Health Sciences Gr Stock Market Value

Symbol

Health

In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Health Sciences' pink sheet what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Health Sciences.

Health Sciences Upside/Downside Indicators

Health Sciences Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Health Sciences' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Health Sciences' standard deviation. In reality, there are many statistical measures that can use Health Sciences historical prices to predict the future Health Sciences' volatility.

Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Health Sciences' 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.

Autocorrelation, which is Health Sciences pink sheet's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Health Sciences' pink sheet expected returns. We can calculate the autocorrelation of Health Sciences returns to help us make a trade decision. For example, suppose you find that Health Sciences has exhibited high autocorrelation historically, and you observe that the pink sheet is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.

Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Health Sciences pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Health Sciences pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Health Sciences pink sheet over time.

When evaluating Health Sciences' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Health Sciences pink sheet have on its future price. Health Sciences autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Health Sciences autocorrelation shows the relationship between Health Sciences pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Health Sciences Gr.

Health Sciences financial ratios help investors to determine whether Health Pink Sheet is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Health with respect to the benefits of owning Health Sciences security.