FEDERATED HIGH Mutual Fund Forward View - Simple Moving Average
| FHIIX Fund | USD 6.76 -0.03 -0.44% |
The Simple Moving Average forecast shown here for FEDERATED HIGH 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 Simple Moving Average output serves as one input among many for analytical review.
The Simple Moving Average forecasted value of Federated High Income on the next trading day is expected to be 6.76 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.57.The simple moving average model is conceptually a linear regression of the current value of Federated High Income price series against current and previous (unobserved) value of FEDERATED HIGH. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future This Simple Moving Average reference page for FEDERATED HIGH presents model-generated projections from historical price data for informational purposes. Simple Moving Average Price Forecast For the 24th of March
Given 90 days horizon, the Simple Moving Average forecasted value of Federated High Income on the next trading day is expected to be 6.76 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0002 , and the sum of the absolute errors of 0.57 .Please note that although there have been many attempts to predict FEDERATED 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 FEDERATED HIGH's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest FEDERATED HIGH | FEDERATED HIGH Price Prediction | Research Analysis |
Forecasted Value
Forecasting Federated High Income for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. 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 Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of FEDERATED HIGH mutual fund data series using in forecasting. Note that when a statistical model is used to represent FEDERATED HIGH 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 | 105.8008 |
| Bias | Arithmetic mean of the errors | 0.0025 |
| MAD | Mean absolute deviation | 0.0097 |
| MAPE | Mean absolute percentage error | 0.0014 |
| SAE | Sum of the absolute errors | 0.57 |
Other Forecasting Options for FEDERATED HIGH
The distribution of FEDERATED HIGH's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in FEDERATED HIGH's chart that simple price charts miss. The slope of FEDERATED HIGH's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in FEDERATED.FEDERATED HIGH Related Equities
These stocks within the High Yield Bond space are often compared to FEDERATED HIGH by analysts and fund managers in the sector. Checking cash flow across this peer set helps gauge FEDERATED HIGH's relative financial strength. When FEDERATED HIGH breaks from its peer group on a key metric, it often signals a firm-level change worth exploring. Peer review is one of the most widely used methods in stock research and portfolio building.
| Risk & Return | Correlation |
FEDERATED HIGH Market Strength Events
Market strength indicators for FEDERATED HIGH give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Federated High Income. Market strength analysis for Federated High Income works best when combined with volume and volatility data. For FEDERATED HIGH, strength indicators are a practical complement to price and fundamental analysis.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 6.76 | |||
| Day Typical Price | 6.76 | |||
| Price Action Indicator | -0.01 | |||
| Period Momentum Indicator | -0.03 | |||
| Relative Strength Index | 32.46 |
FEDERATED HIGH Risk Indicators
A thorough review of FEDERATED HIGH's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in FEDERATED HIGH's allows investors to make better decisions about entry, sizing, and hedging. The assessment of FEDERATED HIGH's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in FEDERATED HIGH's provides context to choose between accepting or hedging exposure.
| Mean Deviation | 0.1247 | |||
| Standard Deviation | 0.1689 | |||
| Variance | 0.0285 |
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 FEDERATED HIGH
The amount of media and story coverage tied to Federated High Income can signal where market attention is concentrating at the moment. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
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.