Empiric 2500 Mutual Fund Forecast - Simple Moving Average
| EMCAX Fund | USD 69.00 0.41 0.59% |
The Simple Moving Average forecasted value of Empiric 2500 Fund on the next trading day is expected to be 69.00 with a mean absolute deviation of 0.58 and the sum of the absolute errors of 34.84. Empiric Mutual Fund Forecast is based on your current time horizon.
Empiric |
Empiric 2500 Simple Moving Average Price Forecast For the 15th of December 2024
Given 90 days horizon, the Simple Moving Average forecasted value of Empiric 2500 Fund on the next trading day is expected to be 69.00 with a mean absolute deviation of 0.58, mean absolute percentage error of 0.63, and the sum of the absolute errors of 34.84.Please note that although there have been many attempts to predict Empiric Mutual Fund prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Empiric 2500's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Empiric 2500 Mutual Fund Forecast Pattern
| Backtest Empiric 2500 | Empiric 2500 Price Prediction | Buy or Sell Advice |
Empiric 2500 Forecasted Value
In the context of forecasting Empiric 2500's Mutual Fund value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Empiric 2500's downside and upside margins for the forecasting period are 68.05 and 69.95, respectively. We have considered Empiric 2500's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of Empiric 2500 mutual fund data series using in forecasting. Note that when a statistical model is used to represent Empiric 2500 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 | 115.8183 |
| Bias | Arithmetic mean of the errors | -0.1095 |
| MAD | Mean absolute deviation | 0.5807 |
| MAPE | Mean absolute percentage error | 0.0086 |
| SAE | Sum of the absolute errors | 34.84 |
Predictive Modules for Empiric 2500
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Empiric 2500. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Other Forecasting Options for Empiric 2500
For every potential investor in Empiric, whether a beginner or expert, Empiric 2500's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Empiric Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Empiric. Basic forecasting techniques help filter out the noise by identifying Empiric 2500's price trends.Empiric 2500 Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Empiric 2500 mutual fund to make a market-neutral strategy. Peer analysis of Empiric 2500 could also be used in its relative valuation, which is a method of valuing Empiric 2500 by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Empiric 2500 Technical and Predictive Analytics
The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Empiric 2500's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Empiric 2500's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Empiric 2500 Market Strength Events
Market strength indicators help investors to evaluate how Empiric 2500 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 Empiric 2500 shares will generate the highest return on investment. By undertsting and applying Empiric 2500 mutual fund market strength indicators, traders can identify Empiric 2500 Fund entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 69.0 | |||
| Day Typical Price | 69.0 | |||
| Price Action Indicator | (0.20) | |||
| Period Momentum Indicator | (0.41) |
Empiric 2500 Risk Indicators
The analysis of Empiric 2500'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 Empiric 2500's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting empiric mutual fund prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 0.7054 | |||
| Semi Deviation | 0.5393 | |||
| Standard Deviation | 0.9452 | |||
| Variance | 0.8934 | |||
| Downside Variance | 0.5445 | |||
| Semi Variance | 0.2909 | |||
| Expected Short fall | (0.80) |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Other Information on Investing in Empiric Mutual Fund
Empiric 2500 financial ratios help investors to determine whether Empiric Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Empiric with respect to the benefits of owning Empiric 2500 security.
| Commodity Channel Use Commodity Channel Index to analyze current equity momentum | |
| ETFs Find actively traded Exchange Traded Funds (ETF) from around the world | |
| Competition Analyzer Analyze and compare many basic indicators for a group of related or unrelated entities | |
| Portfolio Suggestion Get suggestions outside of your existing asset allocation including your own model portfolios |