Refine Group Stock Forward View - Triple Exponential Smoothing

REFINE Stock   0.34  -0.01  -2.86%   
Refine Group's Triple Exponential Smoothing reference data is generated by applying the model to available daily closing prices. Accuracy metrics including mean absolute deviation are provided alongside the projection.
The Triple Exponential Smoothing forecasted value of Refine Group AB on the next trading day is expected to be 0.35 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 0.91.As with simple exponential smoothing, in triple exponential smoothing models past Refine Group observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Refine Group AB observations. Refine Group's Triple Exponential Smoothing reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
Triple exponential smoothing for Refine Group - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Refine Group prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Refine Group price movement. However, neither of these exponential smoothing models address any seasonality of Refine Group AB.

Triple Exponential Smoothing Price Forecast For the 28th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Refine Group AB on the next trading day is expected to be 0.35 with a mean absolute deviation of 0.02 , mean absolute percentage error of 0.0005 , and the sum of the absolute errors of 0.91 .
Please note that although there have been many attempts to predict Refine Stock 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 Refine Group's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

Forecasted Value

Forecasting Refine Group AB for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The projected forecast band currently runs from roughly 0.0034 on the downside to about 14.36 on the upside.
Market Value
0.34
0.0034
Downside
0.35
Expected Value
14.36
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Refine Group stock data series using in forecasting. Note that when a statistical model is used to represent Refine Group 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors -0.0045
MADMean absolute deviation0.0151
MAPEMean absolute percentage error0.0707
SAESum of the absolute errors0.9068
As with simple exponential smoothing, in triple exponential smoothing models past Refine Group observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Refine Group AB observations.

Other Forecasting Options for Refine Group

Analyzing Refine Group's price movement through moving averages at different time horizons reveals whether short-term momentum aligns with the longer-term trend. Touches of the upper or lower band in Refine Group's chart can signal overbought or oversold conditions.

Refine Group Related Equities

The peer firms below can help frame Refine Group's pricing and running costs in context. Market cap and total value checks frame Refine Group's size within the competitive field. When Refine Group breaks from its peer group on a key metric, it often signals a firm-level change worth exploring.
 Risk & Return  Correlation

Refine Group Market Strength Events

Market strength indicators for Refine Group stock provide a framework for assessing security responsiveness. These metrics are widely used to refine market timing and identify favorable moments to trade Refine Group.

Refine Group Risk Indicators

Assessing Refine Group's risk indicators is a critical component of any rigorous approach to forecasting its future price. Forecasting Refine Group's future price accurately requires understanding and quantifying the risks present in the investment.
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 Refine Group

A coverage review of Refine Group AB shows when the security is attracting above-average attention from contributors and market observers. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

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.

More Resources for Refine Stock Analysis