FS Energy Pink Sheet Forecast - Polynomial Regression
| FSENDelisted Stock | USD 14.09 0.00 0.00% |
The Polynomial Regression forecasted value of FS Energy And on the next trading day is expected to be 14.03 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.23. FSEN Pink Sheet Forecast is based on your current time horizon.
As of today the relative strength index (rsi) of FS Energy's share price is below 20 . This usually indicates that the pink sheet is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using FS Energy hype-based prediction, you can estimate the value of FS Energy And from the perspective of FS Energy response to recently generated media hype and the effects of current headlines on its competitors.
The Polynomial Regression forecasted value of FS Energy And on the next trading day is expected to be 14.03 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.23. FS Energy after-hype prediction price | USD 13.59 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as pink sheet price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
FSEN |
FS Energy Additional Predictive Modules
Most predictive techniques to examine FSEN price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for FSEN using various technical indicators. When you analyze FSEN charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
FS Energy Polynomial Regression Price Forecast For the 8th of January
Given 90 days horizon, the Polynomial Regression forecasted value of FS Energy And on the next trading day is expected to be 14.03 with a mean absolute deviation of 0.09, mean absolute percentage error of 0.01, and the sum of the absolute errors of 5.23.Please note that although there have been many attempts to predict FSEN 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 FS Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
FS Energy Pink Sheet Forecast Pattern
| Backtest FS Energy | FS Energy Price Prediction | Buy or Sell Advice |
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 FS Energy pink sheet data series using in forecasting. Note that when a statistical model is used to represent FS 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 | 113.7908 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0858 |
| MAPE | Mean absolute percentage error | 0.0063 |
| SAE | Sum of the absolute errors | 5.2331 |
Predictive Modules for FS 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 FS Energy And. 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 FS 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.
FS Energy 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 FS Energy pink sheet to make a market-neutral strategy. Peer analysis of FS Energy could also be used in its relative valuation, which is a method of valuing FS Energy by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
FS Energy Market Strength Events
Market strength indicators help investors to evaluate how FS 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 FS Energy shares will generate the highest return on investment. By undertsting and applying FS Energy pink sheet market strength indicators, traders can identify FS Energy And entry and exit signals to maximize returns.
FS Energy Risk Indicators
The analysis of FS 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 FS Energy's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fsen 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 | 0.1365 | |||
| Standard Deviation | 0.5639 | |||
| Variance | 0.318 |
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.
Pair Trading with FS Energy
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if FS Energy position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in FS Energy will appreciate offsetting losses from the drop in the long position's value.Moving together with FSEN Pink Sheet
Moving against FSEN Pink Sheet
The ability to find closely correlated positions to FS Energy could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace FS Energy when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back FS Energy - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling FS Energy And to buy it.
The correlation of FS Energy is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as FS Energy moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if FS Energy And moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for FS Energy can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in american community survey. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
Other Consideration for investing in FSEN Pink Sheet
If you are still planning to invest in FS Energy And check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the FS Energy's history and understand the potential risks before investing.
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