Samsung Electronics Stock Forecast - Simple Exponential Smoothing
| SSU Stock | EUR 924.00 18.00 1.91% |
The Simple Exponential Smoothing forecasted value of Samsung Electronics Co on the next trading day is expected to be 924.00 with a mean absolute deviation of 18.22 and the sum of the absolute errors of 1,093. 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.
Samsung |
Samsung Electronics Simple Exponential Smoothing Price Forecast For the 30th of November
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Samsung Electronics Co on the next trading day is expected to be 924.00 with a mean absolute deviation of 18.22, mean absolute percentage error of 524.63, and the sum of the absolute errors of 1,093.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
| Backtest Samsung Electronics | Samsung Electronics Price Prediction | Buy or Sell Advice |
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 921.66 and 926.34, 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.
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 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.| AIC | Akaike Information Criteria | 122.5353 |
| Bias | Arithmetic mean of the errors | 3.5733 |
| MAD | Mean absolute deviation | 18.2157 |
| MAPE | Mean absolute percentage error | 0.0182 |
| SAE | Sum of the absolute errors | 1092.94 |
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.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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
| Accumulation Distribution | 0.93 | |||
| Daily Balance Of Power | (2.25) | |||
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 920.0 | |||
| Day Typical Price | 921.33 | |||
| Market Facilitation Index | 0.0748 | |||
| Price Action Indicator | (5.00) | |||
| Period Momentum Indicator | (18.00) | |||
| Relative Strength Index | 34.45 |
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.
| Mean Deviation | 1.76 | |||
| Standard Deviation | 2.33 | |||
| Variance | 5.43 |
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.
Currently Active Assets on Macroaxis
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.