Atmus Filtration Technologies Inc.

10-Year Study

ATMU.US · Consumer Cyclical · US · Common Stock

Executive Summary: Atmus Filtration Technologies Inc. has compounded at 45.2% annually over the last 10 years, with a maximum drawdown of 21.3% and an annualized volatility of 117.1%.

1Y CAGR
+78.7%
3Y CAGR
+45.2%
5Y CAGR
+45.2%
10Y CAGR
+45.2%

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 →
21.3%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
1.43
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
5.19
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
33.6%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +67.3%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2026 · 17.7%
% 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.
202611.711.4-12.07.6————————17.7%
20256.7-4.8-7.6-5.63.91.36.814.61.30.911.42.633.2%
2024-4.96.935.1-6.11.8-6.77.216.44.73.911.2-9.567.3%
2023—————5.98.6-3.4-9.5-10.016.67.413.3%

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 117.1%. The dominant macroeconomic risk driver is SHV.US, accounting for 75.8% of variance. Idiosyncratic stock-specific factors contribute 1.9%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2023-05-0110000
2023-06-0110588.243878235997
2023-07-0111499.528159627976
2023-08-0111113.786494663827
2023-09-0110053.021237681074
2023-10-019045.32586171672
2023-11-0110549.669711739582
2023-12-0111325.920088725448
2024-01-0110766.618996196092
2024-02-0111509.159540417748
2024-03-0115549.669711739582
2024-04-0114604.626954246078
2024-05-0114869.830429326094
2024-06-0113876.582124546401
2024-07-0114869.830429326094
2024-08-0117313.525766375777
2024-09-0118124.84798957087
2024-10-0118829.93316405452
2024-11-0120933.416999873527
2024-12-0118945.996166905017
2025-01-0120222.591911585867
2025-02-0119245.78505482104
2025-03-0117784.587845002872
2025-04-0116787.156213213475
2025-05-0117440.825380147682
2025-06-0117658.893461362593
2025-07-0118866.221093696797
2025-08-0121613.207638949694
2025-09-0121889.939584975044
2025-10-0122079.259453832605
2025-11-0124597.573670334372
2025-12-0125229.40197881096
2026-01-0128174.70741032601
2026-02-0131389.545573942738
2026-03-0127614.82259774879
2026-04-0129701.621768866316
Annual Return Matrix
YearAnnual Return
20240.6727997388719957
20250.33164821509263454
20260.1772622194458422
Total Factor Risk
1.1708607517770555
VTI.US Exposure
0.14148136232953243
VEA.US Exposure
0.005375642128476246
VWO.US Exposure
-0.0004993411354281925
QQQ.US Exposure
0.01637134677464372
VTV.US Exposure
-0.018349639260604907
IJR.US Exposure
0.008539797717944402
QUAL.US Exposure
0.004951856396216117
SHV.US Exposure
0.758261325078738
TLT.US Exposure
0.0023819062712987357
LQD.US Exposure
0.000994623510201409
HYG.US Exposure
-0.0008512841325005521
GLD.US Exposure
0.005282037229444527
USO.US Exposure
0.0008530735628360864
VNQ.US Exposure
0.003119223949413262
BTC-USD.CC Exposure
0.00044022951233467673
CPER.US Exposure
-0.00044411395324907033
VIX.INDX Exposure
-0.0019167602148422347
UUP.US Exposure
0.002632607581027501
TIP.US Exposure
0.052347758881891
Idiosyncratic Exposure
0.01902834777262673
Value Score
40.8
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
4.3
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
117.1%

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 →23.0x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →0.36%
Market Cap$4.7B
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
$27
Avg Yield on Cost
0.27%
Annual Income Simulation Table
Historical Realised Yields
YearAnnual PayoutYield on CostQuality
2026$26.750.27%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 →
+0.3%
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 →
+21.5%
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 →
6.9% 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 →
1.59
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Atmus Filtration Technologies Inc. a high-risk investment?

Atmus Filtration Technologies Inc. (ATMU.US) has an annualized volatility of 117.1% and experienced a maximum drawdown of 21.3% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, ATMU.US has generated a Compound Annual Growth Rate (CAGR) of 45.2%. 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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