Challenger Energy Pink Sheet Forecast - Polynomial Regression
| BSHPF Stock | USD 0.15 0.00 0.00% |
The Polynomial Regression forecasted value of Challenger Energy Group on the next trading day is expected to be 0.16 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.40. Challenger Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Challenger Energy's historical fundamentals, such as revenue growth or operating cash flow patterns.
As of 2nd of January 2026 the relative strength index (rsi) of Challenger Energy's share price is below 20 suggesting 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 Challenger Energy hype-based prediction, you can estimate the value of Challenger Energy Group from the perspective of Challenger Energy response to recently generated media hype and the effects of current headlines on its competitors.
The Polynomial Regression forecasted value of Challenger Energy Group on the next trading day is expected to be 0.16 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.40. Challenger Energy after-hype prediction price | USD 0.15 |
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.
Challenger |
Challenger Energy Additional Predictive Modules
Most predictive techniques to examine Challenger price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Challenger using various technical indicators. When you analyze Challenger 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 |
Challenger Energy Polynomial Regression Price Forecast For the 3rd of January
Given 90 days horizon, the Polynomial Regression forecasted value of Challenger Energy Group on the next trading day is expected to be 0.16 with a mean absolute deviation of 0.01, mean absolute percentage error of 0.000085, and the sum of the absolute errors of 0.40.Please note that although there have been many attempts to predict Challenger 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 Challenger Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Challenger Energy Pink Sheet Forecast Pattern
| Backtest Challenger Energy | Challenger 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 Challenger Energy pink sheet data series using in forecasting. Note that when a statistical model is used to represent Challenger 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 | 108.7326 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0066 |
| MAPE | Mean absolute percentage error | 0.0406 |
| SAE | Sum of the absolute errors | 0.4006 |
Predictive Modules for Challenger 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 Challenger 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.Challenger 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 Challenger Energy pink sheet to make a market-neutral strategy. Peer analysis of Challenger Energy could also be used in its relative valuation, which is a method of valuing Challenger Energy by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Challenger Energy Market Strength Events
Market strength indicators help investors to evaluate how Challenger 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 Challenger Energy shares will generate the highest return on investment. By undertsting and applying Challenger Energy pink sheet market strength indicators, traders can identify Challenger Energy Group entry and exit signals to maximize returns.
Challenger Energy Risk Indicators
The analysis of Challenger 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 Challenger Energy's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting challenger 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 | 2.7 | |||
| Semi Deviation | 3.29 | |||
| Standard Deviation | 5.22 | |||
| Variance | 27.27 | |||
| Downside Variance | 105.7 | |||
| Semi Variance | 10.85 | |||
| Expected Short fall | (10.35) |
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 Challenger Pink Sheet
Challenger Energy financial ratios help investors to determine whether Challenger Pink Sheet 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 Challenger with respect to the benefits of owning Challenger Energy security.