CALVERT EQUITY Mutual Fund Forward View - Triple Exponential Smoothing

CSECX Fund  USD 17.34  -0.33  -1.87%   
The Triple Exponential Smoothing forecast reference data for Calvert Equity Portfolio is based on the equity's recent trading history. This page summarizes the model output and key accuracy metrics for reference.
The Triple Exponential Smoothing forecasted value of Calvert Equity Portfolio on the next trading day is expected to be 17.27 with a mean absolute deviation of 0.14 and the sum of the absolute errors of 8.25.As with simple exponential smoothing, in triple exponential smoothing models past CALVERT EQUITY 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 Calvert Equity Portfolio observations. All Triple Exponential Smoothing forecast figures shown for Calvert Equity Portfolio are reference data reflecting model output based on available historical prices.
Triple exponential smoothing for CALVERT EQUITY - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When CALVERT EQUITY prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in CALVERT EQUITY price movement. However, neither of these exponential smoothing models address any seasonality of Calvert Equity Portfolio.

Triple Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Calvert Equity Portfolio on the next trading day is expected to be 17.27 with a mean absolute deviation of 0.14 , mean absolute percentage error of 0.03 , and the sum of the absolute errors of 8.25 .
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 EQUITY'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 EQUITY's predictive range by looking for statistically meaningful downside and upside boundaries. The current forecast range spans downside near 16.40 and upside near 18.14.
Market Value
17.34
17.27
Expected Value
18.14
Upside

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 CALVERT EQUITY mutual fund data series using in forecasting. Note that when a statistical model is used to represent CALVERT 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.0273
MADMean absolute deviation0.1398
MAPEMean absolute percentage error0.0076
SAESum of the absolute errors8.2497
As with simple exponential smoothing, in triple exponential smoothing models past CALVERT EQUITY 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 Calvert Equity Portfolio observations.

Other Forecasting Options for CALVERT EQUITY

Whether a novice or experienced investor, anyone considering CALVERT needs to understand the dynamics of CALVERT EQUITY's price movement. Price charts for CALVERT Mutual Fund contain a significant amount of noise that can distort investment decisions.

CALVERT EQUITY Related Equities

The following equities are related to CALVERT EQUITY within the Large Growth space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing CALVERT EQUITY 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 EQUITY Market Strength Events

Analyzing market strength indicators for CALVERT EQUITY enables investors to understand how the mutual fund performs relative to overall market momentum. These indicators are valuable tools for identifying when to enter or exit positions in Calvert Equity Portfolio.

CALVERT EQUITY Risk Indicators

Identifying and analyzing CALVERT EQUITY's key risk indicators is a foundational step in projecting how its price may evolve. This process quantifies the risk associated with CALVERT EQUITY's and decide how to manage 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 EQUITY

Coverage intensity for Calvert Equity Portfolio matters because narrative visibility can influence sentiment, participation, and volatility around the name. The practical risk is that faster visibility can increase both interest and skepticism at the same time.

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.