.US Exposure
0.01703599018131925
LQD.US Exposure
-0.0013417566007990606
HYG.US Exposure
-0.03294601387778974
GLD.US Exposure
-0.0011224836621169427
USO.US Exposure
-0.0006917381832873889
VNQ.US Exposure
-0.04082878984329505
BTC-USD.CC Exposure
-0.0031111292498120446
CPER.US Exposure
0.0016017293660171908
VIX.INDX Exposure
0.016922467424623566
UUP.US Exposure
0.009688495493461836
TIP.US Exposure
-0.006889763491120385
Idiosyncratic Exposure
0.029322821993654505
Value Score
41.4
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
15
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
12.7%

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 →21.4x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →1.25%
Market Cap$622.6B
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 →
+3.7%
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 →
+5.5%
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 →
0.93
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Ea Bridgeway Blue Chip ETF a high-risk investment?

Ea Bridgeway Blue Chip ETF (BBLU.US) has an annualized volatility of 12.7% and experienced a maximum drawdown of 7.3% over the last 10 years. Its primary macro risk driver is VTI.US.

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

Over the past 10 years, BBLU.US has generated a Compound Annual Growth Rate (CAGR) of 22.6%. 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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