Wisconsin Electric OTC Stock Forecast - Polynomial Regression

WELPMDelisted Stock  USD 103.00  0.00  0.00%   
The Polynomial Regression forecasted value of Wisconsin Electric Power on the next trading day is expected to be 102.29 with a mean absolute deviation of 0.43 and the sum of the absolute errors of 26.06. Wisconsin OTC Stock Forecast is based on your current time horizon.
  
Wisconsin Electric polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Wisconsin Electric Power as well as the accuracy indicators are determined from the period prices.

Wisconsin Electric Polynomial Regression Price Forecast For the 14th of December 2024

Given 90 days horizon, the Polynomial Regression forecasted value of Wisconsin Electric Power on the next trading day is expected to be 102.29 with a mean absolute deviation of 0.43, mean absolute percentage error of 0.36, and the sum of the absolute errors of 26.06.
Please note that although there have been many attempts to predict Wisconsin OTC Stock 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 Wisconsin Electric's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Wisconsin Electric OTC Stock Forecast Pattern

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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 Wisconsin Electric otc stock data series using in forecasting. Note that when a statistical model is used to represent Wisconsin Electric otc 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.
AICAkaike Information Criteria117.0796
BiasArithmetic mean of the errors None
MADMean absolute deviation0.4271
MAPEMean absolute percentage error0.0041
SAESum of the absolute errors26.0558
A single variable polynomial regression model attempts to put a curve through the Wisconsin Electric 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 Wisconsin Electric

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Wisconsin Electric Power. Regardless of method or technology, however, to accurately forecast the otc stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the otc stock 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.
Hype
Prediction
LowEstimatedHigh
103.00103.00103.00
Details
Intrinsic
Valuation
LowRealHigh
87.7687.76113.30
Details

Wisconsin Electric 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 Wisconsin Electric otc stock to make a market-neutral strategy. Peer analysis of Wisconsin Electric could also be used in its relative valuation, which is a method of valuing Wisconsin Electric by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Wisconsin Electric Market Strength Events

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

Wisconsin Electric Risk Indicators

The analysis of Wisconsin Electric'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 Wisconsin Electric's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting wisconsin otc stock 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.

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Other Consideration for investing in Wisconsin OTC Stock

If you are still planning to invest in Wisconsin Electric Power check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Wisconsin Electric's history and understand the potential risks before investing.
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