UBS ETF Etf Forward View - Simple Moving Average
| SMMCHA Etf | CHF 288.20 -0.10 -0.03% |
This page documents Simple Moving Average forecast output for UBS ETF SMIM as reference data. The model is applied to historical closing prices and the resulting projection and error statistics are shown below.
The Simple Moving Average forecasted value of UBS ETF SMIM on the next trading day is expected to be 288.20 with a mean absolute deviation of 2.30 and the sum of the absolute errors of 137.83.The simple moving average model is conceptually a linear regression of the current value of UBS ETF SMIM price series against current and previous (unobserved) value of UBS ETF. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future The Simple Moving Average reference information for UBS ETF is based on available price data and is intended for informational purposes. Simple Moving Average Price Forecast For the 22nd of March
Given 90 days horizon, the Simple Moving Average forecasted value of UBS ETF SMIM on the next trading day is expected to be 288.20 with a mean absolute deviation of 2.30 , mean absolute percentage error of 8.97 , and the sum of the absolute errors of 137.83 .Please note that although there have been many attempts to predict UBS 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 UBS ETF's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Etf Forecast Pattern
| Backtest UBS ETF | UBS ETF Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for UBS ETF SMIM uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of UBS ETF etf data series using in forecasting. Note that when a statistical model is used to represent UBS ETF 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 | 118.4662 |
| Bias | Arithmetic mean of the errors | 0.2996 |
| MAD | Mean absolute deviation | 2.2971 |
| MAPE | Mean absolute percentage error | 0.0075 |
| SAE | Sum of the absolute errors | 137.825 |
Other Forecasting Options for UBS ETF
Any investor evaluating UBS must grapple with the challenge of interpreting UBS ETF's price movement accurately. UBS Etf price charts typically contain substantial noise that can complicate analysis and lead to poor decisions.UBS ETF Related Equities
The following equities are related to UBS ETF within the Switzerland Small/Mid-Cap Equity space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing UBS ETF against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
| Risk & Return | Correlation |
UBS ETF Market Strength Events
Market strength indicators for UBS ETF assess how the etf responds to ongoing changes in market conditions and investor sentiment. By monitoring these indicators, investors can identify the most opportune moments to trade UBS ETF SMIM.
UBS ETF Risk Indicators
Risk indicator analysis for UBS ETF is a critical component of accurate price forecasting and sound investment decision-making. By identifying how much risk is embedded in UBS ETF's investment, investors can decide how to position and protect their exposure.
| Mean Deviation | 0.6636 | |||
| Standard Deviation | 0.8788 | |||
| Variance | 0.7723 |
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 UBS ETF
Coverage intensity for UBS ETF SMIM matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
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UBS ETF financial ratios describe how key financial values relate to each other. These measures reflect profitability, cash flow, and enterprise value. Values are aligned to support consistent measurement over time.