DAX Index (Germany) Probability of Future Index Price Finishing Under 18,717
| GDAXI Index | 19,255 177.43 0.93% |
DAX Index Target Price Odds to finish below 18,717
The tendency of DAX Index 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 below current price in 90 days |
| 19,255 | 90 days | 19,255 | about 78.36 |
Based on a normal probability distribution, the odds of DAX Index to move below current price in 90 days from now is about 78.36 (This DAX Index probability density function shows the probability of DAX Index to fall within a particular range of prices over 90 days) .
DAX Index Price Density |
| Price |
Predictive Modules for DAX Index
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as DAX Index. Regardless of method or technology, however, to accurately forecast the index market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the index 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 DAX Index's 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.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as DAX Index. Your research has to be compared to or analyzed against DAX Index's peers to derive any actionable benefits. When done correctly, DAX Index's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in DAX Index. DAX Index Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. DAX Index is not an exception. The market had few large corrections towards the DAX Index'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 DAX Index, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of DAX Index within the framework of very fundamental risk indicators.DAX Index Technical Analysis
DAX Index's future price can be derived by breaking down and analyzing its technical indicators over time. DAX Index technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of DAX Index. In general, you should focus on analyzing DAX Index price patterns and their correlations with different microeconomic environments and drivers.
DAX Index Predictive Forecast Models
DAX Index's time-series forecasting models is one of many DAX Index's index 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 DAX Index'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 index 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 DAX Index 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, DAX Index's short interest history, or implied volatility extrapolated from DAX Index options trading.