LOOMIS SAYLES Mutual Fund Forward View - Double Exponential Smoothing

LSGRX Fund  USD 30.71  0.04  0.13%   
The reference data on this page reflects Double Exponential Smoothing output applied to Loomis Sayles Growth's historical daily closing prices. Forecast values and accuracy statistics are presented for informational purposes.
The Double Exponential Smoothing forecasted value of Loomis Sayles Growth on the next trading day is expected to be 30.67 with a mean absolute deviation of 0.26 and the sum of the absolute errors of 15.40.When Loomis Sayles Growth 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 Loomis Sayles Growth trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent LOOMIS SAYLES observations are given relatively more weight in forecasting than the older observations. The forecast reference data presented here for Loomis Sayles Growth reflects Double Exponential Smoothing model output and is intended as reference material for analytical use.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for LOOMIS SAYLES works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 19th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Loomis Sayles Growth on the next trading day is expected to be 30.67 with a mean absolute deviation of 0.26 , mean absolute percentage error of 0.11 , and the sum of the absolute errors of 15.40 .
Please note that although there have been many attempts to predict LOOMIS 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 LOOMIS SAYLES'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 LOOMIS SAYLES's predictive range by looking for statistically meaningful downside and upside boundaries. The current forecast range spans downside near 29.73 and upside near 31.61.
Market Value
30.71
30.67
Expected Value
31.61
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of LOOMIS SAYLES mutual fund data series using in forecasting. Note that when a statistical model is used to represent LOOMIS SAYLES 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 -0.0474
MADMean absolute deviation0.2567
MAPEMean absolute percentage error0.008
SAESum of the absolute errors15.4046
When Loomis Sayles Growth 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 Loomis Sayles Growth trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent LOOMIS SAYLES observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for LOOMIS SAYLES

Understanding LOOMIS SAYLES's price movement is a prerequisite for any investor considering LOOMIS as a position. LOOMIS Mutual Fund price charts are frequently cluttered with noise that can interfere with accurate interpretation.

LOOMIS SAYLES Related Equities

The following equities are related to LOOMIS SAYLES within the Large Growth space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing LOOMIS SAYLES 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

LOOMIS SAYLES Market Strength Events

For traders and investors in Loomis Sayles Growth, market strength indicators offer a quantitative framework for evaluating the mutual fund's responsiveness to market conditions. These tools help identify when trading LOOMIS SAYLES shares is most likely to generate favorable returns.

LOOMIS SAYLES Risk Indicators

Analyzing LOOMIS SAYLES's risk indicators provides a critical input for price forecasting and investment risk management. By quantifying the risk in LOOMIS SAYLES's investment, investors can make more informed decisions about their exposure and hedging strategies.
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 LOOMIS SAYLES

Story coverage around Loomis Sayles Growth often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

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.