CareMax Stock Forecast - Simple Regression

CMAX Stock  USD 0.0001  0.00  0.000003%   
The Simple Regression forecasted value of CareMax on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. CareMax Stock 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 CareMax 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.

CareMax Simple Regression Price Forecast For the 26th of July

Given 90 days horizon, the Simple Regression forecasted value of CareMax on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict CareMax Stock 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 CareMax's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

CareMax Stock Forecast Pattern

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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 CareMax stock data series using in forecasting. Note that when a statistical model is used to represent CareMax stock, 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 Criteria60.8687
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
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 CareMax 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 CareMax

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as CareMax. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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
0.000.00010.00
Details
Intrinsic
Valuation
LowRealHigh
0.000.0000840.00
Details
Bollinger
Band Projection (param)
LowMiddleHigh
0.00010.00010.0001
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as CareMax. Your research has to be compared to or analyzed against CareMax's peers to derive any actionable benefits. When done correctly, CareMax's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in CareMax.

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

CareMax Market Strength Events

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

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.

Additional Tools for CareMax Stock Analysis

When running CareMax's price analysis, check to measure CareMax's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy CareMax is operating at the current time. Most of CareMax's value examination focuses on studying past and present price action to predict the probability of CareMax's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move CareMax's price. Additionally, you may evaluate how the addition of CareMax to your portfolios can decrease your overall portfolio volatility.