AQR EQUITY Mutual Fund Forward View - Triple Exponential Smoothing

QMNIX Fund  USD 12.04  0.01  0.08%   
The Triple Exponential Smoothing forecast shown here for AQR EQUITY is reference data produced from its historical price series. The projected value and error measures below serve as reference information. This data is provided for reference and analytical review. The Triple Exponential Smoothing output serves as one input among many for analytical review.
The Triple Exponential Smoothing forecasted value of Aqr Equity Market on the next trading day is expected to be 12.05 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.39.As with simple exponential smoothing, in triple exponential smoothing models past AQR EQUITY 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 Aqr Equity Market observations. This Triple Exponential Smoothing reference page for AQR EQUITY presents model-generated projections from historical price data for informational purposes.
Triple exponential smoothing for AQR EQUITY - 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 AQR EQUITY 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 AQR EQUITY price movement. However, neither of these exponential smoothing models address any seasonality of Aqr Equity Market.

Triple Exponential Smoothing Price Forecast For the 26th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Aqr Equity Market on the next trading day is expected to be 12.05 with a mean absolute deviation of 0.04 , mean absolute percentage error of 0.0027 , and the sum of the absolute errors of 2.39 .
Please note that although there have been many attempts to predict AQR 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 AQR EQUITY'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 Aqr Equity Market focuses on identifying predictive downside and upside bands that can frame a realistic trading range. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Market Value
12.04
12.05
Expected Value
12.46
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 AQR EQUITY mutual fund data series using in forecasting. Note that when a statistical model is used to represent AQR EQUITY 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 0.0023
MADMean absolute deviation0.0398
MAPEMean absolute percentage error0.0033
SAESum of the absolute errors2.3875
As with simple exponential smoothing, in triple exponential smoothing models past AQR EQUITY 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 Aqr Equity Market observations.

Other Forecasting Options for AQR EQUITY

The distribution of AQR EQUITY's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in AQR EQUITY's chart that simple price charts miss. The slope of AQR EQUITY's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in AQR.

AQR EQUITY Related Equities

These stocks within the Equity Market Neutral space are often compared to AQR EQUITY by analysts and fund managers in the sector. Checking cash flow across this peer set helps gauge AQR EQUITY's relative financial strength.
 Risk & Return  Correlation

AQR EQUITY Market Strength Events

Market strength indicators for AQR EQUITY give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Aqr Equity Market. Market strength analysis for Aqr Equity Market works best when combined with volume and volatility data. For AQR EQUITY, strength indicators are a practical complement to price and fundamental analysis.

AQR EQUITY Risk Indicators

A thorough review of AQR EQUITY's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in AQR EQUITY's allows investors to make better decisions about entry, sizing, and hedging. The assessment of AQR EQUITY's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in AQR EQUITY's provides context to choose between accepting or hedging exposure.
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 AQR EQUITY

Coverage intensity for Aqr Equity Market matters because narrative visibility can influence sentiment, participation, and volatility around the name. 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.