FIRST TRUST Mutual Fund Forward View - Triple Exponential Smoothing
| FDHCX Fund | USD 17.60 -0.03 -0.17% |
First Trust Short's Triple Exponential Smoothing reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use. The model is fitted to available historical daily prices for FIRST TRUST. This page is updated as new daily closing prices become available for FIRST TRUST.
The Triple Exponential Smoothing forecasted value of First Trust Short on the next trading day is expected to be 17.58 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.40.As with simple exponential smoothing, in triple exponential smoothing models past FIRST TRUST 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 First Trust Short observations. All Triple Exponential Smoothing forecast figures shown for First Trust Short are reference data reflecting model output based on available historical prices. Triple Exponential Smoothing Price Forecast For the 26th of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of First Trust Short on the next trading day is expected to be 17.58 with a mean absolute deviation of 0.02 , mean absolute percentage error of 0.0009 , and the sum of the absolute errors of 1.40 .Please note that although there have been many attempts to predict FIRST 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 FIRST TRUST's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest FIRST TRUST | FIRST TRUST Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for First Trust Short uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
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 FIRST TRUST mutual fund data series using in forecasting. Note that when a statistical model is used to represent FIRST TRUST 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.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | 0.005 |
| MAD | Mean absolute deviation | 0.0233 |
| MAPE | Mean absolute percentage error | 0.0013 |
| SAE | Sum of the absolute errors | 1.3971 |
Other Forecasting Options for FIRST TRUST
Bollinger Bands applied to FIRST Mutual Fund price data measure how far FIRST has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to FIRST TRUST's price data. On-balance volume for FIRST Mutual Fund creates a running indicator of buying versus selling pressure in FIRST. Price departures from the channel boundary often mean-revert, offering tactical signals for FIRST TRUST's.FIRST TRUST Related Equities
FIRST TRUST's market space within the Bank Loan space is best grasped by looking at the firms listed below. Return on equity across these peers shows how well each firm turns capital into profit. Identifying peers that steadily beat or lag FIRST TRUST across many periods highlights durable competitive gaps. Combining quantitative ratios with qualitative context such as management quality and market position sharpens peer comparisons.
| Risk & Return | Correlation |
FIRST TRUST Market Strength Events
For investors tracking First Trust Short, market strength indicators offer quantitative evaluation of mutual fund behavior. These indicators add context to timing decisions around First Trust Short positions. These indicators capture shifts in momentum that may precede significant price moves in FIRST TRUST. These metrics provide actionable context for both entry and risk management decisions around First Trust Short.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 17.6 | |||
| Day Typical Price | 17.6 | |||
| Price Action Indicator | -0.01 | |||
| Period Momentum Indicator | -0.03 |
FIRST TRUST Risk Indicators
Analyzing FIRST TRUST's basic risk indicators provides investors with a structured view of the risk-return trade-off for first mutual fund. By identifying the level of risk embedded in FIRST TRUST's investment, investors can make informed decisions about position sizing. Analyzing FIRST TRUST's risk indicators gives investors important context for price forecasting. Understanding the risk in FIRST TRUST's investment allows investors to make informed choices about mitigating exposure.
| Mean Deviation | 0.1192 | |||
| Standard Deviation | 0.1638 | |||
| Variance | 0.0268 |
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 FIRST TRUST
Story coverage around First Trust Short often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. The practical risk is that faster visibility can increase both interest and skepticism at the same time.
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.