Swiss Life Pink Sheet Forecast - Polynomial Regression

SWSDF Stock  USD 784.85  6.12  0.77%   
The Polynomial Regression forecasted value of Swiss Life Holding on the next trading day is expected to be 775.28 with a mean absolute deviation of 6.64 and the sum of the absolute errors of 405.27. Swiss Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Swiss Life's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Swiss Life polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Swiss Life Holding as well as the accuracy indicators are determined from the period prices.

Swiss Life Polynomial Regression Price Forecast For the 30th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Swiss Life Holding on the next trading day is expected to be 775.28 with a mean absolute deviation of 6.64, mean absolute percentage error of 83.94, and the sum of the absolute errors of 405.27.
Please note that although there have been many attempts to predict Swiss Pink Sheet prices using its time series forecasting, we generally do not recommend 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).

Swiss Life Pink Sheet Forecast Pattern

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Swiss Life Forecasted Value

In the context of forecasting Swiss Life's Pink Sheet value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Swiss Life's downside and upside margins for the forecasting period are 773.92 and 776.64, respectively. We have considered Swiss Life's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
784.85
773.92
Downside
775.28
Expected Value
776.64
Upside

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 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.
AICAkaike Information Criteria122.5406
BiasArithmetic mean of the errors None
MADMean absolute deviation6.6438
MAPEMean absolute percentage error0.0081
SAESum of the absolute errors405.2729
A single variable polynomial regression model attempts to put a curve through the Swiss Life 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

Predictive Modules for Swiss Life

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Swiss Life Holding. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Swiss Life's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
783.49784.85786.21
Details
Intrinsic
Valuation
LowRealHigh
665.94667.30863.34
Details
Bollinger
Band Projection (param)
LowMiddleHigh
770.62807.44844.27
Details

Other Forecasting Options for Swiss Life

For every potential investor in Swiss, whether a beginner or expert, Swiss Life's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Swiss Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Swiss. Basic forecasting techniques help filter out the noise by identifying Swiss Life's price trends.

Swiss Life Related Equities

One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Swiss Life pink sheet to make a market-neutral strategy. Peer analysis of Swiss Life could also be used in its relative valuation, which is a method of valuing Swiss Life by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Swiss Life Holding Technical and Predictive Analytics

The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Swiss Life's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Swiss Life's current price.

Swiss Life Market Strength Events

Market strength indicators help investors to evaluate how Swiss Life pink sheet reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Swiss Life shares will generate the highest return on investment. By undertsting and applying Swiss Life pink sheet market strength indicators, traders can identify Swiss Life Holding entry and exit signals to maximize returns.

Swiss Life Risk Indicators

The analysis of Swiss Life's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Swiss Life's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting swiss pink sheet prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
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.

Currently Active Assets on Macroaxis

Other Information on Investing in Swiss Pink Sheet

Swiss Life financial ratios help investors to determine whether Swiss Pink Sheet is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Swiss with respect to the benefits of owning Swiss Life security.