ZKB Silver Etf Forward View - Polynomial Regression
| ZSIL Etf | CHF 153.36 -3.64 -2.32% |
This page provides Polynomial Regression reference data for ZKB Silver ETF, calculated from historical daily prices. The model output shown here is derived from ZKB Silver's historical price series and is provided for informational purposes. Projected values and accuracy measures are included for reference.
The Polynomial Regression forecasted value of ZKB Silver ETF on the next trading day is expected to be 176.08 with a mean absolute deviation of 14.57 and the sum of the absolute errors of 903.31.A single variable polynomial regression model attempts to put a curve through the ZKB Silver historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm The Polynomial Regression reference information for ZKB Silver is based on available price data and is intended for informational purposes. Polynomial Regression Price Forecast For the 25th of March
Given 90 days horizon, the Polynomial Regression forecasted value of ZKB Silver ETF on the next trading day is expected to be 176.08 with a mean absolute deviation of 14.57 , mean absolute percentage error of 326.09 , and the sum of the absolute errors of 903.31 .Please note that although there have been many attempts to predict ZKB Etf prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that ZKB Silver's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Etf Forecast Pattern
| Backtest ZKB Silver | ZKB Silver Price Prediction | Research Analysis |
Forecasted Value
Forecasting ZKB Silver ETF for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of ZKB Silver etf data series using in forecasting. Note that when a statistical model is used to represent ZKB Silver etf, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 125.7356 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 14.5695 |
| MAPE | Mean absolute percentage error | 0.0775 |
| SAE | Sum of the absolute errors | 903.3094 |
Other Forecasting Options for ZKB Silver
The autocorrelation structure of ZKB Silver's daily returns reveals whether ZKB exhibits momentum, mean-reversion, or random-walk behavior. Separating these elements helps distinguish persistent directional moves from temporary noise in ZKB Etf price data. Stochastic oscillator analysis compares ZKB Silver's closing price to its range over a given period.ZKB Silver Related Equities
These stocks are related to ZKB Silver within the Commodities - Precious Metals space and can be used for peer review, pricing, or spreading risk. Growth rate gaps between ZKB Silver and its peers often explain pricing differences in the market.
| Risk & Return | Correlation |
ZKB Silver Market Strength Events
Market strength indicators applied to ZKB Silver etf help assess momentum and resilience across environments. These indicators support informed market timing decisions when analyzing ZKB Silver. For ZKB Silver ETF, market strength indicators complement fundamental analysis with timing context.
| Accumulation Distribution | 21500.56 | |||
| Daily Balance Of Power | -0.24 | |||
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 150.41 | |||
| Day Typical Price | 151.39 | |||
| Market Facilitation Index | 1.0E-4 | |||
| Price Action Indicator | 1.13 | |||
| Period Momentum Indicator | -3.64 | |||
| Relative Strength Index | 43.64 |
ZKB Silver Risk Indicators
Risk indicator analysis for ZKB Silver is essential for accurately projecting its future price trajectory. The process involves identifying the amount of risk involved in ZKB Silver's investment and either accepting or mitigating it. Understanding the risk profile of ZKB Silver's allows investors to make more informed decisions about position sizing.
| Mean Deviation | 3.93 | |||
| Semi Deviation | 5.46 | |||
| Standard Deviation | 5.33 | |||
| Variance | 28.39 | |||
| Downside Variance | 34.25 | |||
| Semi Variance | 29.81 | |||
| Expected Short fall | -3.98 |
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.
Story Coverage note for ZKB Silver
The amount of media and story coverage tied to ZKB Silver ETF can signal where market attention is concentrating at the moment. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.
Story Categories
Currently Trending Categories
More Resources for ZKB Etf Analysis
Other Information on Investing in ZKB Etf
At ZKB Silver, financial ratios outline links between core financial data. They outline how earnings and cash flow connect to company value.