SHENKMAN SHORT Mutual Fund Forward View - Double Exponential Smoothing

SCFFX Fund  USD 9.77  -0.01  -0.10%   
This page provides Double Exponential Smoothing reference data for Shenkman Short Duration, calculated from historical daily prices. The forecast output and associated deviation metrics are shown for informational use.
The Double Exponential Smoothing forecasted value of Shenkman Short Duration on the next trading day is expected to be 9.77 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.45.When Shenkman Short Duration 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 Shenkman Short Duration 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 SHENKMAN SHORT observations are given relatively more weight in forecasting than the older observations. SHENKMAN SHORT'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 SHENKMAN SHORT works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Shenkman Short Duration on the next trading day is expected to be 9.77 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0001 , and the sum of the absolute errors of 0.45 .
Please note that although there have been many attempts to predict SHENKMAN 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 SHENKMAN SHORT'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

For the next trading day, Macroaxis evaluates SHENKMAN SHORT's predictive range by looking for statistically meaningful downside and upside boundaries. The projected forecast band currently runs from roughly 9.67 on the downside to about 9.88 on the upside.
Market Value
9.77
9.77
Expected Value
9.88
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 SHENKMAN SHORT mutual fund data series using in forecasting. Note that when a statistical model is used to represent SHENKMAN SHORT 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 0.0012
MADMean absolute deviation0.0076
MAPEMean absolute percentage error8.0E-4
SAESum of the absolute errors0.4496
When Shenkman Short Duration 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 Shenkman Short Duration 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 SHENKMAN SHORT observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for SHENKMAN SHORT

The price movement of SHENKMAN is a central concern for all potential investors, regardless of their level of expertise. SHENKMAN Mutual Fund price charts can be difficult to interpret due to the noise present in the data.

SHENKMAN SHORT Related Equities

The following equities are related to SHENKMAN SHORT within the High Yield Bond space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing SHENKMAN SHORT against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

SHENKMAN SHORT Market Strength Events

Market strength indicators applied to SHENKMAN SHORT mutual fund help investors assess the relative momentum and resilience of the security in different market environments. By using these indicators, traders can make more informed decisions about when to buy or sell Shenkman Short Duration.

SHENKMAN SHORT Risk Indicators

Risk indicator analysis for SHENKMAN SHORT is essential for accurately projecting its future price trajectory. By identifying the level of risk embedded in SHENKMAN SHORT's investment, investors can make informed decisions about position sizing and risk mitigation.
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 SHENKMAN SHORT

The amount of media and story coverage tied to Shenkman Short Duration can signal where market attention is concentrating at the moment. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.

Other Macroaxis Stories

Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.