SPDR SAMPP Transportation ETF Performance
| XTN ETF | USD 104.72 0.04 0.04% |
Risk-Adjusted Performance
0High
0 · Weak
The last 90 days of data show SPDR SAMPP Transportation underperforming relative to its volatility profile. Return efficiency below zero signals that holders have absorbed volatility without adequate compensation. SPDR SAMPP is delivering weak return efficiency relative to its risk profile, with recent data suggesting continued pressure on shareholder returns. Learn More
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Relative Risk vs. Return Landscape
If you had invested $ 10,511 in SPDR SAMPP Transportation on February 7, 2026 and sold it today, you would have lost $ 39.00 , a decline of 0.37% over 90 days. SPDR SAMPP Transportation is generating a 0.0209% daily return assuming volatility of 2.32% on return distribution over 90 days investment horizon. In relative terms, SPDR SAMPP exhibits above-average volatility, exceeding roughly 80% of comparable etfs, and XTN delivers lower expected returns than 99% of comparable equities over the next 90 days. Expected Return |
| Risk |
Target Price Odds to finish over Current Price
A fundamental principle of ETF forecasting is that prices tend to revert toward historical averages. This pattern serves as a foundation for forecasting, even though some ETFs exhibit persistent deviations. One possible explanation is that these ETFs carry additional risk requiring compensation through extra returns.
| Current Price | Horizon | Target Price | Odds moving above the current price in 90 days |
| 104.72 | 90 days | 104.72 | about 24.75 % |
According to our probability model, the chance of SPDR SAMPP moving above the current price in 90 days from now is about 24.75 %. Based on past return behavior, the distribution of outcomes has been weighted above current levels over this period. (This distribution highlights the price region that has carried the highest probability weight for SPDR SAMPP ETF over a 90-day horizon).
SPDR SAMPP Price Density |
| Price |
Predictive Modules for SPDR SAMPP
Forecasting SPDR SAMPP Transportation involves applying various models to estimate future ETF price behavior. Despite uncertainty, systematic forecasting provides investors with structured context for evaluating SPDR SAMPP Transportation. Comparing results across methods can improve accuracy, even in unpredictable ETF markets.The concept of mean reversion suggests that SPDR SAMPP's price will eventually return toward its long-run average. Positions sized too aggressively against the trend often suffer sustained losses before reversion occurs in SPDR SAMPP. The mean reversion framework for SPDR SAMPP is built on the premise that markets are not perfectly efficient.
Primary Risk Indicators
Market volatility over the last 10-20 years has created both risk and opportunity across ETF markets including SPDR SAMPP. The pattern of corrections and recoveries in SPDR SAMPP mirrors the broader ETF market experience. Implementing a hedging strategy and tracking SPDR SAMPP's volatility limits the impact of adverse moves.α | Alpha over Dow Jones | 0.05 | |
β | Beta against Dow Jones | 1.68 | |
σ | Overall volatility | 6.99 | |
Ir | Information ratio | 0.02 |
Investor Alerts and Insights
Real-time alerts for SPDR SAMPP track important ETF developments as they happen. Notifications for SPDR SAMPP Transportation highlight significant technical and fundamental shifts that may signal emerging risks. Each alert is generated from real-time data feeds monitoring SPDR SAMPP price action and volume.| Latest headline from news.google.com: XTN Stock Price, Quote Chart SS SPDR SP TRANSPORT ETF - Chart Mill |
SPDR SAMPP Fundamentals Growth
Investors assess SPDR SAMPP ETF by examining SPDR SAMPP's underlying financial health and growth trajectory. Core fundamentals including revenue growth, earnings quality, and debt management directly influence SPDR SAMPP ETF. These fundamentals can have a significant impact on SPDR SAMPP ETF performance across market cycles.
Performance Metrics & Calculation Methodology
Drawdown and recovery analysis for SPDR SAMPP reveals how the fund behaves during stress episodes and subsequent rebounds. Comparing drawdown severity across periods reveals whether risk characteristics are stable or shifting.
SPDR SAMPP Transportation data is compiled from fund disclosures and market reference feeds and standardized for comparability. Return and risk statistics are calculated from historical price series.
Editorial review and methodology oversight provided by: Ellen Johnson, Member of Macroaxis Editorial Board