Skanska AB Stock Forecast - Polynomial Regression
| SKA-B Stock | SEK 191.85 0.40 0.21% |
The Polynomial Regression forecasted value of Skanska AB on the next trading day is expected to be 191.65 with a mean absolute deviation of 2.29 and the sum of the absolute errors of 139.98. Skanska Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Skanska AB stock prices and determine the direction of Skanska AB's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Skanska AB's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Skanska AB to cross-verify your projections. Skanska |
Most investors in Skanska AB cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Skanska AB's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Skanska AB's price structures and extracts relationships that further increase the generated results' accuracy.
Skanska AB polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Skanska AB as well as the accuracy indicators are determined from the period prices. Skanska AB Polynomial Regression Price Forecast For the 3rd of May
Given 90 days horizon, the Polynomial Regression forecasted value of Skanska AB on the next trading day is expected to be 191.65 with a mean absolute deviation of 2.29, mean absolute percentage error of 7.99, and the sum of the absolute errors of 139.98.Please note that although there have been many attempts to predict Skanska 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 Skanska AB's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Skanska AB Stock Forecast Pattern
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Skanska AB Forecasted Value
In the context of forecasting Skanska AB'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. Skanska AB's downside and upside margins for the forecasting period are 190.26 and 193.05, respectively. We have considered Skanska AB'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Skanska AB stock data series using in forecasting. Note that when a statistical model is used to represent Skanska AB 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 | 120.1882 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 2.2947 |
| MAPE | Mean absolute percentage error | 0.0126 |
| SAE | Sum of the absolute errors | 139.9755 |
Predictive Modules for Skanska AB
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Skanska 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Skanska AB's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Other Forecasting Options for Skanska AB
For every potential investor in Skanska, whether a beginner or expert, Skanska AB's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Skanska Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Skanska. Basic forecasting techniques help filter out the noise by identifying Skanska AB's price trends.Skanska AB 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 Skanska AB stock to make a market-neutral strategy. Peer analysis of Skanska AB could also be used in its relative valuation, which is a method of valuing Skanska AB by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Skanska 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 Skanska AB'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 Skanska AB's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Skanska AB Market Strength Events
Market strength indicators help investors to evaluate how Skanska AB stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Skanska AB shares will generate the highest return on investment. By undertsting and applying Skanska AB stock market strength indicators, traders can identify Skanska AB entry and exit signals to maximize returns.
Skanska AB Risk Indicators
The analysis of Skanska AB'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 Skanska AB's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting skanska 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 | 1.05 | |||
| Semi Deviation | 0.9641 | |||
| Standard Deviation | 1.46 | |||
| Variance | 2.12 | |||
| Downside Variance | 1.5 | |||
| Semi Variance | 0.9295 | |||
| Expected Short fall | (1.20) |
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.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Skanska AB in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Skanska AB's short interest history, or implied volatility extrapolated from Skanska AB options trading.
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Check out Historical Fundamental Analysis of Skanska AB to cross-verify your projections. Note that the Skanska AB information on this page should be used as a complementary analysis to other Skanska AB's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Top Crypto Exchanges module to search and analyze digital assets across top global cryptocurrency exchanges.
Complementary Tools for Skanska Stock analysis
When running Skanska AB's price analysis, check to measure Skanska AB'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 Skanska AB is operating at the current time. Most of Skanska AB's value examination focuses on studying past and present price action to predict the probability of Skanska AB's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Skanska AB's price. Additionally, you may evaluate how the addition of Skanska AB to your portfolios can decrease your overall portfolio volatility.
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