DOW JONES Mutual Fund Forward View - Triple Exponential Smoothing

RYDHX Fund  USD 108.83  -0.20  -0.18%   
The Triple Exponential Smoothing reference data for DOW JONES is derived from the equity's published trading history. The resulting forecast and deviation statistics are presented as reference data for informational context. Forecast values and accuracy statistics are presented for informational purposes.
The Triple Exponential Smoothing forecasted value of Dow Jones Industrial on the next trading day is expected to be 108.75 with a mean absolute deviation of 0.73 and the sum of the absolute errors of 43.50.As with simple exponential smoothing, in triple exponential smoothing models past DOW JONES 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 Dow Jones Industrial observations. The forecast reference data presented here for Dow Jones Industrial reflects Triple Exponential Smoothing model output and is intended as reference material for analytical use.
Triple exponential smoothing for DOW JONES - 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 DOW JONES 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 DOW JONES price movement. However, neither of these exponential smoothing models address any seasonality of Dow Jones Industrial.

Triple Exponential Smoothing Price Forecast For the 26th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Dow Jones Industrial on the next trading day is expected to be 108.75 with a mean absolute deviation of 0.73 , mean absolute percentage error of 0.84 , and the sum of the absolute errors of 43.50 .
Please note that although there have been many attempts to predict DOW 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 DOW JONES'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

This next-day forecast for Dow Jones Industrial uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. The current forecast range spans downside near 107.92 and upside near 109.57.
Market Value
108.83
107.92
Downside
108.75
Expected Value
109.57
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 DOW JONES mutual fund data series using in forecasting. Note that when a statistical model is used to represent DOW JONES 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 0.055
MADMean absolute deviation0.725
MAPEMean absolute percentage error0.0063
SAESum of the absolute errors43.5003
As with simple exponential smoothing, in triple exponential smoothing models past DOW JONES 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 Dow Jones Industrial observations.

Other Forecasting Options for DOW JONES

Fibonacci retracement levels applied to DOW Mutual Fund price swings identify potential support and resistance zones. Extreme price moves in DOW occur more frequently than standard risk models assume. Support and resistance levels derived from DOW JONES's historical data identify zones where buying or selling pressure has stalled moves.

DOW JONES Related Equities

The peer firms below within the Large Value space can help frame DOW JONES's pricing and running costs in context. Revenue and margin checks across this group help investors set expectations for DOW JONES's results.
 Risk & Return  Correlation

DOW JONES Market Strength Events

Tracking market strength indicators for DOW JONES provides context for understanding mutual fund momentum dynamics. Tracking these indicators helps identify periods where trading DOW JONES is likely to be most rewarding. These tools are essential for timing trades in Dow Jones Industrial with a quantitative framework.

DOW JONES Risk Indicators

Properly assessing DOW JONES's risk indicators is a prerequisite for building reliable price forecasts. This analysis provides context for determining the appropriate level of risk to accept when holding DOW JONES's. Analyzing DOW JONES's risk indicators provides a critical input for investment risk management.
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 DOW JONES

Coverage intensity for Dow Jones Industrial 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.