ASTOR LONG/SHORT Mutual Fund Forward View - Triple Exponential Smoothing

ASTZX Fund  USD 11.68  -0.02  -0.17%   
This reference page presents Triple Exponential Smoothing forecast data for Astor Longshort Fund. The model output shown here is derived from ASTOR LONG/SHORT's historical price series and is provided for informational purposes.
The Triple Exponential Smoothing forecasted value of Astor Longshort Fund on the next trading day is expected to be 11.66 with a mean absolute deviation of 0.05 and the sum of the absolute errors of 2.76.As with simple exponential smoothing, in triple exponential smoothing models past ASTOR LONG/SHORT 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 Astor Longshort Fund observations. This Triple Exponential Smoothing forecast data for Astor Longshort Fund is sourced from the most recent available trading data and is intended solely as reference information.
Triple exponential smoothing for ASTOR LONG/SHORT - 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 ASTOR LONG/SHORT 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 ASTOR LONG/SHORT price movement. However, neither of these exponential smoothing models address any seasonality of ASTOR LONG/SHORT.

Triple Exponential Smoothing Price Forecast For the 19th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Astor Longshort Fund on the next trading day is expected to be 11.66 with a mean absolute deviation of 0.05 , mean absolute percentage error of 0.01 , and the sum of the absolute errors of 2.76 .
Please note that although there have been many attempts to predict ASTOR 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 ASTOR LONG/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

The next-day forecast for Astor Longshort Fund focuses on identifying predictive downside and upside bands that can frame a realistic trading range. At the moment, the model places downside around 10.95 and upside around 12.36 for the forecasting period.
Market Value
11.68
11.66
Expected Value
12.36
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 ASTOR LONG/SHORT mutual fund data series using in forecasting. Note that when a statistical model is used to represent ASTOR LONG/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 -0.0033
MADMean absolute deviation0.0468
MAPEMean absolute percentage error0.0039
SAESum of the absolute errors2.7618
As with simple exponential smoothing, in triple exponential smoothing models past ASTOR LONG/SHORT 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 Astor Longshort Fund observations.

Other Forecasting Options for ASTOR LONG/SHORT

For every potential investor in ASTOR, whether a beginner or expert, ASTOR LONG/SHORT's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better.

ASTOR LONG/SHORT Related Equities

The following equities are related to ASTOR LONG/SHORT within the Tactical Allocation space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing ASTOR LONG/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

ASTOR LONG/SHORT Market Strength Events

Market strength indicators help investors to evaluate how ASTOR LONG/SHORT mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading ASTOR LONG/SHORT shares will generate the highest return on.

ASTOR LONG/SHORT Risk Indicators

The analysis of ASTOR LONG/SHORT's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in ASTOR LONG/SHORT's investment and either accepting that risk or mitigating 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 ASTOR LONG/SHORT

The amount of media and story coverage tied to Astor Longshort Fund can signal where market attention is concentrating at the moment. A disciplined read of coverage helps investors separate durable relevance from temporary noise.

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.