Salient Adaptive Mutual Fund Forecast - Polynomial Regression

ACSIX Fund  USD 11.50  0.01  0.09%   
The Polynomial Regression forecasted value of Salient Adaptive Equity on the next trading day is expected to be 11.57 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.42. Salient Mutual Fund Forecast is based on your current time horizon.
  
Salient Adaptive polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Salient Adaptive Equity as well as the accuracy indicators are determined from the period prices.

Salient Adaptive Polynomial Regression Price Forecast For the 12th of December 2024

Given 90 days horizon, the Polynomial Regression forecasted value of Salient Adaptive Equity on the next trading day is expected to be 11.57 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0009, and the sum of the absolute errors of 1.42.
Please note that although there have been many attempts to predict Salient 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 Salient Adaptive's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Salient Adaptive Mutual Fund Forecast Pattern

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Salient Adaptive Forecasted Value

In the context of forecasting Salient Adaptive'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. Salient Adaptive's downside and upside margins for the forecasting period are 11.38 and 11.75, respectively. We have considered Salient Adaptive'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
11.50
11.57
Expected Value
11.75
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Salient Adaptive mutual fund data series using in forecasting. Note that when a statistical model is used to represent Salient Adaptive 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 Criteria111.0816
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0234
MAPEMean absolute percentage error0.0021
SAESum of the absolute errors1.4247
A single variable polynomial regression model attempts to put a curve through the Salient Adaptive historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Salient Adaptive

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Salient Adaptive Equity. 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.
Hype
Prediction
LowEstimatedHigh
11.3111.5011.69
Details
Intrinsic
Valuation
LowRealHigh
10.3510.5412.65
Details
Bollinger
Band Projection (param)
LowMiddleHigh
11.3711.4611.55
Details

Other Forecasting Options for Salient Adaptive

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

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

Salient Adaptive Equity 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 Salient Adaptive'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 Salient Adaptive's current price.

Salient Adaptive Market Strength Events

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

Salient Adaptive Risk Indicators

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

Salient Adaptive financial ratios help investors to determine whether Salient 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 Salient with respect to the benefits of owning Salient Adaptive security.
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