Energy Transfer Stock Forecast - Naive Prediction
| ET-PI Stock | 11.95 0.01 0.08% |
The Naive Prediction forecasted value of Energy Transfer LP on the next trading day is expected to be 11.84 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.56. Energy Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Energy Transfer's historical fundamentals, such as revenue growth or operating cash flow patterns.
Energy |
Energy Transfer Cash Forecast
Predicting cash flow or other financial metrics requires analysts to utilize a variety of statistical methods, techniques, and algorithms. These tools help uncover hidden patterns in the Energy Transfer's financial statements, enabling forecasts of their impact on future stock prices.
Cash | First Reported 2010-12-31 | Previous Quarter 161 M | Current Value 225.9 M | Quarterly Volatility 45.8 M |
Energy Transfer Naive Prediction Price Forecast For the 28th of November
Given 90 days horizon, the Naive Prediction forecasted value of Energy Transfer LP on the next trading day is expected to be 11.84 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.56.Please note that although there have been many attempts to predict Energy 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 Energy Transfer's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Energy Transfer Stock Forecast Pattern
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Energy Transfer Forecasted Value
In the context of forecasting Energy Transfer'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. Energy Transfer's downside and upside margins for the forecasting period are 11.01 and 12.67, respectively. We have considered Energy Transfer'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Energy Transfer stock data series using in forecasting. Note that when a statistical model is used to represent Energy Transfer 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 | 113.3649 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0747 |
| MAPE | Mean absolute percentage error | 0.0064 |
| SAE | Sum of the absolute errors | 4.5563 |
Predictive Modules for Energy Transfer
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Energy Transfer LP. 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 Energy Transfer
For every potential investor in Energy, whether a beginner or expert, Energy Transfer's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Energy Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Energy. Basic forecasting techniques help filter out the noise by identifying Energy Transfer's price trends.Energy Transfer 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 Energy Transfer stock to make a market-neutral strategy. Peer analysis of Energy Transfer could also be used in its relative valuation, which is a method of valuing Energy Transfer by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Energy Transfer LP 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 Energy Transfer'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 Energy Transfer's current price.| Cycle Indicators | ||
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Energy Transfer Market Strength Events
Market strength indicators help investors to evaluate how Energy Transfer stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Energy Transfer shares will generate the highest return on investment. By undertsting and applying Energy Transfer stock market strength indicators, traders can identify Energy Transfer LP entry and exit signals to maximize returns.
Energy Transfer Risk Indicators
The analysis of Energy Transfer'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 Energy Transfer's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting energy 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 | 0.6072 | |||
| Semi Deviation | 0.6333 | |||
| Standard Deviation | 0.8266 | |||
| Variance | 0.6833 | |||
| Downside Variance | 0.5586 | |||
| Semi Variance | 0.4011 | |||
| Expected Short fall | (0.70) |
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
When determining whether Energy Transfer LP is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Energy Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Energy Transfer Lp Stock. Highlighted below are key reports to facilitate an investment decision about Energy Transfer Lp Stock:Check out Historical Fundamental Analysis of Energy Transfer to cross-verify your projections. You can also try the Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.