MFS Emerging Triple Exponential Smoothing

EMLMX -- USA Fund  

USD 6.86  0.01  0.15%

Investors can use this prediction interface to forecast MFS Emerging historic prices and determine the direction of MFS Emerging Markets Debt Local future trends based on various well-known forecasting models. However looking at historical price movement exclusively is usually misleading. Macroaxis recommends to always use this module together with analysis of MFS Emerging historical fundamentals such as revenue growth or operating cash flow patterns. Additionally see Historical Fundamental Analysis of MFS Emerging to cross-verify your projections.
Horizon     30 Days    Login   to change
Triple exponential smoothing for MFS Emerging - 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 MFS Emerging 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 MFS Emerging price movement. However, neither of these exponential smoothing models address any seasonality of MFS Emerging Markets.
Given 30 days horizon, the value of MFS Emerging Markets Debt Local on the next trading day is expected to be 6.845113

MFS Emerging Markets Prediction Pattern

Backtest MFS Emerging | MFS Emerging Price Prediction | Buy or Sell Advice 

MFS Emerging Forecasted Value

November 14, 2019
Market Value
Expected Value

Model Predictive Factors

AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors -8.0E-4
MADMean absolute deviation0.022
MAPEMean absolute percentage error0.0032
SAESum of the absolute errors1.2997
As with simple exponential smoothing, in triple exponential smoothing models past MFS Emerging 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 MFS Emerging Markets Debt Local observations.

Volatility Measures

MFS Emerging Risk Indicators