Goldman Sachs Etf Probability of Future Etf Price Finishing Over 50.30
| GMUB Etf | 50.30 0.04 0.08% |
Goldman |
Goldman Sachs Target Price Odds to finish over 50.30
The tendency of Goldman Etf price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for forecasting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
| Current Price | Horizon | Target Price | Odds to move above the current price in 90 days |
| 50.30 | 90 days | 50.30 | about 50.0 |
Based on a normal probability distribution, the odds of Goldman Sachs to move above the current price in 90 days from now is about 50.0 (This Goldman Sachs ETF probability density function shows the probability of Goldman Etf to fall within a particular range of prices over 90 days) .
Given the investment horizon of 90 days Goldman Sachs ETF has a beta of -0.0776. This usually indicates as returns on the benchmark increase, returns on holding Goldman Sachs are expected to decrease at a much lower rate. During a bear market, however, Goldman Sachs ETF is likely to outperform the market. Additionally Goldman Sachs ETF has an alpha of 0.0059, implying that it can generate a 0.005864 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Goldman Sachs Price Density |
| Price |
Predictive Modules for Goldman Sachs
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Goldman Sachs ETF. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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 Goldman Sachs' 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.
Goldman Sachs Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Goldman Sachs is not an exception. The market had few large corrections towards the Goldman Sachs' value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold Goldman Sachs ETF, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Goldman Sachs within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.01 | |
β | Beta against Dow Jones | -0.08 | |
σ | Overall volatility | 0.18 | |
Ir | Information ratio | -0.71 |
Goldman Sachs Technical Analysis
Goldman Sachs' future price can be derived by breaking down and analyzing its technical indicators over time. Goldman Etf technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Goldman Sachs ETF. In general, you should focus on analyzing Goldman Etf price patterns and their correlations with different microeconomic environments and drivers.
Goldman Sachs Predictive Forecast Models
Goldman Sachs' time-series forecasting models is one of many Goldman Sachs' etf analysis techniques aimed to predict future share value based on previously observed values. Time-series forecasting models are widely used for non-stationary data. Non-stationary data are called the data whose statistical properties, e.g., the mean and standard deviation, are not constant over time, but instead, these metrics vary over time. This non-stationary Goldman Sachs' historical data is usually called time series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the etf market movement and maximize returns from investment trading.
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 Goldman Sachs 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, Goldman Sachs' short interest history, or implied volatility extrapolated from Goldman Sachs options trading.
Check out Goldman Sachs Backtesting, Portfolio Optimization, Goldman Sachs Correlation, Goldman Sachs Hype Analysis, Goldman Sachs Volatility, Goldman Sachs History as well as Goldman Sachs Performance. You can also try the Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
The market value of Goldman Sachs ETF is measured differently than its book value, which is the value of Goldman that is recorded on the company's balance sheet. Investors also form their own opinion of Goldman Sachs' value that differs from its market value or its book value, called intrinsic value, which is Goldman Sachs' 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 Goldman Sachs' market value can be influenced by many factors that don't directly affect Goldman Sachs' 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 Goldman Sachs' value and its price as these two are different measures arrived at by different means. Investors typically determine if Goldman Sachs is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Goldman Sachs' 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.