Alpha Architect 1-3 Month Box ETF

10-Year Study

BOXX.US · · US · ETF

Executive Summary: Alpha Architect 1-3 Month Box ETF has compounded at 4.7% annually over the last 10 years, with a maximum drawdown of 0.0% and an annualized volatility of 1.7%.

1Y CAGR
+3.9%
3Y CAGR
+4.7%
5Y CAGR
+4.7%
10Y CAGR
+4.7%

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 →
0.0%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.76
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.00
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
0.3%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +5.2%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · 1.1%
% 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.
20260.30.30.40.1————————1.1%
20250.40.30.30.40.40.30.30.40.30.30.40.44.4%
20240.40.50.40.40.40.40.40.40.40.40.40.45.2%
20230.30.30.40.30.40.40.40.50.50.50.40.55.0%

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 1.7%. The dominant macroeconomic risk driver is SHV.US, accounting for 98.8% of variance. Idiosyncratic stock-specific factors contribute 0.3%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2022-12-0110000
2023-01-0110034.958940774146
2023-02-0110068.926209589366
2023-03-0110111.878627365739
2023-04-0110146.847585028358
2023-05-0110183.809903497297
2023-06-0110226.271493738444
2023-07-0110263.233812207382
2023-08-0110310.683812908565
2023-09-0110357.632969186048
2023-10-0110406.585503158325
2023-11-0110450.549626670567
2023-12-0110504.49057110288
2024-01-0110541.452889571818
2024-02-0110594.40216204521
2024-03-0110635.36121901526
2024-04-0110679.315325639027
2024-05-0110727.266170763909
2024-06-0110770.729449852452
2024-07-0110819.171122512556
2024-08-0110867.322305406915
2024-09-0110911.396614692372
2024-10-0110958.475990520017
2024-11-0111001.548610958074
2024-12-0111046.624609090926
2025-01-0111095.707362613364
2025-02-0111130.766472272251
2025-03-0111167.82895962593
2025-04-0111209.89989121659
2025-05-0111250.969133959856
2025-06-0111287.02993246614
2025-07-0111323.09073097242
2025-08-0111369.16841795267
2025-09-0111405.229216458949
2025-10-0111436.281570728248
2025-11-0111479.354191166307
2025-12-0111529.438633536141
2026-01-0111564.497743195026
2026-02-0111602.561919396101
2026-03-0111648.639606376351
2026-04-0111655.651428308127
Annual Return Matrix
YearAnnual Return
20230.05044905711028802
20240.051609741026320766
20250.04370692782009433
20260.010947002606429335
Total Factor Risk
0.017379531038379716
VTI.US Exposure
-0.0006339142132971798
VEA.US Exposure
0.00008501506657044516
VWO.US Exposure
0.0010733918617008523
QQQ.US Exposure
0.000545688237207663
VTV.US Exposure
0.0006629944535545163
IJR.US Exposure
-0.00020479135027264245
QUAL.US Exposure
-0.0003861493838247424
SHV.US Exposure
0.9879964929490238
TLT.US Exposure
-0.000158593060791887
LQD.US Exposure
0.001963940375849178
HYG.US Exposure
0.002570813216954789
GLD.US Exposure
0.000013263698080498052
USO.US Exposure
0.0009508962367296838
VNQ.US Exposure
0.00000799276951532731
BTC-USD.CC Exposure
0.00012929798959226111
CPER.US Exposure
0.00007635688476520266
VIX.INDX Exposure
0.0002540156389610306
UUP.US Exposure
-0.00013132374187304903
TIP.US Exposure
0.002290019638269629
Idiosyncratic Exposure
0.0028945927332848236
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
1.7%

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$430.7B
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 →
+0.4%
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 →
+1.6%
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 →
1.00
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Alpha Architect 1-3 Month Box ETF a high-risk investment?

Alpha Architect 1-3 Month Box ETF (BOXX.US) has an annualized volatility of 1.7% and experienced a maximum drawdown of 0.0% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, BOXX.US has generated a Compound Annual Growth Rate (CAGR) of 4.7%. 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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