Crude Oil Commodity Forecast - Simple Exponential Smoothing
| CLUSD Commodity | 61.07 1.71 2.88% |
Momentum 0
Sell Peaked
Oversold | Overbought |
Using Crude Oil hype-based prediction, you can estimate the value of Crude Oil from the perspective of Crude Oil response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Exponential Smoothing forecasted value of Crude Oil on the next trading day is expected to be 61.00 with a mean absolute deviation of 0.77 and the sum of the absolute errors of 46.84. Crude Oil after-hype prediction price | USD 61.07 |
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 commodity price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Crude |
Crude Oil Additional Predictive Modules
Most predictive techniques to examine Crude price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Crude using various technical indicators. When you analyze Crude 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 |
Crude Oil Simple Exponential Smoothing Price Forecast For the 25th of January
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Crude Oil on the next trading day is expected to be 61.00 with a mean absolute deviation of 0.77, mean absolute percentage error of 0.91, and the sum of the absolute errors of 46.84.Please note that although there have been many attempts to predict Crude Commodity 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 Crude Oil's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Crude Oil Commodity Forecast Pattern
Crude Oil Forecasted Value
In the context of forecasting Crude Oil's Commodity 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. Crude Oil's downside and upside margins for the forecasting period are 59.38 and 62.63, respectively. We have considered Crude Oil'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 Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Crude Oil commodity data series using in forecasting. Note that when a statistical model is used to represent Crude Oil commodity, 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 | 118.0148 |
| Bias | Arithmetic mean of the errors | -0.009 |
| MAD | Mean absolute deviation | 0.7678 |
| MAPE | Mean absolute percentage error | 0.0131 |
| SAE | Sum of the absolute errors | 46.8358 |
Predictive Modules for Crude Oil
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Crude Oil. Regardless of method or technology, however, to accurately forecast the commodity market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the commodity 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 Crude Oil'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.
Crude Oil Estimiated After-Hype Price Prediction Volatility
As far as predicting the price of Crude Oil at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Crude Oil or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Commodity prices, such as prices of Crude Oil, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Crude Oil Commodity Price Prediction Analysis
Have you ever been surprised when a price of a Commodity such as Crude Oil is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Crude Oil backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Commodity price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Crude Oil, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.01 | 1.63 | 0.00 | 0.00 | 0 Events / Month | 0 Events / Month | In 5 to 10 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
61.07 | 61.07 | 0.00 |
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Crude Oil Hype Timeline
Crude Oil is currently traded for 61.07. This commodity is not elastic to its hype. The commodity elasticity to the hype of similar commodities is 0.0. Crude is projected not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is projected to be very small, whereas the daily expected return is currently at 0.01%. %. The volatility of related hype on Crude Oil is about 0.0%, with the expected price after the next announcement by competition of 61.07. Assuming the 90 days horizon the next projected press release will be in 5 to 10 days. Check out Trending Equities to better understand how to build diversified portfolios. Also, note that the market value of any commodity could be closely tied with the direction of predictive economic indicators such as signals in main economic indicators.Crude Oil Related Hype Analysis
Having access to credible news sources related to Crude Oil's direct competition is more important than ever and may enhance your ability to predict Crude Oil's future price movements. Getting to know how Crude Oil's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Crude Oil may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| ZFUSD | Five Year Treasury Note | 0.00 | 0 per month | 0.00 | (0.71) | 0.17 | (0.24) | 0.58 | |
| CTUSX | Cotton | 0.00 | 0 per month | 0.00 | (0.11) | 1.08 | (1.31) | 4.51 | |
| LEUSX | Live Cattle Futures | 0.00 | 0 per month | 0.00 | (0.10) | 2.39 | (3.01) | 6.67 | |
| CLUSD | Crude Oil | 0.00 | 0 per month | 0.00 | (0.05) | 2.39 | (2.73) | 7.72 | |
| NGUSD | Natural Gas | 0.00 | 0 per month | 6.12 | 0.04 | 12.05 | (8.04) | 26.13 | |
| ZRUSD | Rough Rice Futures | 0.00 | 0 per month | 5.16 | 0.1 | 4.19 | (2.76) | 90.61 |
Other Forecasting Options for Crude Oil
For every potential investor in Crude, whether a beginner or expert, Crude Oil's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Crude Commodity price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Crude. Basic forecasting techniques help filter out the noise by identifying Crude Oil's price trends.Crude Oil Related Commodities
One prevalent trading approach among algorithmic traders in the commodities sector involves employing market-neutral strategies, wherein each trade is designed to hedge away specific risks. Given that this approach necessitates two distinct transactions, if one position underperforms unexpectedly, the other can potentially offset some of the losses. This method can be applied to commodities such as Crude Oil, pairing it with other commodities or financial instruments to create a balanced, market-neutral setup.
| Risk & Return | Correlation |
Crude Oil Market Strength Events
Market strength indicators help investors to evaluate how Crude Oil commodity reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Crude Oil shares will generate the highest return on investment. By undertsting and applying Crude Oil commodity market strength indicators, traders can identify Crude Oil entry and exit signals to maximize returns.
| Accumulation Distribution | 7907.17 | |||
| Daily Balance Of Power | 0.9293 | |||
| Rate Of Daily Change | 1.03 | |||
| Day Median Price | 60.44 | |||
| Day Typical Price | 60.65 | |||
| Price Action Indicator | 1.48 | |||
| Period Momentum Indicator | 1.71 |
Crude Oil Risk Indicators
The analysis of Crude Oil'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 Crude Oil's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting crude commodity 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 | 1.23 | |||
| Standard Deviation | 1.6 | |||
| Variance | 2.57 |
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.
Story Coverage note for Crude Oil
The number of cover stories for Crude Oil depends on current market conditions and Crude Oil's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Crude Oil is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Crude Oil's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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