Green Shift's market value is the price at which a share of Green Shift trades on a public exchange. It measures the collective expectations of Green Shift Commodities investors about its performance. Green Shift is trading at 0.03 as of the 27th of November 2024. This is a 8.81% down since the beginning of the trading day. The stock's lowest day price was 0.03. With this module, you can estimate the performance of a buy and hold strategy of Green Shift Commodities and determine expected loss or profit from investing in Green Shift over a given investment horizon. Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any otc stock could be closely tied with the direction of predictive economic indicators such as signals in population.
Symbol
Green
Green Shift 'What if' Analysis
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 Green Shift's otc stock 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 Green Shift.
0.00
10/28/2024
No Change 0.00
0.0
In 31 days
11/27/2024
0.00
If you would invest 0.00 in Green Shift on October 28, 2024 and sell it all today you would earn a total of 0.00 from holding Green Shift Commodities or generate 0.0% return on investment in Green Shift over 30 days.
Green Shift Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Green Shift's otc stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Green Shift Commodities upside and downside potential and time the market with a certain degree of confidence.
Today, many novice investors tend to focus exclusively on investment returns with little concern for Green Shift's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Green Shift's standard deviation. In reality, there are many statistical measures that can use Green Shift historical prices to predict the future Green Shift's volatility.
Green Shift Commodities holds Efficiency (Sharpe) Ratio of 0.0261, which attests that the entity had a 0.0261% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Green Shift Commodities, which you can use to evaluate the volatility of the firm. Please utilize Green Shift's Market Risk Adjusted Performance of 0.2703, downside deviation of 14.37, and Risk Adjusted Performance of 0.0317 to validate if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Green Shift holds a performance score of 2. The company retains a Market Volatility (i.e., Beta) of 1.0, which attests to a somewhat significant risk relative to the market. Green Shift returns are very sensitive to returns on the market. As the market goes up or down, Green Shift is expected to follow. Please check Green Shift's information ratio, downside variance, day typical price, as well as the relationship between the treynor ratio and kurtosis , to make a quick decision on whether Green Shift's current trending patterns will revert.
Auto-correlation
0.05
Virtually no predictability
Green Shift Commodities has virtually no predictability. Overlapping area represents the amount of predictability between Green Shift time series from 28th of October 2024 to 12th of November 2024 and 12th of November 2024 to 27th of November 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Green Shift Commodities price movement. The serial correlation of 0.05 indicates that only as little as 5.0% of current Green Shift price fluctuation can be explain by its past prices.
Correlation Coefficient
0.05
Spearman Rank Test
-0.79
Residual Average
0.0
Price Variance
0.0
Green Shift Commodities lagged returns against current returns
Autocorrelation, which is Green Shift otc stock'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 Green Shift's otc stock expected returns. We can calculate the autocorrelation of Green Shift returns to help us make a trade decision. For example, suppose you find that Green Shift has exhibited high autocorrelation historically, and you observe that the otc stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values
Timeline
Green Shift regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Green Shift otc stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Green Shift otc stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Green Shift otc stock over time.
Current vs Lagged Prices
Timeline
Green Shift Lagged Returns
When evaluating Green Shift's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Green Shift otc stock have on its future price. Green Shift 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, Green Shift autocorrelation shows the relationship between Green Shift otc stock current value and its past values and can show if there is a momentum factor associated with investing in Green Shift Commodities.