Digital Health Stock Forecast - Polynomial Regression
| DHACDelisted Stock | USD 12.11 0.39 3.12% |
The Polynomial Regression forecasted value of Digital Health Acquisition on the next trading day is expected to be 11.98 with a mean absolute deviation of 1.00 and the sum of the absolute errors of 61.05. Digital Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Digital Health stock prices and determine the direction of Digital Health Acquisition's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Digital Health's historical fundamentals, such as revenue growth or operating cash flow patterns.
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Digital Health Polynomial Regression Price Forecast For the 28th of November
Given 90 days horizon, the Polynomial Regression forecasted value of Digital Health Acquisition on the next trading day is expected to be 11.98 with a mean absolute deviation of 1.00, mean absolute percentage error of 1.98, and the sum of the absolute errors of 61.05.Please note that although there have been many attempts to predict Digital 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 Digital Health's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Digital Health Stock Forecast Pattern
| Backtest Digital Health | Digital Health Price Prediction | Buy or Sell Advice |
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 Digital Health stock data series using in forecasting. Note that when a statistical model is used to represent Digital Health 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 | 118.7956 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.0009 |
| MAPE | Mean absolute percentage error | 0.0732 |
| SAE | Sum of the absolute errors | 61.0525 |
Predictive Modules for Digital Health
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Digital Health Acqui. 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.View Digital Health Related Equities
| Risk & Return | Correlation |
Digital Health Market Strength Events
Market strength indicators help investors to evaluate how Digital Health stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Digital Health shares will generate the highest return on investment. By undertsting and applying Digital Health stock market strength indicators, traders can identify Digital Health Acquisition entry and exit signals to maximize returns.
Digital Health Risk Indicators
The analysis of Digital Health'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 Digital Health's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting digital 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 | 3.71 | |||
| Semi Deviation | 4.64 | |||
| Standard Deviation | 5.98 | |||
| Variance | 35.79 | |||
| Downside Variance | 35.01 | |||
| Semi Variance | 21.54 | |||
| Expected Short fall | (6.36) |
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.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 signals in nation. You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
Other Consideration for investing in Digital Stock
If you are still planning to invest in Digital Health Acqui 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 Digital Health's history and understand the potential risks before investing.
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