SPDR SAMPP ETF Forward View - Polynomial Regression
| GXC ETF | USD 97.53 0.08 0.08% |
Polynomial Regression is applied to SPDR SAMPP China's daily closing prices, and the resulting forecast is presented with accuracy metrics. Wide deviation between fitted and observed values suggests the model's assumptions may not match current market conditions. The Polynomial Regression model projects SPDR SAMPP at 98.28 for the next trading day, above the most recent closing price. This Polynomial Regression output is provided as analytical reference and does not constitute a trading recommendation.
Polynomial Regression Price Forecast For the 11th of May 2026
Over a 90-day horizon, the Polynomial Regression model forecasts SPDR SAMPP at 98.28 for the next trading day, with a mean absolute deviation of 1.36 , mean absolute percentage error of 0.01 , and sum of absolute errors of 83.11 .This represents a very tight forecast — the model closely tracks SPDR SAMPP's recent price behavior. This output is intended for short-term analytical reference.
ETF Forecast Pattern
| Backtest SPDR SAMPP | SPDR SAMPP Price Prediction | Research Analysis |
Forecasted Value
SPDR SAMPP's next-session forecast estimates practical downside and upside boundaries based on the model's historical fit. The current forecast range spans downside near 97.08 and upside near 99.47. The narrow range indicates limited short-term dispersion.
Model Predictive Factors
The table below summarizes the Polynomial Regression model's error metrics for SPDR SAMPP ETF. Lower MAD and MAPE values indicate tighter forecast accuracy. AIC measures relative model quality — lower values indicate less information loss and a better-fitting model. A large Bias suggests systematic over- or under-prediction.| AIC | Akaike Information Criteria | 119.0627 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.3625 |
| MAPE | Mean absolute percentage error | 0.0142 |
| SAE | Sum of the absolute errors | 83.111 |
Other Forecasting Options for SPDR SAMPP
SPDR SAMPP's daily price returns decompose into trend, seasonal, and residual components. Divergence between short-term and long-term averages in SPDR SAMPP often signals an upcoming reversal or acceleration.SPDR SAMPP Comparable Funds
These peer funds are related to SPDR SAMPP and help frame its category context. Useful comparisons usually include net asset value behavior, total return, volatility, distribution profile, and leverage. Category-relative analysis helps separate fund-specific behavior from broader market moves affecting the whole group. Taken together, these peers help define a more relevant comparison frame for SPDR SAMPP.
| Risk & Return | Correlation |
SPDR SAMPP Market Strength Events
Market strength indicators for SPDR SAMPP ETF provide a framework for assessing security responsiveness. A rising Accumulation/Distribution line alongside rising price confirms institutional buying interest in SPDR SAMPP.
SPDR SAMPP Risk Indicators
Assessing SPDR SAMPP's risk indicators is a structured way to evaluate the risk-return trade-off for spdr sampp etf. The level of risk embedded in SPDR SAMPP's feeds directly into exposure calibration.
| Mean Deviation | 0.8856 | |||
| Standard Deviation | 1.22 | |||
| Variance | 1.48 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
More Resources for SPDR SAMPP ETF Analysis
SPDR SAMPP China can be assessed through both market price and NAV, which can tell different stories during volatile periods.
The distinction between SPDR SAMPP's trading price and NAV is an important analytical consideration. Premium-to-NAV history and bid-ask spread trends are among factors that shape perceived value.