Gold Futures Commodity Probability of Future Commodity Price Finishing Over 2,713
| GCUSD Commodity | 2,662 3.30 0.12% |
Gold |
Gold Futures Target Price Odds to finish over 2,713
The tendency of Gold Commodity 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 |
| 2,662 | 90 days | 2,662 | about 44.35 |
Based on a normal probability distribution, the odds of Gold Futures to move above the current price in 90 days from now is about 44.35 (This Gold Futures probability density function shows the probability of Gold Commodity to fall within a particular range of prices over 90 days) .
Assuming the 90 days horizon Gold Futures has a beta of -0.0627. This usually indicates as returns on the benchmark increase, returns on holding Gold Futures are expected to decrease at a much lower rate. During a bear market, however, Gold Futures is likely to outperform the market. Additionally Gold Futures has an alpha of 0.0612, implying that it can generate a 0.0612 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Gold Futures Price Density |
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Predictive Modules for Gold Futures
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Gold Futures. Regardless of method or technology, however, to accurately forecast the commodity market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the commodity 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 Gold Futures' 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.
Gold Futures Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Gold Futures is not an exception. The market had few large corrections towards the Gold Futures' 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 Gold Futures, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Gold Futures within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.06 | |
β | Beta against Dow Jones | -0.06 | |
σ | Overall volatility | 73.55 | |
Ir | Information ratio | -0.06 |
Gold Futures Technical Analysis
Gold Futures' future price can be derived by breaking down and analyzing its technical indicators over time. Gold Commodity technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Gold Futures. In general, you should focus on analyzing Gold Commodity price patterns and their correlations with different microeconomic environments and drivers.
Gold Futures Predictive Forecast Models
Gold Futures' time-series forecasting models is one of many Gold Futures' commodity 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 Gold Futures' 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 commodity 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 Gold Futures 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, Gold Futures' short interest history, or implied volatility extrapolated from Gold Futures options trading.