Decision Diagnostics Stock Forecast - Polynomial Regression

DECN Stock  USD 0.0001  0.00  0.00%   
The Polynomial Regression forecasted value of Decision Diagnostics 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. Decision Stock Forecast is based on your current time horizon. Although Decision Diagnostics' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Decision Diagnostics' systematic risk associated with finding meaningful patterns of Decision Diagnostics fundamentals over time.
  
As of the 2nd of December 2024, Inventory Turnover is likely to drop to 10.07. In addition to that, Payables Turnover is likely to drop to 0.95. As of the 2nd of December 2024, Common Stock Shares Outstanding is likely to drop to about 284 M. In addition to that, Net Loss is likely to grow to about (25.4 M).
Decision Diagnostics polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Decision Diagnostics as well as the accuracy indicators are determined from the period prices.

Decision Diagnostics Polynomial Regression Price Forecast For the 3rd of December

Given 90 days horizon, the Polynomial Regression forecasted value of Decision Diagnostics 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 Decision 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 Decision Diagnostics' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Decision Diagnostics Stock Forecast Pattern

Backtest Decision DiagnosticsDecision Diagnostics Price PredictionBuy or Sell Advice 

Decision Diagnostics Forecasted Value

In the context of forecasting Decision Diagnostics' Stock 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. Decision Diagnostics' downside and upside margins for the forecasting period are 0.0001 and 0.0001, respectively. We have considered Decision Diagnostics' 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
0.0001
0.0001
Downside
0.0001
Expected Value
0.0001
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 Decision Diagnostics stock data series using in forecasting. Note that when a statistical model is used to represent Decision Diagnostics 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 Criteria34.379
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
A single variable polynomial regression model attempts to put a curve through the Decision Diagnostics 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 Decision Diagnostics

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Decision Diagnostics. 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 Decision Diagnostics' 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
0.000.00010.00
Details
Intrinsic
Valuation
LowRealHigh
0.000.0000840.00
Details
Bollinger
Band Projection (param)
LowMiddleHigh
0.00010.00010.0001
Details

Other Forecasting Options for Decision Diagnostics

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

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

Decision Diagnostics Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Decision Diagnostics' 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 Decision Diagnostics' current price.

Decision Diagnostics Market Strength Events

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

Pair Trading with Decision Diagnostics

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Decision Diagnostics position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Decision Diagnostics will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Decision Diagnostics could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Decision Diagnostics when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Decision Diagnostics - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Decision Diagnostics to buy it.
The correlation of Decision Diagnostics is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Decision Diagnostics moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Decision Diagnostics moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Decision Diagnostics can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
When determining whether Decision Diagnostics offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Decision Diagnostics' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Decision Diagnostics Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Decision Diagnostics Stock:
Check out Historical Fundamental Analysis of Decision Diagnostics to cross-verify your projections.
To learn how to invest in Decision Stock, please use our How to Invest in Decision Diagnostics guide.
You can also try the Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
Is Health Care Technology space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Decision Diagnostics. If investors know Decision will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Decision Diagnostics listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share
(0.02)
Revenue Per Share
0.006
Quarterly Revenue Growth
(0)
Return On Assets
(0.21)
Return On Equity
(81.61)
The market value of Decision Diagnostics is measured differently than its book value, which is the value of Decision that is recorded on the company's balance sheet. Investors also form their own opinion of Decision Diagnostics' value that differs from its market value or its book value, called intrinsic value, which is Decision Diagnostics' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Decision Diagnostics' market value can be influenced by many factors that don't directly affect Decision Diagnostics' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Decision Diagnostics' value and its price as these two are different measures arrived at by different means. Investors typically determine if Decision Diagnostics is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Decision Diagnostics' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.