FEDERATED EQUITY Mutual Fund Forward View - Simple Regression
| LFEIX Fund | USD 20.59 -0.25 -1.20% |
The Simple Regression forecast shown here for FEDERATED 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 Simple Regression output serves as one input among many for analytical review.
The Simple Regression forecasted value of Federated Equity Income on the next trading day is expected to be 21.71 with a mean absolute deviation of 0.39 and the sum of the absolute errors of 23.71.In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Federated Equity Income historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. This Simple Regression reference page for FEDERATED EQUITY presents model-generated projections from historical price data for informational purposes. Simple Regression Price Forecast For the 23rd of March
Given 90 days horizon, the Simple Regression forecasted value of Federated Equity Income on the next trading day is expected to be 21.71 with a mean absolute deviation of 0.39 , mean absolute percentage error of 0.22 , and the sum of the absolute errors of 23.71 .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 EQUITY'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 EQUITY | FEDERATED EQUITY Price Prediction | Research Analysis |
Forecasted Value
Forecasting Federated Equity 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 Regression forecasting method's relative quality and the estimations of the prediction error of FEDERATED EQUITY mutual fund data series using in forecasting. Note that when a statistical model is used to represent FEDERATED 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.| AIC | Akaike Information Criteria | 116.5842 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.3887 |
| MAPE | Mean absolute percentage error | 0.0184 |
| SAE | Sum of the absolute errors | 23.7087 |
Other Forecasting Options for FEDERATED EQUITY
The distribution of FEDERATED 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 FEDERATED EQUITY's chart that simple price charts miss. The slope of FEDERATED 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 FEDERATED.FEDERATED EQUITY Related Equities
The peer firms below within the Large Value space can help frame FEDERATED EQUITY's pricing and running costs in context. Profit comparisons show whether FEDERATED EQUITY earns above or below average returns next to its peers. How FEDERATED EQUITY ranks within this group can shift over time as the competitive picture changes. These links can also guide portfolio spreading choices within the sector.
| Risk & Return | Correlation |
FEDERATED EQUITY Market Strength Events
Market strength indicators for FEDERATED EQUITY give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Federated Equity Income. Market strength analysis for Federated Equity Income works best when combined with volume and volatility data. For FEDERATED EQUITY, strength indicators are a practical complement to price and fundamental analysis.
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 20.59 | |||
| Day Typical Price | 20.59 | |||
| Price Action Indicator | -0.12 | |||
| Period Momentum Indicator | -0.25 | |||
| Relative Strength Index | 40.21 |
FEDERATED EQUITY Risk Indicators
A thorough review of FEDERATED EQUITY's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in FEDERATED EQUITY's allows investors to make better decisions about entry, sizing, and hedging. The assessment of FEDERATED EQUITY's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in FEDERATED EQUITY's provides context to choose between accepting or hedging exposure.
| Mean Deviation | 0.4622 | |||
| Semi Deviation | 0.5759 | |||
| Standard Deviation | 0.6229 | |||
| Variance | 0.388 | |||
| Downside Variance | 0.431 | |||
| Semi Variance | 0.3316 | |||
| Expected Short fall | -0.52 |
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 EQUITY
A coverage review of Federated Equity Income shows when the security is attracting above-average attention from contributors and market observers. 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.