DAX Price (Germany) Market Value
| GDAXIP Index | 7,104 27.11 0.38% |
| Symbol | DAX |
DAX Price '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 DAX Price's index 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 DAX Price.
| 03/26/2024 |
| 04/25/2024 |
If you would invest 0.00 in DAX Price on March 26, 2024 and sell it all today you would earn a total of 0.00 from holding DAX Price or generate 0.0% return on investment in DAX Price over 30 days.
DAX Price 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 DAX Price's index 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 DAX Price upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6477 | |||
| Information Ratio | 0.0433 | |||
| Maximum Drawdown | 3.11 | |||
| Value At Risk | (1.09) | |||
| Potential Upside | 1.23 |
DAX Price Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for DAX Price's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as DAX Price's standard deviation. In reality, there are many statistical measures that can use DAX Price historical prices to predict the future DAX Price's volatility.| Risk Adjusted Performance | 0.1219 | |||
| Total Risk Alpha | 0.0267 | |||
| Sortino Ratio | 0.0419 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of DAX Price'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 Price. Your research has to be compared to or analyzed against DAX Price's peers to derive any actionable benefits. When done correctly, DAX Price'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 Price.
DAX Price Backtested Returns
DAX Price secures Sharpe Ratio (or Efficiency) of 0.15, which denotes the index had a 0.15% return per unit of volatility over the last 3 months. We have found twenty-six technical indicators for DAX Price, which you can use to evaluate the volatility of the entity. The entity shows a Beta (market volatility) of 0.0, which means not very significant fluctuations relative to the market. the returns on MARKET and DAX Price are completely uncorrelated.
Auto-correlation | -0.1 |
Very weak reverse predictability
DAX Price has very weak reverse predictability. Overlapping area represents the amount of predictability between DAX Price time series from 26th of March 2024 to 10th of April 2024 and 10th of April 2024 to 25th of April 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 DAX Price price movement. The serial correlation of -0.1 indicates that less than 10.0% of current DAX Price price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.1 | |
| Spearman Rank Test | 0.21 | |
| Residual Average | 0.0 | |
| Price Variance | 3115.59 |
DAX Price lagged returns against current returns
Autocorrelation, which is DAX Price index'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 DAX Price's index expected returns. We can calculate the autocorrelation of DAX Price returns to help us make a trade decision. For example, suppose you find that DAX Price has exhibited high autocorrelation historically, and you observe that the index 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 |
DAX Price 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 DAX Price index is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if DAX Price index is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in DAX Price index over time.
Current vs Lagged Prices |
| Timeline |
DAX Price Lagged Returns
When evaluating DAX Price's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of DAX Price index have on its future price. DAX Price 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, DAX Price autocorrelation shows the relationship between DAX Price index current value and its past values and can show if there is a momentum factor associated with investing in DAX Price.
Regressed Prices |
| Timeline |
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 Price 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 Price's short interest history, or implied volatility extrapolated from DAX Price options trading.
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DAX Price technical index analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, index market cycles, or different charting patterns.