CALVERT INCOME Mutual Fund Forward View - Simple Exponential Smoothing
| CINCX Fund | USD 15.24 0.05 0.33% |
Calvert Income Fund's Simple 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 CALVERT INCOME. This page is updated as new daily closing prices become available for CALVERT INCOME.
The Simple Exponential Smoothing forecasted value of Calvert Income Fund on the next trading day is expected to be 15.24 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.46.This simple exponential smoothing model begins by setting Calvert Income Fund forecast for the second period equal to the observation of the first period. In other words, recent CALVERT INCOME observations are given relatively more weight in forecasting than the older observations. All Simple Exponential Smoothing forecast figures shown for Calvert Income Fund are reference data reflecting model output based on available historical prices. Simple Exponential Smoothing Price Forecast For the 25th of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Calvert Income Fund on the next trading day is expected to be 15.24 with a mean absolute deviation of 0.02 , mean absolute percentage error of 0.0011 , and the sum of the absolute errors of 1.46 .Please note that although there have been many attempts to predict CALVERT 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 CALVERT INCOME'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 Calvert Income Fund 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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of CALVERT INCOME mutual fund data series using in forecasting. Note that when a statistical model is used to represent CALVERT INCOME 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 | 111.257 |
| Bias | Arithmetic mean of the errors | 3.0E-4 |
| MAD | Mean absolute deviation | 0.0239 |
| MAPE | Mean absolute percentage error | 0.0016 |
| SAE | Sum of the absolute errors | 1.46 |
Other Forecasting Options for CALVERT INCOME
Bollinger Bands applied to CALVERT Mutual Fund price data measure how far CALVERT has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to CALVERT INCOME's price data. On-balance volume for CALVERT Mutual Fund creates a running indicator of buying versus selling pressure in CALVERT. Price departures from the channel boundary often mean-revert, offering tactical signals for CALVERT INCOME's.CALVERT INCOME Related Equities
These stocks within the Intermediate Core-Plus Bond space are often compared to CALVERT INCOME by analysts and fund managers in the sector. Growth rate gaps between CALVERT INCOME and its peers often explain pricing differences in the market. Sector-wide trends across this peer group can help split company-level factors from broader forces. This type of review is most useful when done often to track how positions shift over time.
| Risk & Return | Correlation |
CALVERT INCOME Market Strength Events
For investors tracking Calvert Income Fund, market strength indicators offer quantitative evaluation of mutual fund behavior. These indicators add context to timing decisions around Calvert Income Fund positions. These indicators capture shifts in momentum that may precede significant price moves in CALVERT INCOME. These metrics provide actionable context for both entry and risk management decisions around Calvert Income Fund.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 15.24 | |||
| Day Typical Price | 15.24 | |||
| Price Action Indicator | 0.025 | |||
| Period Momentum Indicator | 0.05 | |||
| Relative Strength Index | 39.69 |
CALVERT INCOME Risk Indicators
Analyzing CALVERT INCOME's basic risk indicators provides investors with a structured view of the risk-return trade-off for calvert mutual fund. By identifying the level of risk embedded in CALVERT INCOME's investment, investors can make informed decisions about position sizing. Analyzing CALVERT INCOME's risk indicators gives investors important context for price forecasting. Understanding the risk in CALVERT INCOME's investment allows investors to make informed choices about mitigating exposure.
| Mean Deviation | 0.151 | |||
| Standard Deviation | 0.2069 | |||
| Variance | 0.0428 |
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 CALVERT INCOME
Coverage intensity for Calvert Income Fund 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.