Ferrovial Pink Sheet Forecast - Polynomial Regression

FRRVYDelisted Stock  USD 30.75  0.55  1.76%   
The Polynomial Regression forecasted value of Ferrovial SA on the next trading day is expected to be 31.19 with a mean absolute deviation of 0.47 and the sum of the absolute errors of 28.45. Ferrovial Pink Sheet Forecast is based on your current time horizon.
  
Ferrovial polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Ferrovial SA as well as the accuracy indicators are determined from the period prices.

Ferrovial Polynomial Regression Price Forecast For the 10th of January

Given 90 days horizon, the Polynomial Regression forecasted value of Ferrovial SA on the next trading day is expected to be 31.19 with a mean absolute deviation of 0.47, mean absolute percentage error of 0.54, and the sum of the absolute errors of 28.45.
Please note that although there have been many attempts to predict Ferrovial 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 Ferrovial's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Ferrovial Pink Sheet 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 Ferrovial pink sheet data series using in forecasting. Note that when a statistical model is used to represent Ferrovial 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 Criteria117.4981
BiasArithmetic mean of the errors None
MADMean absolute deviation0.4664
MAPEMean absolute percentage error0.0153
SAESum of the absolute errors28.4499
A single variable polynomial regression model attempts to put a curve through the Ferrovial 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 Ferrovial

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Ferrovial SA. 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 Ferrovial'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
30.7530.7530.75
Details
Intrinsic
Valuation
LowRealHigh
25.7425.7433.83
Details

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

Ferrovial Market Strength Events

Market strength indicators help investors to evaluate how Ferrovial 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 Ferrovial shares will generate the highest return on investment. By undertsting and applying Ferrovial pink sheet market strength indicators, traders can identify Ferrovial SA entry and exit signals to maximize returns.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.
Check out Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in real.
You can also try the Portfolio File Import module to quickly import all of your third-party portfolios from your local drive in csv format.

Other Consideration for investing in Ferrovial Pink Sheet

If you are still planning to invest in Ferrovial SA 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 Ferrovial's history and understand the potential risks before investing.
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