Fathom Digital Stock Forecast - Polynomial Regression

FATHDelisted Stock  USD 0.46  0.05  12.20%   
The Polynomial Regression forecasted value of Fathom Digital Manufacturing on the next trading day is expected to be 0.47 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.44. Fathom Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Fathom Digital's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Fathom Digital polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Fathom Digital Manufacturing as well as the accuracy indicators are determined from the period prices.

Fathom Digital Polynomial Regression Price Forecast For the 1st of February

Given 90 days horizon, the Polynomial Regression forecasted value of Fathom Digital Manufacturing on the next trading day is expected to be 0.47 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0009, and the sum of the absolute errors of 1.44.
Please note that although there have been many attempts to predict Fathom 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 Fathom Digital's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fathom Digital Stock Forecast Pattern

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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 Fathom Digital stock data series using in forecasting. Note that when a statistical model is used to represent Fathom Digital 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 Criteria111.1486
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0237
MAPEMean absolute percentage error0.0573
SAESum of the absolute errors1.4429
A single variable polynomial regression model attempts to put a curve through the Fathom Digital 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 Fathom Digital

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fathom Digital Manuf. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Fathom Digital'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
0.460.460.46
Details
Intrinsic
Valuation
LowRealHigh
0.370.370.51
Details

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

Fathom Digital Market Strength Events

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

Currently Active Assets on Macroaxis

Check out Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as various price indices.
You can also try the Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.

Other Consideration for investing in Fathom Stock

If you are still planning to invest in Fathom Digital Manuf check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Fathom Digital's history and understand the potential risks before investing.
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