GMO Emerging Mutual Fund Forward View - Triple Exponential Smoothing
| GMAUX Fund | USD 14.86 -0.45 -2.94% |
This page documents Triple Exponential Smoothing forecast output for Gmo Emerging Markets as reference data. The model is applied to historical closing prices and the resulting projection and error statistics are shown below. Key metrics including projected price and mean absolute deviation are summarized below. The reference data on this page covers both forecast levels and error statistics.
The Triple Exponential Smoothing forecasted value of Gmo Emerging Markets on the next trading day is expected to be 14.79 with a mean absolute deviation of 0.15 and the sum of the absolute errors of 8.66.As with simple exponential smoothing, in triple exponential smoothing models past GMO 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 Gmo Emerging Markets observations. GMO Emerging's Triple Exponential Smoothing reference values are drawn from available trading data and are presented for informational reference only. Triple Exponential Smoothing Price Forecast For the 23rd of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Gmo Emerging Markets on the next trading day is expected to be 14.79 with a mean absolute deviation of 0.15 , mean absolute percentage error of 0.04 , and the sum of the absolute errors of 8.66 .Please note that although there have been many attempts to predict GMO 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 GMO Emerging's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest GMO Emerging | GMO Emerging Price Prediction | Research Analysis |
Forecasted Value
Forecasting Gmo Emerging Markets for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. At the moment, the model places downside around 13.38 and upside around 16.21 for the forecasting period.
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 GMO Emerging mutual fund data series using in forecasting. Note that when a statistical model is used to represent GMO 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.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | 0.0358 |
| MAD | Mean absolute deviation | 0.1467 |
| MAPE | Mean absolute percentage error | 0.0094 |
| SAE | Sum of the absolute errors | 8.6572 |
Other Forecasting Options for GMO Emerging
MACD analysis of GMO tracks the relationship between two exponential moving averages of GMO Emerging's price. Many GMO Emerging's traders use Fibonacci levels to set entry and exit targets based on prior price swings. Average True Range measures the typical daily price swing for GMO, accounting for gaps. The frequency and magnitude of gaps reveal how much new information is being priced into GMO outside regular hours.GMO Emerging Related Equities
Checking GMO Emerging against related firms within the Diversified Emerging Mkts space helps investors see where the stock stands among peers. Growth rate gaps between GMO Emerging and its peers often explain pricing differences in the market. Finding which peers are closest to GMO Emerging in business model helps sharpen the comparison.
| Risk & Return | Correlation |
GMO Emerging Market Strength Events
Market strength indicators for GMO Emerging assess how the mutual fund responds to changes in investor sentiment. These signals support informed decisions about when to enter or exit Gmo Emerging Markets positions. Market strength signals help investors time Gmo Emerging Markets positions with greater precision and confidence. Use these tools to enhance your market timing discipline when trading GMO Emerging mutual fund.
| Rate Of Daily Change | 0.97 | |||
| Day Median Price | 14.86 | |||
| Day Typical Price | 14.86 | |||
| Price Action Indicator | -0.23 | |||
| Period Momentum Indicator | -0.45 | |||
| Relative Strength Index | 44.56 |
GMO Emerging Risk Indicators
Risk indicator analysis for GMO Emerging is a critical component of accurate price forecasting. Identifying and quantifying the risks associated with GMO Emerging's allows investors to make better-informed decisions. Understanding GMO Emerging's risk indicators is a fundamental step in managing investment exposure responsibly. Understanding the risk embedded in GMO Emerging's allows investors to decide whether to accept, reduce, or hedge exposure.
| Mean Deviation | 0.9763 | |||
| Semi Deviation | 1.41 | |||
| Standard Deviation | 1.42 | |||
| Variance | 2.01 | |||
| Downside Variance | 3.46 | |||
| Semi Variance | 2.0 | |||
| Expected Short fall | -0.96 |
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 GMO Emerging
A coverage review of Gmo Emerging Markets shows when the security is attracting above-average attention from contributors and market observers. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.