Swiss Water Stock Forward View
| SWP Stock | CAD 4.84 0.15 3.20% |
Swiss Water Decaffeinated's Naive Prediction reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use.
The Naive Prediction forecasted value of Swiss Water Decaffeinated on the next trading day is expected to be 4.90 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.46.This model is not at all useful as a medium-long range forecasting tool of Swiss Water Decaffeinated. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Swiss Water. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights. All Naive Prediction forecast figures shown for Swiss Water Decaffeinated are reference data reflecting model output based on available historical prices. Naive Prediction Price Forecast For the 24th of March
Given 90 days horizon, the Naive Prediction forecasted value of Swiss Water Decaffeinated on the next trading day is expected to be 4.90 with a mean absolute deviation of 0.04 , mean absolute percentage error of 0.0023 , and the sum of the absolute errors of 2.46 .Please note that although there have been many attempts to predict Swiss Stock 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 Swiss Water's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest Swiss Water | Swiss Water Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for Swiss Water Decaffeinated uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. 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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Swiss Water stock data series using in forecasting. Note that when a statistical model is used to represent Swiss Water stock, 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 | 112.024 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0403 |
| MAPE | Mean absolute percentage error | 0.009 |
| SAE | Sum of the absolute errors | 2.4595 |
Other Forecasting Options for Swiss Water
Bollinger Bands applied to Swiss Stock price data measure how far Swiss has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to Swiss Water's price data.Swiss Water Related Equities
These stocks within the Consumer Staples space are often compared to Swiss Water by analysts and fund managers in the sector. Market cap and total value checks frame Swiss Water's size within the competitive field. Firms that trade at big discounts to peers on core metrics may be worth more research. This type of review is most useful when done often to track how positions shift over time.
| Risk & Return | Correlation |
Swiss Water Market Strength Events
For investors tracking Swiss Water Decaffeinated, market strength indicators offer quantitative evaluation of stock behavior. By using these indicators, traders can make more informed decisions about when to buy or sell Swiss Water Decaffeinated.
Swiss Water Risk Indicators
Analyzing Swiss Water's basic risk indicators provides investors with a structured view of the risk-return trade-off for swiss stock. By identifying the level of risk embedded in Swiss Water's investment, investors can make informed decisions about position sizing.
| Mean Deviation | 0.8581 | |||
| Semi Deviation | 1.17 | |||
| Standard Deviation | 1.32 | |||
| Variance | 1.75 | |||
| Downside Variance | 4.03 | |||
| Semi Variance | 1.36 | |||
| Expected Short fall | -1.17 |
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 Swiss Water
Coverage intensity for Swiss Water Decaffeinated matters because narrative visibility can influence sentiment, participation, and volatility around the name. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
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.
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Swiss Water Short Properties
A short-interest review of Swiss Water Decaffeinated provides context for understanding whether skepticism in the market is becoming more influential. The stronger read compares short sentiment with trend behavior, volume, and the broader market narrative.
| Common Stock Shares Outstanding | 9.7 M | |
| Cash And Short Term Investments | 6.6 M |
More Resources for Swiss Stock Analysis
Other Information on Investing in Swiss Stock
Financial ratios for Swiss Water organize key financial data into structured relationships. This helps maintain uniform comparisons across financial reports.