MTU Aero Engines NA O.N. (0FC9.LSE)

10-Year Study

0FC9.LSE · Unknown · Common Stock

About MTU Aero Engines NA O.N. (0FC9.LSE)

Unknown

MTU Aero Engines AG, together with its subsidiaries, engages in the development, manufacture, marketing, and maintenance of commercial and military aircraft engines, and aero-derivative industrial gas turbines in Germany, other European countries, North America, Asia, and internationally. It operates through two segments: Original Equipment Manufacturing Business; and Maintenance, Repair, and Overhaul Business....

Source: EODHD Financial Datasets
Fundamentals updated: Feb 23, 2026

Fundamental Snapshot

MTU Aero Engines NA O.N. (0FC9.LSE) operates in the Unknown market. Detailed fundamentals are summarized below as reported in trailing financial disclosures.

Executive Summary: MTU Aero Engines NA O.N. has compounded at 15.5% annually over the last 10 years, with a maximum drawdown of 52.3% and an annualized volatility of 46.2%.

1Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
-5.7%
3Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+29.1%
5Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+14.1%
10Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+15.5%

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

View full price history data
DateValue
2016-08-01$10,000
2016-09-01$9,825
2016-10-01$10,397
2016-11-01$10,817
2016-12-01$11,947
2017-01-01$12,115
2017-02-01$13,080
2017-03-01$13,337
2017-04-01$14,383
2017-05-01$13,996
2017-06-01$14,115
2017-08-01$13,047
2017-09-01$14,917
2017-10-01$16,013
2017-11-01$16,639
2017-12-01$16,622
2018-01-01$15,976
2018-02-01$15,257
2018-03-01$15,177
2018-04-01$16,177
2018-05-01$18,245
2018-06-01$18,707
2018-07-01$20,490
2018-08-01$21,361
2018-09-01$21,968
2018-10-01$21,190
2018-11-01$20,682
2018-12-01$17,918
2019-01-01$21,224
2019-02-01$21,269
2019-03-01$22,769
2019-04-01$23,996
2019-05-01$22,205
2019-06-01$23,973
2019-07-01$25,930
2019-08-01$28,413
2019-09-01$27,898
2019-10-01$27,395
2019-11-01$28,161
2019-12-01$29,134
2020-01-01$31,400
2020-02-01$25,255
2020-03-01$15,259
2020-04-01$14,990
2020-05-01$16,581
2020-06-01$17,761
2020-07-01$16,804
2020-08-01$18,062
2020-09-01$16,122
2020-10-01$16,728
2020-11-01$23,247
2020-12-01$24,781
2021-01-01$21,997
2021-02-01$22,733
2021-03-01$23,236
2021-04-01$24,128
2021-05-01$24,716
2021-06-01$23,985
2021-07-01$24,287
2021-08-01$22,392
2021-09-01$22,516
2021-10-01$22,158
2021-11-01$19,075
2021-12-01$20,669
2022-01-01$21,535
2022-02-01$24,817
2022-03-01$24,236
2022-04-01$22,308
2022-05-01$21,412
2022-06-01$20,188
2022-07-01$21,831
2022-08-01$20,571
2022-09-01$17,861
2022-10-01$21,170
2022-11-01$23,293
2022-12-01$23,712
2023-01-01$26,654
2023-02-01$26,703
2023-03-01$26,783
2023-04-01$27,559
2023-05-01$25,882
2023-06-01$27,998
2023-07-01$25,065
2023-08-01$25,497
2023-09-01$20,433
2023-10-01$20,859
2023-11-01$22,130
2023-12-01$23,040
2024-01-01$25,277
2024-02-01$26,258
2024-03-01$27,790
2024-04-01$26,913
2024-05-01$27,560
2024-06-01$28,243
2024-07-01$31,166
2024-08-01$32,230
2024-09-01$33,348
2024-10-01$35,879
2024-11-01$38,175
2024-12-01$38,051
2025-01-01$39,366
2025-02-01$39,481
2025-03-01$38,286
2025-04-01$36,085
2025-05-01$42,426
2025-06-01$45,334
2025-07-01$45,335
2025-08-01$45,839
2025-09-01$45,385
2025-10-01$45,455
2025-11-01$42,138
2025-12-01$42,450
2026-01-01$44,760
2026-02-01$43,920
2026-03-01$37,063
2026-04-01$34,783
2026-05-01$37,987
2026-06-01$43,662
2026-07-01$43,374
2026-08-01$43,002
Max DrawdownMax DrawdownThe largest peak-to-trough decline in the asset's value over the measurement period.Click for full definition →
52.3%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.55
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.69
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
31.0%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · +65.2%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2021 · -16.6%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
70%

Annual Returns

View full annual returns data
YearReturn
201739.1%
20187.8%
201962.6%
2020-14.9%
2021-16.6%
202214.7%
2023-2.8%
202465.2%
202511.6%
20261.3%

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20265.4-1.9-15.6-6.29.214.9-0.7-0.91.3%
20253.50.3-3.0-5.717.66.90.01.1-1.00.2-7.30.711.6%
20249.73.95.8-3.22.42.510.33.43.57.66.4-0.365.2%
202312.40.20.32.9-6.18.2-10.51.7-19.92.16.14.1-2.8%
20224.215.2-2.3-8.0-4.0-5.78.1-5.8-13.218.510.01.814.7%
2021-11.23.32.23.82.4-3.01.3-7.80.6-1.6-13.98.4-16.6%
20207.8-19.6-39.6-1.810.67.1-5.47.5-10.73.839.06.6-14.9%
201918.50.27.15.4-7.58.08.29.6-1.8-1.82.83.562.6%
2018-3.9-4.5-0.56.612.82.59.54.32.8-3.5-2.4-13.47.8%
20171.48.02.07.8-2.70.9-7.614.37.33.9-0.139.1%
2016-1.85.84.010.519.5%

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.

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
46.2%
View full factor risk breakdown
FactorRisk Exposure
VTI.US-5.2%
VEA.US6.6%
VWO.US3.5%
QQQ.US-1.8%
VTV.US2.6%
IJR.US8.3%
QUAL.US9.5%
SHV.US2.7%
TLT.US-0.6%
LQD.US3.0%
HYG.US23.5%
GLD.US-0.3%
USO.US1.3%
VNQ.US-4.2%
BTC-USD.CC0.2%
CPER.US0.7%
VIX.INDX-0.4%
UUP.US-0.3%
TIP.US25.7%
Idiosyncratic25.1%

MTU Aero Engines NA O.N. Business Fundamentals

Company financial statements are not available for 0FC9.LSE from our data provider. Return, risk, and factor analysis above are computed independently from daily price history.

Dividend & Income Analysisi10-Year historical income simulation on a $10,000 initial investment, cumulative dividend income generated, average yield on cost, and annual payout table.

Income Simulation

Based on $10,000 initial investment.

Total Income Generated
$432
Avg Yield on Cost
4.32%
Annual Income Simulation Table
Historical Realised Yields
YearAnnual PayoutYield on CostQuality
2026$431.944.32%

Momentum & MacroiPrice momentum indicators: distance from 50/200-Day SMA, 52-Week High proximity, Golden Cross trend signal, RSI momentum gauge, Fibonacci retracement levels, and Beta (market sensitivity).

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 →
-0.6%
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 →
+3.6%
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 →
10.9% 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 →
0.93
Market sensitivity coefficient
Trend SignalGolden Cross & Death CrossTechnical chart patterns that occur when a short-term moving average crosses over a long-term moving average.Click for full definition →
✦ Golden Cross
Bullish — 50 SMA above 200 SMA
RSI (14-Day)Relative Strength Index (RSI)A momentum oscillator that measures the speed and change of price movements to identify overbought or oversold conditions.Click for full definition →
36
OversoldNeutralOverbought
Neutral
Fibonacci LevelsFibonacci RetracementTechnical levels based on mathematical ratios that indicate potential support and resistance areas.Click for full definition →
38.2% retracement+2.0%
50.0% retracement+6.8%
61.8% retracement+12.0%
% distance of current price from each 52-week Fibonacci support level.

In-Depth Analysis

0FC9.LSE — 10-Year Return & Risk Profile

MTU Aero Engines NA O.N. (0FC9.LSE) has delivered strong annualized growth of 15.5% over the last 10 years. A $10,000 investment at the start of the period would have grown to approximately $42,378, representing a total return of 324%. Over this period, 0FC9.LSE generated positive annual returns in 7 out of 10 calendar years (70%).

The best single calendar year for 0FC9.LSE was 2024, with a return of +65.2%. The worst year was 2021, when the asset declined 16.6%. This spread between best and worst year is a useful indicator of the range of outcomes an investor might have experienced in a given 12-month window.

The asset's Sharpe ratio of 0.55 is considered acceptable on a risk-adjusted basis. The Sharpe ratio measures return earned above the risk-free rate per unit of total volatility — a higher reading indicates more efficient return generation relative to the risk taken. Investors focused on risk-adjusted outcomes should weigh this figure alongside absolute CAGR when making allocation decisions.

0FC9.LSE — Drawdown, Volatility & Downside Risk

0FC9.LSE's annualized volatility of 31.0% is classified as high relative to the long-run US equity benchmark of approximately 15%. This above-average volatility means investors in 0FC9.LSE have historically experienced larger day-to-day price swings than the broader market, which requires a higher tolerance for short-term portfolio fluctuations.

The asset's maximum peak-to-trough decline over the study period was 52.3% — a severe bear-market collapse. Drawdown magnitude is a critical consideration for investors who may need to liquidate positions during market stress, as a larger decline requires proportionally greater subsequent gains to recover to the prior peak. A 52% drawdown, for example, requires a 109% gain just to break even.

When evaluating 0FC9.LSE for inclusion in a diversified US portfolio, it is important to note that historical volatility and drawdown metrics are backward-looking. They capture the risk environment of the past 10 years, which included the COVID-19 market crash (2020), the 2022 Federal Reserve rate hike cycle, and various geopolitical disruptions. Future risk may differ materially, particularly in response to structural changes in US monetary policy, sector regulation, or macroeconomic regime shifts.

0FC9.LSE — Macroeconomic Factor Risk Exposure

The macroeconomic factor model attributes 25.7% of 0FC9.LSE's return variance to Inflation-Linked Bonds (TIPS). This means that when Inflation-Linked Bonds (TIPS) rises or falls sharply, 0FC9.LSE tends to move in the same direction with meaningful magnitude. Investors who already hold significant exposure to this factor — through other funds or direct equity positions — should be aware of this concentration when sizing their 0FC9.LSE allocation.

The second-largest macro driver is High-Yield Corporate Credit, contributing 23.5% of variance. 25.1% of 0FC9.LSE's risk is attributable to idiosyncratic, stock-specific factors that are uncorrelated with the broader macro drivers. A higher idiosyncratic share generally indicates that the fund's performance is more dependent on the security selection or holdings composition of the individual underlying assets, rather than broad market forces.

For US investors building a diversified multi-asset portfolio, understanding 0FC9.LSE's factor exposures helps assess its marginal contribution to overall portfolio risk. Adding 0FC9.LSE alongside assets with low correlation to Inflation-Linked Bonds (TIPS) — such as US Treasury bonds, commodities, or assets with significant developed-market ex-US exposure — can reduce the overall portfolio's sensitivity to any single macroeconomic theme.

Compare this AssetiRun a head-to-head backtest and risk analysis against similar assets.

Frequently Asked Questions & Methodology

Is MTU Aero Engines NA O.N. a high-risk investment?

MTU Aero Engines NA O.N. (0FC9.LSE) has an annualized volatility of 46.2% and experienced a maximum drawdown of 52.3% over the last 10 years. Its primary macro risk driver is TIP.US.

What is the 10-year return of 0FC9.LSE?

Over the past 10 years, 0FC9.LSE has generated a Compound Annual Growth Rate (CAGR) of 15.5%. A $10,000 investment would have grown to approximately $42,378. It has had a positive return in 70% of calendar years.

What is 0FC9.LSE's Sharpe ratio?

0FC9.LSE has a Sharpe ratio of 0.55 and a Sortino ratio of 0.69 over the 10-year period. The Sharpe ratio measures risk-adjusted return — how much excess return is earned per unit of volatility. A reading below 1.0 suggests investors were not fully compensated on a risk-adjusted basis.

What is 0FC9.LSE's dividend yield?

0FC9.LSE does not pay a meaningful dividend. Its returns are driven primarily by price appreciation. Investors seeking regular income may wish to consider dividend-focused alternatives.

Is 0FC9.LSE above its 200-day moving average?

0FC9.LSE is currently above its 200-day moving average by 3.6%. The current trend signal is: Bullish — 50 SMA above 200 SMA. The 200-day SMA is a widely used long-term trend filter — assets trading above it tend to exhibit positive price momentum.

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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