Pf Bakkafrost Stock Forecast - Naive Prediction

BAKKA Stock  NOK 642.00  27.50  4.11%   
The Naive Prediction forecasted value of Pf Bakkafrost on the next trading day is expected to be 668.75 with a mean absolute deviation of 7.88 and the sum of the absolute errors of 488.32. BAKKA Stock Forecast is based on your current time horizon.
  
A naive forecasting model for Pf Bakkafrost is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Pf Bakkafrost 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.

Pf Bakkafrost Naive Prediction Price Forecast For the 28th of November

Given 90 days horizon, the Naive Prediction forecasted value of Pf Bakkafrost on the next trading day is expected to be 668.75 with a mean absolute deviation of 7.88, mean absolute percentage error of 104.29, and the sum of the absolute errors of 488.32.
Please note that although there have been many attempts to predict BAKKA 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 Pf Bakkafrost's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Pf Bakkafrost Stock Forecast Pattern

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Pf Bakkafrost Forecasted Value

In the context of forecasting Pf Bakkafrost'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. Pf Bakkafrost's downside and upside margins for the forecasting period are 667.02 and 670.49, respectively. We have considered Pf Bakkafrost'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
642.00
667.02
Downside
668.75
Expected Value
670.49
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 Pf Bakkafrost stock data series using in forecasting. Note that when a statistical model is used to represent Pf Bakkafrost 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 Criteria124.5955
BiasArithmetic mean of the errors None
MADMean absolute deviation7.876
MAPEMean absolute percentage error0.0125
SAESum of the absolute errors488.3151
This model is not at all useful as a medium-long range forecasting tool of Pf Bakkafrost. 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 Pf Bakkafrost. 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 Pf Bakkafrost

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Pf Bakkafrost. 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
640.29642.00643.71
Details
Intrinsic
Valuation
LowRealHigh
531.15532.86706.20
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Pf Bakkafrost. Your research has to be compared to or analyzed against Pf Bakkafrost's peers to derive any actionable benefits. When done correctly, Pf Bakkafrost'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 Pf Bakkafrost.

Other Forecasting Options for Pf Bakkafrost

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

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

Pf Bakkafrost 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 Pf Bakkafrost'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 Pf Bakkafrost's current price.

Pf Bakkafrost Market Strength Events

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

Pf Bakkafrost Risk Indicators

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

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Other Information on Investing in BAKKA Stock

Pf Bakkafrost financial ratios help investors to determine whether BAKKA 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 BAKKA with respect to the benefits of owning Pf Bakkafrost security.