Analytics Fund Forecast - Simple Regression

0P0000ZSMO   10.01  0.03  0.30%   
The Simple Regression forecasted value of Analytics Ci Balanced on the next trading day is expected to be 9.99 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.65. Investors can use prediction functions to forecast Analytics' fund prices and determine the direction of Analytics Ci Balanced's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through Analytics price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Analytics Simple Regression Price Forecast For the 12th of December 2024

Given 90 days horizon, the Simple Regression forecasted value of Analytics Ci Balanced on the next trading day is expected to be 9.99 with a mean absolute deviation of 0.04, mean absolute percentage error of 0, and the sum of the absolute errors of 2.65.
Please note that although there have been many attempts to predict Analytics 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 Analytics' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Analytics Fund Forecast Pattern

Analytics Forecasted Value

In the context of forecasting Analytics' 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. Analytics' downside and upside margins for the forecasting period are 9.64 and 10.34, respectively. We have considered Analytics' 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
10.01
9.99
Expected Value
10.34
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Analytics fund data series using in forecasting. Note that when a statistical model is used to represent Analytics 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 Criteria112.2083
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0435
MAPEMean absolute percentage error0.0044
SAESum of the absolute errors2.6544
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Analytics Ci Balanced historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for Analytics

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Analytics Ci Balanced. 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 Analytics

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

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

Analytics Ci Balanced 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 Analytics' 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 Analytics' current price.

Analytics Market Strength Events

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

Analytics Risk Indicators

The analysis of Analytics' 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 Analytics' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting analytics 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.

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.
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