Plug Power Stock Forecast - Polynomial Regression
| PLUN Stock | 2.44 0.25 11.42% |
The Polynomial Regression forecasted value of Plug Power on the next trading day is expected to be 2.54 with a mean absolute deviation of 0.1 and the sum of the absolute errors of 6.05. Plug Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Plug Power stock prices and determine the direction of Plug Power's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Plug Power's historical fundamentals, such as revenue growth or operating cash flow patterns.
Plug |
Plug Power Polynomial Regression Price Forecast For the 23rd of December
Given 90 days horizon, the Polynomial Regression forecasted value of Plug Power on the next trading day is expected to be 2.54 with a mean absolute deviation of 0.1, mean absolute percentage error of 0.02, and the sum of the absolute errors of 6.05.Please note that although there have been many attempts to predict Plug 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 Plug Power's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Plug Power Stock Forecast Pattern
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Plug Power Forecasted Value
In the context of forecasting Plug Power'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. Plug Power's downside and upside margins for the forecasting period are 0.02 and 8.58, respectively. We have considered Plug Power'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 Plug Power stock data series using in forecasting. Note that when a statistical model is used to represent Plug Power 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 | 114.0704 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0992 |
| MAPE | Mean absolute percentage error | 0.0481 |
| SAE | Sum of the absolute errors | 6.0521 |
Predictive Modules for Plug Power
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Plug Power. 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 Plug Power
For every potential investor in Plug, whether a beginner or expert, Plug Power's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Plug Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Plug. Basic forecasting techniques help filter out the noise by identifying Plug Power's price trends.Plug Power 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 Plug Power stock to make a market-neutral strategy. Peer analysis of Plug Power could also be used in its relative valuation, which is a method of valuing Plug Power by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Plug Power 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 Plug Power'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 Plug Power's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Plug Power Market Strength Events
Market strength indicators help investors to evaluate how Plug Power stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Plug Power shares will generate the highest return on investment. By undertsting and applying Plug Power stock market strength indicators, traders can identify Plug Power entry and exit signals to maximize returns.
Plug Power Risk Indicators
The analysis of Plug Power'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 Plug Power's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting plug 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 | 4.23 | |||
| Semi Deviation | 5.04 | |||
| Standard Deviation | 6.09 | |||
| Variance | 37.07 | |||
| Downside Variance | 33.31 | |||
| Semi Variance | 25.37 | |||
| Expected Short fall | (5.54) |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Additional Information and Resources on Investing in Plug Stock
When determining whether Plug Power is a strong investment it is important to analyze Plug Power's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Plug Power's future performance. For an informed investment choice regarding Plug Stock, refer to the following important reports:Check out Historical Fundamental Analysis of Plug Power to cross-verify your projections. For information on how to trade Plug Stock refer to our How to Trade Plug Stock guide.You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.