Predictive Oncology Stock Forecast - Simple Regression
POAI Stock | USD 0.72 0.03 4.35% |
The Simple Regression forecasted value of Predictive Oncology on the next trading day is expected to be 0.65 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.31. Predictive Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Predictive Oncology's historical fundamentals, such as revenue growth or operating cash flow patterns.
Predictive |
Predictive Oncology Simple Regression Price Forecast For the 24th of November
Given 90 days horizon, the Simple Regression forecasted value of Predictive Oncology on the next trading day is expected to be 0.65 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.31.Please note that although there have been many attempts to predict Predictive 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 Predictive Oncology's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Predictive Oncology Stock Forecast Pattern
Backtest Predictive Oncology | Predictive Oncology Price Prediction | Buy or Sell Advice |
Predictive Oncology Forecasted Value
In the context of forecasting Predictive Oncology's 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. Predictive Oncology's downside and upside margins for the forecasting period are 0.01 and 6.35, respectively. We have considered Predictive Oncology'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.
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 Predictive Oncology stock data series using in forecasting. Note that when a statistical model is used to represent Predictive Oncology 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.AIC | Akaike Information Criteria | 113.2111 |
Bias | Arithmetic mean of the errors | None |
MAD | Mean absolute deviation | 0.0707 |
MAPE | Mean absolute percentage error | 0.0979 |
SAE | Sum of the absolute errors | 4.311 |
Predictive Modules for Predictive Oncology
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Predictive Oncology. 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.Other Forecasting Options for Predictive Oncology
For every potential investor in Predictive, whether a beginner or expert, Predictive Oncology's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Predictive Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Predictive. Basic forecasting techniques help filter out the noise by identifying Predictive Oncology's price trends.Predictive Oncology 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 Predictive Oncology stock to make a market-neutral strategy. Peer analysis of Predictive Oncology could also be used in its relative valuation, which is a method of valuing Predictive Oncology by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Predictive Oncology 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 Predictive Oncology'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 Predictive Oncology's current price.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
Predictive Oncology Market Strength Events
Market strength indicators help investors to evaluate how Predictive Oncology stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Predictive Oncology shares will generate the highest return on investment. By undertsting and applying Predictive Oncology stock market strength indicators, traders can identify Predictive Oncology entry and exit signals to maximize returns.
Predictive Oncology Risk Indicators
The analysis of Predictive Oncology'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 Predictive Oncology's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting predictive stock 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.
Mean Deviation | 4.01 | |||
Standard Deviation | 5.68 | |||
Variance | 32.22 |
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.
Currently Active Assets on Macroaxis
When determining whether Predictive Oncology offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Predictive Oncology's 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 Predictive Oncology Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Predictive Oncology Stock:Check out Historical Fundamental Analysis of Predictive Oncology to cross-verify your projections. For more detail on how to invest in Predictive Stock please use our How to Invest in Predictive Oncology 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 Equipment & Supplies 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 Predictive Oncology. If investors know Predictive 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 Predictive Oncology listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share (2.96) | Revenue Per Share 0.416 | Quarterly Revenue Growth (0.43) | Return On Assets (0.56) | Return On Equity (1.49) |
The market value of Predictive Oncology is measured differently than its book value, which is the value of Predictive that is recorded on the company's balance sheet. Investors also form their own opinion of Predictive Oncology's value that differs from its market value or its book value, called intrinsic value, which is Predictive Oncology's 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 Predictive Oncology's market value can be influenced by many factors that don't directly affect Predictive Oncology's 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 Predictive Oncology's value and its price as these two are different measures arrived at by different means. Investors typically determine if Predictive Oncology is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Predictive Oncology's 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.