MFS CONSERVATIVE Mutual Fund Forward View - Double Exponential Smoothing

MACFX Fund  USD 16.54  -0.16  -0.96%   
MFS CONSERVATIVE's Double 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 Double Exponential Smoothing forecasted value of Mfs Servative Allocation on the next trading day is expected to be 16.51 with a mean absolute deviation of 0.05 and the sum of the absolute errors of 2.67.When Mfs Servative Allocation 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 Mfs Servative Allocation trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent MFS CONSERVATIVE observations are given relatively more weight in forecasting than the older observations. MFS CONSERVATIVE's Double Exponential Smoothing reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for MFS CONSERVATIVE works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Mfs Servative Allocation on the next trading day is expected to be 16.51 with a mean absolute deviation of 0.05 , mean absolute percentage error of 0.0034 , and the sum of the absolute errors of 2.67 .
Please note that although there have been many attempts to predict MFS Mutual Fund 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 MFS CONSERVATIVE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

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Forecasted Value

The next-day forecast for Mfs Servative Allocation focuses on identifying predictive downside and upside bands that can frame a realistic trading range. At the moment, the model places downside around 16.17 and upside around 16.85 for the forecasting period.
Market Value
16.54
16.51
Expected Value
16.85
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of MFS CONSERVATIVE mutual fund data series using in forecasting. Note that when a statistical model is used to represent MFS CONSERVATIVE mutual fund, 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 0.0117
MADMean absolute deviation0.0453
MAPEMean absolute percentage error0.0027
SAESum of the absolute errors2.6698
When Mfs Servative Allocation 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 Mfs Servative Allocation trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent MFS CONSERVATIVE observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for MFS CONSERVATIVE

Analyzing MFS CONSERVATIVE'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 MFS CONSERVATIVE's chart can signal overbought or oversold conditions.

MFS CONSERVATIVE Related Equities

These related stocks within the Allocation--30% to 50% Equity space give benchmarks for judging MFS CONSERVATIVE's results, margins, and growth trend. Return on equity across these peers shows how well each firm turns capital into profit. When MFS CONSERVATIVE breaks from its peer group on a key metric, it often signals a firm-level change worth exploring.
 Risk & Return  Correlation

MFS CONSERVATIVE Market Strength Events

Market strength indicators for MFS CONSERVATIVE mutual fund provide a framework for assessing security responsiveness. These metrics are widely used to refine market timing and identify favorable moments to trade MFS CONSERVATIVE.

MFS CONSERVATIVE Risk Indicators

Assessing MFS CONSERVATIVE's risk indicators is a critical component of any rigorous approach to forecasting its future price. Forecasting MFS CONSERVATIVE'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 MFS CONSERVATIVE

Coverage intensity for Mfs Servative Allocation matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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.