Aeluma, Inc

10-Year Study

ALMU.US · Technology · US · Common Stock

Executive Summary: Aeluma, Inc has compounded at 85.6% annually over the last 10 years, with a maximum drawdown of 43.1% and an annualized volatility of 441.8%.

1Y CAGR
+23.8%
3Y CAGR
+66.8%
5Y CAGR
+85.6%
10Y CAGR
+85.6%

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 →
43.1%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
1.55
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
5.08
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
96.1%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +163.8%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · 1.0%
% 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.
2026-8.0-2.0-15.432.5————————1.0%
2025-9.2-8.012.845.635.814.835.13.0-29.41.3-14.022.5124.4%
202413.8-9.40.31.78.28.7-16.4-7.013.6-2.58.4128.4163.8%
20230.066.72.918.1-8.2-25.633.4-4.4-10.80.2-26.819.838.1%
2022———————————0.00.0%

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 441.8%. The dominant macroeconomic risk driver is SHV.US, accounting for 86.3% of variance. Idiosyncratic stock-specific factors contribute 1.4%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2022-11-0110000
2022-12-0110000
2023-01-0110000
2023-02-0116666.666666666664
2023-03-0117142.85714285714
2023-04-0120238.095238095237
2023-05-0118571.42857142857
2023-06-0113809.52380952381
2023-07-0118428.571428571428
2023-08-0117619.04761904762
2023-09-0115714.285714285712
2023-10-0115750
2023-11-0111523.809523809523
2023-12-0113809.52380952381
2024-01-0115714.285714285712
2024-02-0114238.095238095239
2024-03-0114285.714285714286
2024-04-0114523.809523809523
2024-05-0115714.285714285712
2024-06-0117083.333333333332
2024-07-0114285.714285714286
2024-08-0113285.714285714284
2024-09-0115095.238095238095
2024-10-0114714.285714285714
2024-11-0115952.38095238095
2024-12-0136428.57142857143
2025-01-0133095.23809523809
2025-02-0130447.61904761905
2025-03-0134333.33333333333
2025-04-0150000
2025-05-0167904.76190476191
2025-06-0177952.38095238095
2025-07-01105333.33333333333
2025-08-01108523.80952380951
2025-09-0176666.66666666667
2025-10-0177666.66666666666
2025-11-0166761.90476190475
2025-12-0181761.90476190478
2026-01-0175190.47619047618
2026-02-0173666.66666666666
2026-03-0162333.333333333336
2026-04-0182619.04761904763
Annual Return Matrix
YearAnnual Return
20230.38095238095238093
20241.637931034482759
20251.2444444444444445
20260.01048340128130465
Total Factor Risk
4.417687910969508
VTI.US Exposure
0.04622420000776
VEA.US Exposure
0.0060980666911601
VWO.US Exposure
-0.00010321648798896297
QQQ.US Exposure
0.0009317478458739259
VTV.US Exposure
0.021654761346955233
IJR.US Exposure
0.0013977540334537014
QUAL.US Exposure
0.0009027677195863983
SHV.US Exposure
0.863102978275402
TLT.US Exposure
-0.00004446632890050641
LQD.US Exposure
0.004543318925611165
HYG.US Exposure
-0.00014620496403894078
GLD.US Exposure
-0.00024251044300204264
USO.US Exposure
0.000258946537169519
VNQ.US Exposure
0.0022921185563919313
BTC-USD.CC Exposure
0.0005008143032091711
CPER.US Exposure
-0.00018913075542707357
VIX.INDX Exposure
-0.000045409656026659325
UUP.US Exposure
0.0023945894558296036
TIP.US Exposure
0.036731300131977174
Idiosyncratic Exposure
0.013737574805004035
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
441.8%

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 →0.00%
Market Cap$242.6M
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 →
+17.6%
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 →
+3.1%
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 →
27.8% 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 →
-1.33
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Aeluma, Inc a high-risk investment?

Aeluma, Inc (ALMU.US) has an annualized volatility of 441.8% and experienced a maximum drawdown of 43.1% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, ALMU.US has generated a Compound Annual Growth Rate (CAGR) of 85.6%. 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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