DAX Index's market value is the price at which a share of DAX Index trades on a public exchange. It measures the collective expectations of DAX Index investors about its performance. DAX Index is listed for 19626.45 as of the 30th of November 2024. This is a 1.03% up since the beginning of the trading day. The index's open price was 19425.73. With this module, you can estimate the performance of a buy and hold strategy of DAX Index and determine expected loss or profit from investing in DAX Index over a given investment horizon. Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any index could be closely tied with the direction of predictive economic indicators such as signals in gross domestic product.
Symbol
DAX
DAX Index '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 Index'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 Index.
0.00
06/03/2024
No Change 0.00
0.0
In 5 months and 30 days
11/30/2024
0.00
If you would invest 0.00 in DAX Index on June 3, 2024 and sell it all today you would earn a total of 0.00 from holding DAX Index or generate 0.0% return on investment in DAX Index over 180 days.
DAX Index 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 Index'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 Index upside and downside potential and time the market with a certain degree of confidence.
Today, many novice investors tend to focus exclusively on investment returns with little concern for DAX Index's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as DAX Index's standard deviation. In reality, there are many statistical measures that can use DAX Index historical prices to predict the future DAX Index's volatility.
DAX Index secures Sharpe Ratio (or Efficiency) of 0.0704, which denotes the index had a 0.0704% return per unit of volatility over the last 3 months. We have found twenty-six technical indicators for DAX Index, 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 Index are completely uncorrelated.
Auto-correlation
0.03
Virtually no predictability
DAX Index has virtually no predictability. Overlapping area represents the amount of predictability between DAX Index time series from 3rd of June 2024 to 1st of September 2024 and 1st of September 2024 to 30th of November 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 Index price movement. The serial correlation of 0.03 indicates that only 3.0% of current DAX Index price fluctuation can be explain by its past prices.
Correlation Coefficient
0.03
Spearman Rank Test
-0.02
Residual Average
0.0
Price Variance
114.5 K
DAX Index lagged returns against current returns
Autocorrelation, which is DAX Index 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 Index's index expected returns. We can calculate the autocorrelation of DAX Index returns to help us make a trade decision. For example, suppose you find that DAX Index 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 Index 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 Index index is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if DAX Index index is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in DAX Index index over time.
Current vs Lagged Prices
Timeline
DAX Index Lagged Returns
When evaluating DAX Index's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of DAX Index index have on its future price. DAX Index 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 Index autocorrelation shows the relationship between DAX Index index current value and its past values and can show if there is a momentum factor associated with investing in DAX Index.
Regressed Prices
Timeline
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.