Samsung Electronics Stock Forecast - Naive Prediction

SSUN Stock  EUR 800.00  14.00  1.72%   
The Naive Prediction forecasted value of Samsung Electronics Co on the next trading day is expected to be 815.19 with a mean absolute deviation of 15.32 and the sum of the absolute errors of 950.10. Samsung Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Samsung Electronics' historical fundamentals, such as revenue growth or operating cash flow patterns.
  
A naive forecasting model for Samsung Electronics is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Samsung Electronics Co 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.

Samsung Electronics Naive Prediction Price Forecast For the 1st of December

Given 90 days horizon, the Naive Prediction forecasted value of Samsung Electronics Co on the next trading day is expected to be 815.19 with a mean absolute deviation of 15.32, mean absolute percentage error of 415.86, and the sum of the absolute errors of 950.10.
Please note that although there have been many attempts to predict Samsung 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 Samsung Electronics' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Samsung Electronics Stock Forecast Pattern

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Samsung Electronics Forecasted Value

In the context of forecasting Samsung Electronics' 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. Samsung Electronics' downside and upside margins for the forecasting period are 812.57 and 817.81, respectively. We have considered Samsung Electronics' 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
800.00
812.57
Downside
815.19
Expected Value
817.81
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 Samsung Electronics stock data series using in forecasting. Note that when a statistical model is used to represent Samsung Electronics 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 Criteria125.9787
BiasArithmetic mean of the errors None
MADMean absolute deviation15.3243
MAPEMean absolute percentage error0.0186
SAESum of the absolute errors950.1043
This model is not at all useful as a medium-long range forecasting tool of Samsung Electronics Co. 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 Samsung Electronics. 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 Samsung Electronics

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Samsung Electronics. 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
797.38800.00802.62
Details
Intrinsic
Valuation
LowRealHigh
685.15687.77880.00
Details
Bollinger
Band Projection (param)
LowMiddleHigh
789.75821.40853.05
Details

Other Forecasting Options for Samsung Electronics

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

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

Samsung Electronics 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 Samsung Electronics' 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 Samsung Electronics' current price.

Samsung Electronics Market Strength Events

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

Samsung Electronics Risk Indicators

The analysis of Samsung Electronics' 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 Samsung Electronics' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting samsung 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 Samsung Stock

Samsung Electronics financial ratios help investors to determine whether Samsung 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 Samsung with respect to the benefits of owning Samsung Electronics security.