The Polynomial Regression forecasted value of Eni SpA on the next trading day is expected to be 17.27 with a mean absolute deviation of 0.46 and the sum of the absolute errors of 28.77. Eni Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Eni SpA's historical fundamentals, such as revenue growth or operating cash flow patterns.
Eni
Eni SpA polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Eni SpA as well as the accuracy indicators are determined from the period prices.
Eni SpA Polynomial Regression Price Forecast For the 27th of July
Given 90 days horizon, the Polynomial Regression forecasted value of Eni SpA on the next trading day is expected to be 17.27 with a mean absolute deviation of 0.46, mean absolute percentage error of 0.29, and the sum of the absolute errors of 28.77.
Please note that although there have been many attempts to predict Eni 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 Eni SpA's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
In the context of forecasting Eni SpA'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. Eni SpA's downside and upside margins for the forecasting period are 13.96 and 20.58, respectively. We have considered Eni SpA'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.
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 Eni SpA pink sheet data series using in forecasting. Note that when a statistical model is used to represent Eni SpA 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
118.7141
Bias
Arithmetic mean of the errors
None
MAD
Mean absolute deviation
0.464
MAPE
Mean absolute percentage error
0.0291
SAE
Sum of the absolute errors
28.768
A single variable polynomial regression model attempts to put a curve through the Eni SpA 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 Eni SpA
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Eni SpA. 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.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Eni SpA. Your research has to be compared to or analyzed against Eni SpA's peers to derive any actionable benefits. When done correctly, Eni SpA's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Eni SpA.
Other Forecasting Options for Eni SpA
For every potential investor in Eni, whether a beginner or expert, Eni SpA's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Eni Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Eni. Basic forecasting techniques help filter out the noise by identifying Eni SpA's price trends.
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 Eni SpA'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 Eni SpA's current price.
Market strength indicators help investors to evaluate how Eni SpA 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 Eni SpA shares will generate the highest return on investment. By undertsting and applying Eni SpA pink sheet market strength indicators, traders can identify Eni SpA entry and exit signals to maximize returns.
The analysis of Eni SpA'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 Eni SpA's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting eni 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.
Eni SpA financial ratios help investors to determine whether Eni 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 Eni with respect to the benefits of owning Eni SpA security.