Swiss Life Pink Sheet Forward View - Triple Exponential Smoothing
| SWSDF Stock | USD 1,067 -14.65 -1.35% |
The Triple Exponential Smoothing forecast reference data for Swiss Life Holding is based on the equity's recent trading history. This page summarizes the model output and key accuracy metrics for reference.
The Triple Exponential Smoothing forecasted value of Swiss Life Holding on the next trading day is expected to be 1,067 with a mean absolute deviation of 5.10 and the sum of the absolute errors of 305.74.As with simple exponential smoothing, in triple exponential smoothing models past Swiss Life observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Swiss Life Holding observations. All Triple Exponential Smoothing forecast figures shown for Swiss Life Holding are reference data reflecting model output based on available historical prices. Triple Exponential Smoothing Price Forecast For the 22nd of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Swiss Life Holding on the next trading day is expected to be 1,067 with a mean absolute deviation of 5.10 , mean absolute percentage error of 236.18 , and the sum of the absolute errors of 305.74 .Please note that although there have been many attempts to predict Swiss Pink Sheet 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 Life's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Pink Sheet Forecast Pattern
| Backtest Swiss Life | Swiss Life Price Prediction | Research Analysis |
Forecasted Value
Forecasting Swiss Life Holding for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Swiss Life pink sheet data series using in forecasting. Note that when a statistical model is used to represent Swiss Life pink sheet, 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 | Huge |
| Bias | Arithmetic mean of the errors | 1.3 |
| MAD | Mean absolute deviation | 5.0957 |
| MAPE | Mean absolute percentage error | 0.0045 |
| SAE | Sum of the absolute errors | 305.74 |
Other Forecasting Options for Swiss Life
Whether a novice or experienced investor, anyone considering Swiss needs to understand the dynamics of Swiss Life's price movement. Price charts for Swiss Pink Sheet contain a significant amount of noise that can distort investment decisions.Swiss Life Related Equities
The following equities are related to Swiss Life within the Insurance—Diversified space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Swiss Life 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 |
Swiss Life Market Strength Events
Analyzing market strength indicators for Swiss Life enables investors to understand how the pink sheet performs relative to overall market momentum. These indicators are valuable tools for identifying when to enter or exit positions in Swiss Life Holding.
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 1067.0 | |||
| Day Typical Price | 1067.0 | |||
| Price Action Indicator | -7.33 | |||
| Period Momentum Indicator | -14.65 |
Swiss Life Risk Indicators
Identifying and analyzing Swiss Life's key risk indicators is a foundational step in projecting how its price may evolve. This process quantifies the risk associated with Swiss Life's and decide how to manage it.
| Mean Deviation | 0.5012 | |||
| Standard Deviation | 1.41 | |||
| Variance | 1.99 |
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 Life
Story coverage around Swiss Life Holding often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
Other Macroaxis Stories
Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.
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Swiss Life Short Properties
Short-interest signals around Swiss Life Holding can help investors judge whether skeptical positioning is starting to pressure price predictability and market tone. The stronger read compares short sentiment with trend behavior, volume, and the broader market narrative.
| Common Stock Shares Outstanding | 31.2 M | |
| Cash And Short Term Investments | 108.7 B |
More Resources for Swiss Pink Sheet Analysis
Other Information on Investing in Swiss Pink Sheet
These ratios describe connections between financial data points for Swiss Life. This helps frame how profit and cash flow relate to overall value. The format ensures data can be compared on a consistent basis. This data is based on the latest available financial reporting cycle.