Listed Funds Trust ETF Performance
| FEBZ ETF | USD 39.96 -0.02 -0.05% |
Risk-Adjusted Performance
0High
11 · Moderate
Across the last 90 days, the risk-adjusted return profile of Listed Funds Trust is weaker than 11% of the global equities and portfolios reviewed by Macroaxis. This score becomes more informative when compared with downside risk, Sharpe Ratio, and current trend stability. Recent data suggests Listed Funds is converting risk into modest positive returns, a constructive signal if sustained. Learn More
Relative Risk vs. Return Landscape
If you had invested $ 3,752 in Listed Funds Trust on February 12, 2026 and sold it today, you would have earned $ 244.25 , a return of 6.51% over 90 days. Listed Funds Trust is currently generating a 0.1024% daily expected return and carries 0.6777% risk (volatility on return distribution) over a 90-day horizon. In relative terms, Listed Funds exhibits above-average volatility, exceeding roughly 94% of comparable etfs, and FEBZ has trailed 98% of traded instruments in return over the 90-day horizon. Expected Return |
| Risk |
Target Price Odds to finish over Current Price
Historical averages are sometimes used as a secondary reference point when assessing Listed Funds ETF price behavior. In practice, valuation gaps may persist longer than expected when market sentiment or liquidity conditions dominate trading activity. Changes in interest rates, capital flows, or geopolitical developments can influence how investors value Listed Funds ETF.
| Current Price | Horizon | Target Price | Odds moving above the current price in 90 days |
| 39.96 | 90 days | 39.96 | roughly 2.03 % |
Applying a normal distribution to this ETF, the odds of Listed Funds moving above the current price in 90 days from now are roughly 2.03 %. Based on past return behavior, the distribution of outcomes has been weighted above current levels over this period. (The probability curve shows the outcome range with the heaviest concentration for Listed Funds ETF over 90 days). A tighter center suggests recent price behavior has been clustering into a narrower range for Listed Funds ETF.
Listed Funds Price Density |
| Price |
Predictive Modules for Listed Funds
For Listed Funds Trust, multiple forecasting techniques provide different perspectives on future ETF price direction. No method can consistently predict the ETF market with certainty, but disciplined forecasting sharpens analysis. Comparing the outputs of diverse models helps set realistic expectations for Listed Funds Trust price behavior.Tracking mean reversion in Listed Funds centers on spotting price extremes that have drifted well away from the historical norm. High prices relative to historical norms contrast with unusually low prices, where recovery expectations may emerge. Mean reversion in Listed Funds is the opposite of trend following: it bets on reversals rather than riding momentum.
Primary Risk Indicators
The ETF market's volatility over the past 10-20 years has tested even experienced investors in Listed Funds. Large corrections and rapid recoveries have created challenges for investors in Listed Funds Trust. A disciplined approach to monitoring Listed Funds' risk indicators supports more effective hedging decisions.α | Alpha over Dow Jones | 0.08 | |
β | Beta against Dow Jones | 0.68 | |
σ | Overall volatility | 1.07 | |
Ir | Information ratio | 0.12 |
Listed Funds Fundamentals Growth
Listed Funds' financial fundamentals are the foundation of Listed Funds ETF market pricing and valuation. Metrics like earnings growth, revenue consistency, and margin trends collectively determine market sentiment toward Listed Funds ETF. Listed Funds ETF market pricing reflects the collective assessment of Listed Funds's financial fundamentals.
| Total Asset TTM | 3.13 M | |||
Performance Metrics & Calculation Methodology
Drawdown and recovery analysis for Listed Funds reveals how the fund behaves during stress episodes and subsequent rebounds. Maximum drawdown depth defines the worst observed loss from peak, framing downside exposure.
Listed Funds Trust analytics rely on fund disclosures and market reference feeds, with quality checks and normalization applied. Return and risk statistics are calculated from historical price series.
Editorial review and methodology oversight provided by: Vlad Skutelnik, Macroaxis Contributor