BlackRock Advantage Mutual Fund Forward View - Triple Exponential Smoothing

BDSKX Fund  USD 19.79  -0.47  -2.32%   
BlackRock Advantage's Triple Exponential Smoothing reference data reflects the model's output when applied to available daily price observations. The projected value and error measures below serve as reference information.
The Triple Exponential Smoothing forecasted value of BlackRock Advantage Small on the next trading day is expected to be 19.85 with a mean absolute deviation of 0.21 and the sum of the absolute errors of 12.17.As with simple exponential smoothing, in triple exponential smoothing models past BlackRock Advantage 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 BlackRock Advantage Small observations. BlackRock Advantage's Triple Exponential Smoothing reference values are drawn from available trading data and are presented for informational reference only.
Triple exponential smoothing for BlackRock Advantage - 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 BlackRock Advantage 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 BlackRock Advantage price movement. However, neither of these exponential smoothing models address any seasonality of BlackRock Advantage Small.

Triple Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of BlackRock Advantage Small on the next trading day is expected to be 19.85 with a mean absolute deviation of 0.21 , mean absolute percentage error of 0.07 , and the sum of the absolute errors of 12.17 .
Please note that although there have been many attempts to predict BlackRock 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 BlackRock Advantage'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 BlackRock Advantage's predictive range by looking for statistically meaningful downside and upside boundaries. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Market Value
19.79
19.85
Expected Value
21.02
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 BlackRock Advantage mutual fund data series using in forecasting. Note that when a statistical model is used to represent BlackRock Advantage 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 -0.0094
MADMean absolute deviation0.2063
MAPEMean absolute percentage error0.0099
SAESum of the absolute errors12.173
As with simple exponential smoothing, in triple exponential smoothing models past BlackRock Advantage 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 BlackRock Advantage Small observations.

Other Forecasting Options for BlackRock Advantage

Understanding BlackRock Advantage's price movement is a critical first step for any investor considering BlackRock. The noise present in BlackRock Mutual Fund price charts can easily mislead investors who rely solely on visual inspection.

BlackRock Advantage Related Equities

The following equities are related to BlackRock Advantage within the Small Blend space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing BlackRock Advantage 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

BlackRock Advantage Market Strength Events

Market strength indicators provide a structured view of how BlackRock Advantage mutual fund is positioned relative to prevailing market trends. Investors use these tools to determine the best times to initiate or close positions in BlackRock Advantage Small.

BlackRock Advantage Risk Indicators

The analysis of BlackRock Advantage's risk metrics is one of the most important steps in accurately projecting its future price. This process involves measuring the level of investment risk in BlackRock Advantage's and determining how best to manage it.
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 BlackRock Advantage

The amount of media and story coverage tied to BlackRock Advantage Small can signal where market attention is concentrating at the moment. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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.