Graybug Vision Stock Forecast - 8 Period Moving Average
| GRAYDelisted Stock | USD 6.33 1.06 20.11% |
The 8 Period Moving Average forecasted value of Graybug Vision on the next trading day is expected to be 4.92 with a mean absolute deviation of 0.48 and the sum of the absolute errors of 25.64. Graybug Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Graybug Vision stock prices and determine the direction of Graybug Vision's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Graybug Vision's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as various price indices. Graybug |
Most investors in Graybug Vision cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Graybug Vision's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Graybug Vision's price structures and extracts relationships that further increase the generated results' accuracy.
An 8-period moving average forecast model for Graybug Vision is based on an artificially constructed time series of Graybug Vision daily prices in which the value for a trading day is replaced by the mean of that value and the values for 8 of preceding and succeeding time periods. This model is best suited for price series data that changes over time. Graybug Vision 8 Period Moving Average Price Forecast For the 19th of April
Given 90 days horizon, the 8 Period Moving Average forecasted value of Graybug Vision on the next trading day is expected to be 4.92 with a mean absolute deviation of 0.48, mean absolute percentage error of 2.07, and the sum of the absolute errors of 25.64.Please note that although there have been many attempts to predict Graybug 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 Graybug Vision's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Graybug Vision Stock Forecast Pattern
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Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 8 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Graybug Vision stock data series using in forecasting. Note that when a statistical model is used to represent Graybug Vision 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 | 104.1364 |
| Bias | Arithmetic mean of the errors | -0.4475 |
| MAD | Mean absolute deviation | 0.4837 |
| MAPE | Mean absolute percentage error | 0.1252 |
| SAE | Sum of the absolute errors | 25.6362 |
Predictive Modules for Graybug Vision
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Graybug Vision. 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 Graybug Vision'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.
Graybug Vision 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 Graybug Vision stock to make a market-neutral strategy. Peer analysis of Graybug Vision could also be used in its relative valuation, which is a method of valuing Graybug Vision by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Graybug Vision Market Strength Events
Market strength indicators help investors to evaluate how Graybug Vision stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Graybug Vision shares will generate the highest return on investment. By undertsting and applying Graybug Vision stock market strength indicators, traders can identify Graybug Vision entry and exit signals to maximize returns.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Graybug Vision in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Graybug Vision's short interest history, or implied volatility extrapolated from Graybug Vision options trading.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectCheck out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as various price indices. Note that the Graybug Vision information on this page should be used as a complementary analysis to other Graybug Vision's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Commodity Directory module to find actively traded commodities issued by global exchanges.
Other Consideration for investing in Graybug Stock
If you are still planning to invest in Graybug Vision 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 Graybug Vision's history and understand the potential risks before investing.
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