ETFS Ultra (Australia) Probability of Future Etf Price Finishing Under 8.46
| LNAS Etf | 10.55 0.07 0.67% |
ETFS |
ETFS Ultra Target Price Odds to finish below 8.46
The tendency of ETFS 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 drop to 8.46 or more in 90 days |
| 10.55 | 90 days | 8.46 | about 1.3 |
Based on a normal probability distribution, the odds of ETFS Ultra to drop to 8.46 or more in 90 days from now is about 1.3 (This ETFS Ultra Long probability density function shows the probability of ETFS Etf to fall within a particular range of prices over 90 days) . Probability of ETFS Ultra Long price to stay between 8.46 and its current price of 10.55 at the end of the 90-day period is about 85.01 .
Assuming the 90 days trading horizon the etf has the beta coefficient of 1.57 . This indicates as the benchmark fluctuates upward, the company is expected to outperform it on average. However, if the benchmark returns are projected to be negative, ETFS Ultra will likely underperform. Additionally ETFS Ultra Long has an alpha of 0.0131, implying that it can generate a 0.0131 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). ETFS Ultra Price Density |
| Price |
Predictive Modules for ETFS Ultra
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as ETFS Ultra Long. 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.ETFS Ultra Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. ETFS Ultra is not an exception. The market had few large corrections towards the ETFS Ultra's 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 ETFS Ultra Long, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of ETFS Ultra within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.01 | |
β | Beta against Dow Jones | 1.57 | |
σ | Overall volatility | 0.63 | |
Ir | Information ratio | 0.04 |
ETFS Ultra Technical Analysis
ETFS Ultra's future price can be derived by breaking down and analyzing its technical indicators over time. ETFS Etf technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of ETFS Ultra Long. In general, you should focus on analyzing ETFS Etf price patterns and their correlations with different microeconomic environments and drivers.
ETFS Ultra Predictive Forecast Models
ETFS Ultra's time-series forecasting models is one of many ETFS Ultra's 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 ETFS Ultra's 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 ETFS Ultra 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, ETFS Ultra's short interest history, or implied volatility extrapolated from ETFS Ultra options trading.
Other Information on Investing in ETFS Etf
ETFS Ultra financial ratios help investors to determine whether ETFS Etf 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 ETFS with respect to the benefits of owning ETFS Ultra security.