Atlas Energy Solutions Inc.

10-Year Study

AESI.US · Energy · US · Common Stock

Executive Summary: Atlas Energy Solutions Inc. has compounded at -3.9% annually over the last 10 years, with a maximum drawdown of 61.7% and an annualized volatility of 212.2%.

1Y CAGR
+14.2%
3Y CAGR
-1.5%
5Y CAGR
-3.9%
10Y CAGR
-3.9%

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 →
61.7%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.07
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.11
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
48.1%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · +42.7%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · -55.3%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
67%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
202623.9-17.536.22.4————————42.7%
20253.5-14.6-7.9-24.2-8.510.0-2.8-8.0-2.98.9-30.49.3-55.3%
20240.99.519.9-1.89.8-17.76.60.53.4-10.221.8-5.933.9%
2023———5.9-12.711.113.88.64.4-18.1-5.50.93.6%

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 212.2%. The dominant macroeconomic risk driver is SHV.US, accounting for 95.2% of variance. Idiosyncratic stock-specific factors contribute 0.8%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2023-03-0110000
2023-04-0110593.084738619975
2023-05-019253.03061231209
2023-06-0110283.7351103268
2023-07-0111699.579237095617
2023-08-0112703.220581166417
2023-09-0113264.106092831227
2023-10-0110865.428302396176
2023-11-0110263.717595000888
2023-12-0110359.986040416945
2024-01-0110450.262400653202
2024-02-0111446.463023566675
2024-03-0113728.459770720434
2024-04-0113479.6236180342
2024-05-0114800.911323724047
2024-06-0112179.275286928694
2024-07-0112979.844205785324
2024-08-0113041.806317369805
2024-09-0113480.87471274207
2024-10-0112101.904956310455
2024-11-0114740.52954229688
2024-12-0113871.21626159732
2025-01-0114359.011503486603
2025-02-0112260.662290030094
2025-03-0111286.388748049281
2025-04-018559.660755792896
2025-05-017834.552601947757
2025-06-018621.227784838049
2025-07-018382.663778174323
2025-08-017710.694225868689
2025-09-017486.814120249955
2025-10-018151.869728117365
2025-11-015676.0191483337385
2025-12-016202.795867436639
2026-01-017684.355389913543
2026-02-016341.07475620115
2026-03-018639.138193287547
2026-04-018849.848880928706
Annual Return Matrix
YearAnnual Return
20240.3389222927021496
2025-0.5528297050195103
20260.4267515923566878
Total Factor Risk
2.1224991333870733
VTI.US Exposure
-0.0015089513102184496
VEA.US Exposure
0.0004615173692750177
VWO.US Exposure
0.0012951067094842616
QQQ.US Exposure
-0.00004153157138043531
VTV.US Exposure
0.012243948425950831
IJR.US Exposure
0.002875331764775309
QUAL.US Exposure
0.00030306991234748537
SHV.US Exposure
0.9522391775395133
TLT.US Exposure
0.0004784257334090485
LQD.US Exposure
0.0009198398605385223
HYG.US Exposure
0.0005586526958079775
GLD.US Exposure
0.0006229701336490295
USO.US Exposure
0.009859348550940335
VNQ.US Exposure
-0.00004280736334232023
BTC-USD.CC Exposure
0.0009113001718139593
CPER.US Exposure
0.0014517332324225905
VIX.INDX Exposure
0.0012173177840991139
UUP.US Exposure
0.00007478455284567143
TIP.US Exposure
0.00781222900177861
Idiosyncratic Exposure
0.008268536806290014
Value Score
50
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
73.8
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
212.2%

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 →6.15%
Market Cap$1.5B
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 →
+11.8%
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 →
+18.6%
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 →
6.3% 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 →
0.57
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Atlas Energy Solutions Inc. a high-risk investment?

Atlas Energy Solutions Inc. (AESI.US) has an annualized volatility of 212.2% and experienced a maximum drawdown of 61.7% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, AESI.US has generated a Compound Annual Growth Rate (CAGR) of -3.9%. It has had a positive return in 67% 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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