Surge Energy Pink Sheet Forecast - Polynomial Regression
| ZPTAF Stock | USD 5.60 0.06 1.06% |
The Polynomial Regression forecasted value of Surge Energy on the next trading day is expected to be 5.57 with a mean absolute deviation of 0.14 and the sum of the absolute errors of 8.63. Surge Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Surge Energy stock prices and determine the direction of Surge Energy's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Surge Energy's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Surge Energy to cross-verify your projections. Surge |
Most investors in Surge Energy 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 Surge Energy's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Surge Energy's price structures and extracts relationships that further increase the generated results' accuracy.
Surge Energy polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Surge Energy as well as the accuracy indicators are determined from the period prices. Surge Energy Polynomial Regression Price Forecast For the 25th of April
Given 90 days horizon, the Polynomial Regression forecasted value of Surge Energy on the next trading day is expected to be 5.57 with a mean absolute deviation of 0.14, mean absolute percentage error of 0.03, and the sum of the absolute errors of 8.63.Please note that although there have been many attempts to predict Surge Pink Sheet 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 Surge Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Surge Energy Pink Sheet Forecast Pattern
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Surge Energy Forecasted Value
In the context of forecasting Surge Energy's Pink Sheet 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. Surge Energy's downside and upside margins for the forecasting period are 3.59 and 7.55, respectively. We have considered Surge Energy'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 Surge Energy pink sheet data series using in forecasting. Note that when a statistical model is used to represent Surge Energy pink sheet, 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 | 114.682 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1414 |
| MAPE | Mean absolute percentage error | 0.0276 |
| SAE | Sum of the absolute errors | 8.6267 |
Predictive Modules for Surge Energy
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Surge Energy. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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 Surge Energy'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 Surge Energy
For every potential investor in Surge, whether a beginner or expert, Surge Energy's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Surge Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Surge. Basic forecasting techniques help filter out the noise by identifying Surge Energy's price trends.View Surge Energy Related Equities
| Risk & Return | Correlation |
Surge Energy Technical and Predictive Analytics
The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Surge Energy'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 Surge Energy's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Surge Energy Market Strength Events
Market strength indicators help investors to evaluate how Surge Energy pink sheet reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Surge Energy shares will generate the highest return on investment. By undertsting and applying Surge Energy pink sheet market strength indicators, traders can identify Surge Energy entry and exit signals to maximize returns.
Surge Energy Risk Indicators
The analysis of Surge Energy'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 Surge Energy's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting surge pink sheet 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 | 1.53 | |||
| Semi Deviation | 1.5 | |||
| Standard Deviation | 1.94 | |||
| Variance | 3.77 | |||
| Downside Variance | 3.45 | |||
| Semi Variance | 2.25 | |||
| Expected Short fall | (1.79) |
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 Surge Energy 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, Surge Energy's short interest history, or implied volatility extrapolated from Surge Energy options trading.
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.Check out Historical Fundamental Analysis of Surge Energy to cross-verify your projections. Note that the Surge Energy information on this page should be used as a complementary analysis to other Surge Energy'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 ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.
Complementary Tools for Surge Pink Sheet analysis
When running Surge Energy's price analysis, check to measure Surge Energy'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 Surge Energy is operating at the current time. Most of Surge Energy's value examination focuses on studying past and present price action to predict the probability of Surge Energy's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Surge Energy's price. Additionally, you may evaluate how the addition of Surge Energy to your portfolios can decrease your overall portfolio volatility.
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