Managed Volatility Mutual Fund Forecast - Simple Regression

BRBPX Fund  USD 10.80  0.01  0.09%   
The Simple Regression forecasted value of Managed Volatility Fund on the next trading day is expected to be 10.78 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.68. Managed Mutual Fund Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through Managed Volatility 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.

Managed Volatility Simple Regression Price Forecast For the 6th of October

Given 90 days horizon, the Simple Regression forecasted value of Managed Volatility Fund on the next trading day is expected to be 10.78 with a mean absolute deviation of 0.04, mean absolute percentage error of 0.01, and the sum of the absolute errors of 2.68.
Please note that although there have been many attempts to predict Managed 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 Managed Volatility's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Managed Volatility Mutual Fund Forecast Pattern

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Managed Volatility Forecasted Value

In the context of forecasting Managed Volatility'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. Managed Volatility's downside and upside margins for the forecasting period are 10.39 and 11.16, respectively. We have considered Managed Volatility'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
10.80
10.78
Expected Value
11.16
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 Managed Volatility mutual fund data series using in forecasting. Note that when a statistical model is used to represent Managed Volatility 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 Criteria112.8256
BiasArithmetic mean of the errors None
MADMean absolute deviation0.044
MAPEMean absolute percentage error0.0041
SAESum of the absolute errors2.6816
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 Managed Volatility Fund 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 Managed Volatility

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Managed Volatility. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Managed Volatility's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
10.4110.8011.19
Details
Intrinsic
Valuation
LowRealHigh
10.3910.7811.17
Details

Other Forecasting Options for Managed Volatility

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

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

Managed Volatility 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 Managed Volatility'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 Managed Volatility's current price.

Managed Volatility Market Strength Events

Market strength indicators help investors to evaluate how Managed Volatility 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 Managed Volatility shares will generate the highest return on investment. By undertsting and applying Managed Volatility mutual fund market strength indicators, traders can identify Managed Volatility Fund entry and exit signals to maximize returns.

Managed Volatility Risk Indicators

The analysis of Managed Volatility'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 Managed Volatility's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting managed 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.
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 Managed Mutual Fund

Managed Volatility financial ratios help investors to determine whether Managed 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 Managed with respect to the benefits of owning Managed Volatility security.
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