Coffee Commodity Forward View - Simple Regression
| KCUSX Commodity | 307.00 -2.75 -0.89% |
The Simple Regression forecast shown here for Coffee is reference data produced from its historical price series. The projected value and error measures below serve as reference information.
The Simple Regression forecasted value of Coffee on the next trading day is expected to be 272.87 with a mean absolute deviation of 15.32 and the sum of the absolute errors of 949.65.In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Coffee historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. This Simple Regression reference page for Coffee presents model-generated projections from historical price data for informational purposes. Simple Regression Price Forecast For the 25th of March
Given 90 days horizon, the Simple Regression forecasted value of Coffee on the next trading day is expected to be 272.87 with a mean absolute deviation of 15.32 , mean absolute percentage error of 306.05 , and the sum of the absolute errors of 949.65 .Please note that although there have been many attempts to predict Coffee Commodity prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Coffee's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Commodity Forecast Pattern
Forecasted Value
Forecasting Coffee for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The current forecast range spans downside near 270.85 and upside near 274.90.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Coffee commodity data series using in forecasting. Note that when a statistical model is used to represent Coffee 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 | 125.6721 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 15.3169 |
| MAPE | Mean absolute percentage error | 0.0486 |
| SAE | Sum of the absolute errors | 949.6458 |
Other Forecasting Options for Coffee
The distribution of Coffee's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in Coffee's chart that simple price charts miss.Coffee Related Commodities
Related goods for Coffee give broader market context for the forces that drive its price. Swing checks across these instruments help investors gauge the relative risk of holding Coffee.
| Risk & Return | Correlation |
Coffee Market Strength Events
Market strength indicators for Coffee give insight into the commodity's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Coffee.
Coffee Risk Indicators
A thorough review of Coffee's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in Coffee's allows investors to make better decisions about entry, sizing, and hedging.
| Mean Deviation | 1.48 | |||
| Standard Deviation | 1.96 | |||
| Variance | 3.83 |
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 Coffee
The amount of media and story coverage tied to Coffee can signal where market attention is concentrating at the moment. The practical risk is that faster visibility can increase both interest and skepticism at the same time.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.