UBS ETF (Switzerland) Performance
| USMUFS Etf | CHF 24.80 -0.10 -0.40% |
The etf owns a Beta (Systematic Risk) of 0.24, which signifies relatively modest fluctuations relative to the market. UBS ETF moves in the same direction as the market but with less intensity, offering a degree of cushion during selloffs.
Risk-Adjusted Performance
Weak
Weak | Strong |
UBS ETF plc has delivered negative risk-adjusted returns across the last 90 days, suggesting that volatility was not compensated by return. Used correctly, this score supports evaluation of raw price movement versus actual return efficiency. Despite somewhat strong primary indicators, UBS ETF is not utilizing all of its potential. The current price disturbance may contribute to short-term losses for investors. Learn More
UBS |
Relative Risk vs. Return Landscape
If you had invested ₣ 2,536 in UBS ETF plc on December 21, 2025 and sold it today you would have lost ₣ 56.00 from holding UBS ETF plc or given up 2.21% of portfolio value over 90 days. UBS ETF plc is generating negative expected returns and shows 0.684% volatility on return distribution over a 90-day horizon. Simply put, 6% of etfs are less volatile than UBS, and 99% of all equity instruments are likely to generate higher returns than the ETF over the next 90 trading days. Expected Return |
| Risk |
Target Price Odds to finish over Current Price
Prices of ETFs like UBS Etf tend to oscillate around a central value over time, a phenomenon known as mean reversion. Although this tendency is a useful forecasting input, some instruments remain persistently underpriced or overpriced before the market corrects the discrepancy.
| Current Price | Horizon | Target Price | Odds moving above the current price in 90 days |
| 24.80 | 90 days | 24.80 | close to 99 |
Under a normal probability framework, the likelihood of UBS ETF moving above the current price in 90 days from now is close to 99 (The distribution above models the probability of UBS Etf reaching different price points within 90 days).
UBS ETF Price Density |
| Price |
Predictive Modules for UBS ETF
The challenge of forecasting UBS ETF plc mirrors the broader difficulty of predicting ETF market movements. No single technique offers reliable accuracy, but investors who apply multiple methods and compare the results are better positioned to identify potential outcomes and manage risk effectively.While mean reversion in UBS ETF is a statistically observable tendency, it operates on uncertain timelines. Positions sized too aggressively against the trend can suffer sustained losses before reversion occurs.
Primary Risk Indicators
The etf market has been marked by significant volatility in the last 10-20 years, and UBS ETF has not been spared. Both sharp declines and strong rallies have tested investor discipline. A hedging strategy built around UBS ETF's risk indicators can help those holding UBS ETF plc manage downside risk more effectively.α | Alpha over Dow Jones | -0.0217 | |
β | Beta against Dow Jones | 0.24 | |
σ | Overall volatility | 0.44 | |
Ir | Information ratio | 0.08 |
Investor Alerts and Insights
Investors who use alerts for UBS ETF can respond more quickly to important ETF events. Notifications for UBS ETF plc highlight significant technical and fundamental shifts that may create new opportunities or signal emerging risks.| UBS ETF plc generated a negative expected return over the last 90 days | |
| The fund keeps 99.78% of its net assets in stocks |
UBS ETF Fundamentals Growth
Investor sentiment toward UBS Etf is largely driven by UBS ETF's fundamental metrics. Revenue growth rates, earnings per share trends, profit margin changes, and leverage ratios are among the most impactful factors determining UBS Etf market behavior.
Performance Metrics & Calculation Methodology
UBS ETF performance is typically evaluated relative to its benchmark and tracking difference over time. Benchmark comparison clarifies whether outcomes reflect exposure or implementation effects.
Data shown for UBS ETF plc is aggregated from fund disclosures and market reference feeds and normalized across reporting formats. Source publication cadence can introduce delays. Return and risk statistics are calculated from historical price series.