ALM ES Fund Forecast - 20 Period Moving Average

0P0001NBQF   117.50  0.00  0.00%   
The 20 Period Moving Average forecasted value of ALM ES Actions on the next trading day is expected to be 125.70 with a mean absolute deviation of 2.92 and the sum of the absolute errors of 119.70. Investors can use prediction functions to forecast ALM ES's fund prices and determine the direction of ALM ES Actions's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading.
  
A commonly used 20-period moving average forecast model for ALM ES Actions is based on a synthetically constructed ALM ESdaily price series in which the value for a trading day is replaced by the mean of that value and the values for 20 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

ALM ES 20 Period Moving Average Price Forecast For the 19th of March

Given 90 days horizon, the 20 Period Moving Average forecasted value of ALM ES Actions on the next trading day is expected to be 125.70 with a mean absolute deviation of 2.92, mean absolute percentage error of 17.61, and the sum of the absolute errors of 119.70.
Please note that although there have been many attempts to predict ALM 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 ALM ES's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

ALM ES Fund Forecast Pattern

ALM ES Forecasted Value

In the context of forecasting ALM ES's 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. ALM ES's downside and upside margins for the forecasting period are 124.85 and 126.55, respectively. We have considered ALM ES'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.
Market Value
117.50
124.85
Downside
125.70
Expected Value
126.55
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of ALM ES fund data series using in forecasting. Note that when a statistical model is used to represent ALM ES 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 Criteria84.2212
BiasArithmetic mean of the errors 1.2016
MADMean absolute deviation2.9195
MAPEMean absolute percentage error0.0236
SAESum of the absolute errors119.698
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. ALM ES Actions 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for ALM ES

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as ALM ES Actions. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the 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 ALM ES

For every potential investor in ALM, whether a beginner or expert, ALM ES's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. ALM Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in ALM. Basic forecasting techniques help filter out the noise by identifying ALM ES's price trends.

ALM ES 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 ALM ES fund to make a market-neutral strategy. Peer analysis of ALM ES could also be used in its relative valuation, which is a method of valuing ALM ES by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

ALM ES Actions Technical and Predictive Analytics

The fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of ALM ES'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 ALM ES's current price.

ALM ES Market Strength Events

Market strength indicators help investors to evaluate how ALM ES fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading ALM ES shares will generate the highest return on investment. By undertsting and applying ALM ES fund market strength indicators, traders can identify ALM ES Actions entry and exit signals to maximize returns.

ALM ES Risk Indicators

The analysis of ALM ES'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 ALM ES's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting alm 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.
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.

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