Caisse Regionale Stock Forecast - Simple Exponential Smoothing
| CRBP2 Stock | EUR 21.44 0.12 0.56% |
The Simple Exponential Smoothing forecasted value of Caisse Regionale de on the next trading day is expected to be 21.44 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 9.98. Caisse Stock Forecast is based on your current time horizon.
Caisse |
Caisse Regionale Simple Exponential Smoothing Price Forecast For the 3rd of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Caisse Regionale de on the next trading day is expected to be 21.44 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.07, and the sum of the absolute errors of 9.98.Please note that although there have been many attempts to predict Caisse 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 Caisse Regionale's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Caisse Regionale Stock Forecast Pattern
| Backtest Caisse Regionale | Caisse Regionale Price Prediction | Buy or Sell Advice |
Caisse Regionale Forecasted Value
In the context of forecasting Caisse Regionale'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. Caisse Regionale's downside and upside margins for the forecasting period are 20.18 and 22.70, respectively. We have considered Caisse Regionale'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Caisse Regionale stock data series using in forecasting. Note that when a statistical model is used to represent Caisse Regionale 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.| AIC | Akaike Information Criteria | 113.5952 |
| Bias | Arithmetic mean of the errors | -0.059 |
| MAD | Mean absolute deviation | 0.1663 |
| MAPE | Mean absolute percentage error | 0.0084 |
| SAE | Sum of the absolute errors | 9.98 |
Predictive Modules for Caisse Regionale
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Caisse Regionale. 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.Other Forecasting Options for Caisse Regionale
For every potential investor in Caisse, whether a beginner or expert, Caisse Regionale's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Caisse Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Caisse. Basic forecasting techniques help filter out the noise by identifying Caisse Regionale's price trends.Caisse Regionale 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 Caisse Regionale stock to make a market-neutral strategy. Peer analysis of Caisse Regionale could also be used in its relative valuation, which is a method of valuing Caisse Regionale by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Caisse Regionale 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 Caisse Regionale'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 Caisse Regionale's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Caisse Regionale Market Strength Events
Market strength indicators help investors to evaluate how Caisse Regionale stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Caisse Regionale shares will generate the highest return on investment. By undertsting and applying Caisse Regionale stock market strength indicators, traders can identify Caisse Regionale de entry and exit signals to maximize returns.
Caisse Regionale Risk Indicators
The analysis of Caisse Regionale'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 Caisse Regionale's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting caisse 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.
| Mean Deviation | 0.8682 | |||
| Semi Deviation | 0.4521 | |||
| Standard Deviation | 1.27 | |||
| Variance | 1.6 | |||
| Downside Variance | 0.8888 | |||
| Semi Variance | 0.2044 | |||
| Expected Short fall | (1.17) |
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.Additional Tools for Caisse Stock Analysis
When running Caisse Regionale's price analysis, check to measure Caisse Regionale's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Caisse Regionale is operating at the current time. Most of Caisse Regionale's value examination focuses on studying past and present price action to predict the probability of Caisse Regionale's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Caisse Regionale's price. Additionally, you may evaluate how the addition of Caisse Regionale to your portfolios can decrease your overall portfolio volatility.