Calvert Emerging Mutual Fund Forward View

CEMAX Fund  USD 11.92  -0.22  -1.81%   
This reference page presents Naive Prediction forecast data for Calvert Emerging Markets. The model output shown here is derived from Calvert Emerging's historical price series and is provided for informational purposes.
The Naive Prediction forecasted value of Calvert Emerging Markets on the next trading day is expected to be 12.16 with a mean absolute deviation of 0.13 and the sum of the absolute errors of 7.81.This model is not at all useful as a medium-long range forecasting tool of Calvert Emerging Markets. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Calvert Emerging. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights. This Naive Prediction forecast data for Calvert Emerging Markets is sourced from the most recent available trading data and is intended solely as reference information.
A naive forecasting model for Calvert Emerging is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Calvert Emerging Markets value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Naive Prediction Price Forecast For the 20th of March

Given 90 days horizon, the Naive Prediction forecasted value of Calvert Emerging Markets on the next trading day is expected to be 12.16 with a mean absolute deviation of 0.13 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 7.81 .
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 Emerging'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

For the next trading day, Macroaxis evaluates Calvert Emerging's predictive range by looking for statistically meaningful downside and upside boundaries. The current forecast range spans downside near 10.80 and upside near 13.53.
Market Value
11.92
12.16
Expected Value
13.53
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Calvert Emerging mutual fund data series using in forecasting. Note that when a statistical model is used to represent Calvert Emerging 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 Criteria116.2217
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1259
MAPEMean absolute percentage error0.0102
SAESum of the absolute errors7.8056
This model is not at all useful as a medium-long range forecasting tool of Calvert Emerging Markets. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Calvert Emerging. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Other Forecasting Options for Calvert Emerging

For every potential investor in Calvert, whether a beginner or expert, Calvert Emerging's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better.

Calvert Emerging Related Equities

The following equities are related to Calvert Emerging within the Diversified Emerging Mkts space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Calvert Emerging against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

Calvert Emerging Market Strength Events

Market strength indicators help investors to evaluate how Calvert Emerging mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Calvert Emerging shares will generate the highest return on.

Calvert Emerging Risk Indicators

The analysis of Calvert Emerging's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Calvert Emerging's investment and either accepting that risk or mitigating it.
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 Emerging

The amount of media and story coverage tied to Calvert Emerging Markets can signal where market attention is concentrating at the moment. A disciplined read of coverage helps investors separate durable relevance from temporary noise.

Other Macroaxis Stories

Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.