Financeira Alfa Stock Forecast - Naive Prediction

CRIV3 Stock  BRL 6.98  0.00  0.00%   
The Naive Prediction forecasted value of Financeira Alfa SA on the next trading day is expected to be 6.98 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Financeira Stock Forecast is based on your current time horizon.
  
A naive forecasting model for Financeira Alfa is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Financeira Alfa SA value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Financeira Alfa Naive Prediction Price Forecast For the 28th of November

Given 90 days horizon, the Naive Prediction forecasted value of Financeira Alfa SA on the next trading day is expected to be 6.98 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict Financeira 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 Financeira Alfa's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Financeira Alfa Stock Forecast Pattern

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Financeira Alfa Forecasted Value

In the context of forecasting Financeira Alfa'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. Financeira Alfa's downside and upside margins for the forecasting period are 6.98 and 6.98, respectively. We have considered Financeira Alfa'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
6.98
6.98
Expected Value
6.98
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Financeira Alfa stock data series using in forecasting. Note that when a statistical model is used to represent Financeira Alfa 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 Criteria53.2246
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
This model is not at all useful as a medium-long range forecasting tool of Financeira Alfa SA. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Financeira Alfa. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Financeira Alfa

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Financeira Alfa SA. 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.
Hype
Prediction
LowEstimatedHigh
6.986.986.98
Details
Intrinsic
Valuation
LowRealHigh
6.986.986.98
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Financeira Alfa. Your research has to be compared to or analyzed against Financeira Alfa's peers to derive any actionable benefits. When done correctly, Financeira Alfa'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 Financeira Alfa SA.

Other Forecasting Options for Financeira Alfa

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

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

Financeira Alfa SA 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 Financeira Alfa'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 Financeira Alfa's current price.

Financeira Alfa Market Strength Events

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

Additional Tools for Financeira Stock Analysis

When running Financeira Alfa's price analysis, check to measure Financeira Alfa'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 Financeira Alfa is operating at the current time. Most of Financeira Alfa's value examination focuses on studying past and present price action to predict the probability of Financeira Alfa's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Financeira Alfa's price. Additionally, you may evaluate how the addition of Financeira Alfa to your portfolios can decrease your overall portfolio volatility.