ASHMORE EMERGING Mutual Fund Forward View - Simple Regression

EMQAX Fund  USD 10.11  0.18  1.81%   
This reference page presents Simple Regression forecast data for Ashmore Emerging Markets. The model output shown here is derived from ASHMORE EMERGING's historical price series and is provided for informational purposes.
The Simple Regression forecasted value of Ashmore Emerging Markets on the next trading day is expected to be 10.70 with a mean absolute deviation of 0.31 and the sum of the absolute errors of 19.15.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 Ashmore Emerging Markets 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 forecast data for Ashmore Emerging Markets is sourced from the most recent available trading data and is intended solely as reference information.
Simple Regression model is a single variable regression model that attempts to put a straight line through ASHMORE EMERGING price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Simple Regression Price Forecast For the 18th of March 2026

Given 90 days horizon, the Simple Regression forecasted value of Ashmore Emerging Markets on the next trading day is expected to be 10.70 with a mean absolute deviation of 0.31 , mean absolute percentage error of 0.13 , and the sum of the absolute errors of 19.15 .
Please note that although there have been many attempts to predict ASHMORE 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 ASHMORE 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

Forecasting Ashmore Emerging Markets for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Market Value
10.11
10.70
Expected Value
11.94
Upside

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 ASHMORE EMERGING mutual fund data series using in forecasting. Note that when a statistical model is used to represent ASHMORE 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 Criteria116.051
BiasArithmetic mean of the errors None
MADMean absolute deviation0.3139
MAPEMean absolute percentage error0.0309
SAESum of the absolute errors19.1479
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 Ashmore Emerging Markets historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Other Forecasting Options for ASHMORE EMERGING

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

ASHMORE EMERGING Related Equities

The following equities are related to ASHMORE EMERGING within the Diversified Emerging Mkts space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing ASHMORE 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

ASHMORE EMERGING Market Strength Events

Market strength indicators help investors to evaluate how ASHMORE 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 ASHMORE EMERGING shares will generate the highest return on.

ASHMORE EMERGING Risk Indicators

The analysis of ASHMORE 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 ASHMORE 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 ASHMORE EMERGING

The amount of media and story coverage tied to Ashmore Emerging Markets can signal where market attention is concentrating at the moment. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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.