Fagerhult Stock Forecast - Double Exponential Smoothing

FAG Stock  SEK 57.50  1.50  2.68%   
The Double Exponential Smoothing forecasted value of Fagerhult AB on the next trading day is expected to be 57.67 with a mean absolute deviation of 0.62 and the sum of the absolute errors of 36.40. Fagerhult Stock Forecast is based on your current time horizon.
  
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Fagerhult works best with periods where there are trends or seasonality.

Fagerhult Double Exponential Smoothing Price Forecast For the 2nd of December

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Fagerhult AB on the next trading day is expected to be 57.67 with a mean absolute deviation of 0.62, mean absolute percentage error of 0.60, and the sum of the absolute errors of 36.40.
Please note that although there have been many attempts to predict Fagerhult 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 Fagerhult's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fagerhult Stock Forecast Pattern

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Fagerhult Forecasted Value

In the context of forecasting Fagerhult'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. Fagerhult's downside and upside margins for the forecasting period are 56.46 and 58.89, respectively. We have considered Fagerhult'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
57.50
57.67
Expected Value
58.89
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Fagerhult stock data series using in forecasting. Note that when a statistical model is used to represent Fagerhult 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 CriteriaHuge
BiasArithmetic mean of the errors -0.0562
MADMean absolute deviation0.617
MAPEMean absolute percentage error0.0101
SAESum of the absolute errors36.4044
When Fagerhult AB prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any Fagerhult AB trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Fagerhult observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Fagerhult

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fagerhult AB. 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
56.2857.5058.72
Details
Intrinsic
Valuation
LowRealHigh
51.7559.3360.55
Details

Other Forecasting Options for Fagerhult

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

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

Fagerhult AB 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 Fagerhult'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 Fagerhult's current price.

Fagerhult Market Strength Events

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

Fagerhult Risk Indicators

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

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Additional Tools for Fagerhult Stock Analysis

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