Revenio Stock Forecast - Polynomial Regression

REG1V Stock  EUR 27.78  0.64  2.36%   
The Polynomial Regression forecasted value of Revenio Group on the next trading day is expected to be 27.11 with a mean absolute deviation of 0.57 and the sum of the absolute errors of 34.90. Revenio Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Revenio's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Revenio polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Revenio Group as well as the accuracy indicators are determined from the period prices.

Revenio Polynomial Regression Price Forecast For the 23rd of November

Given 90 days horizon, the Polynomial Regression forecasted value of Revenio Group on the next trading day is expected to be 27.11 with a mean absolute deviation of 0.57, mean absolute percentage error of 0.55, and the sum of the absolute errors of 34.90.
Please note that although there have been many attempts to predict Revenio 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 Revenio's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Revenio Stock Forecast Pattern

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Revenio Forecasted Value

In the context of forecasting Revenio's Stock 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. Revenio's downside and upside margins for the forecasting period are 25.01 and 29.20, respectively. We have considered Revenio'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
27.78
27.11
Expected Value
29.20
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 Revenio stock data series using in forecasting. Note that when a statistical model is used to represent Revenio 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 Criteria117.5134
BiasArithmetic mean of the errors None
MADMean absolute deviation0.5721
MAPEMean absolute percentage error0.0182
SAESum of the absolute errors34.899
A single variable polynomial regression model attempts to put a curve through the Revenio 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 Revenio

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Revenio Group. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Revenio'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
25.6927.7829.87
Details
Intrinsic
Valuation
LowRealHigh
23.6525.7427.83
Details
Bollinger
Band Projection (param)
LowMiddleHigh
26.1129.5833.04
Details

Other Forecasting Options for Revenio

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

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

Revenio Group Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Revenio'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 Revenio's current price.

Revenio Market Strength Events

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

Revenio Risk Indicators

The analysis of Revenio'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 Revenio's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting revenio 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.

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.

Other Information on Investing in Revenio Stock

Revenio financial ratios help investors to determine whether Revenio Stock 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 Revenio with respect to the benefits of owning Revenio security.