Deutsche Boerse Ag Stock Market Value
| DBOEY Stock | USD 19.61 0.07 0.36% |
| Symbol | Deutsche |
Deutsche Boerse '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 Deutsche Boerse's pink sheet 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 Deutsche Boerse.
| 03/18/2024 |
| 05/17/2024 |
If you would invest 0.00 in Deutsche Boerse on March 18, 2024 and sell it all today you would earn a total of 0.00 from holding Deutsche Boerse AG or generate 0.0% return on investment in Deutsche Boerse over 60 days. Deutsche Boerse is related to or competes with Deutsche Brse, Morningstar, FactSet Research, Intercontinental, Nasdaq, and CME. Deutsche Brse AG operates as an exchange organization in Europe, the United States, and the Asia-Pacific More
Deutsche Boerse 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 Deutsche Boerse's pink sheet 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 Deutsche Boerse AG upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.3 | |||
| Information Ratio | (0.1) | |||
| Maximum Drawdown | 5.97 | |||
| Value At Risk | (2.17) | |||
| Potential Upside | 1.49 |
Deutsche Boerse Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Deutsche Boerse's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Deutsche Boerse's standard deviation. In reality, there are many statistical measures that can use Deutsche Boerse historical prices to predict the future Deutsche Boerse's volatility.| Risk Adjusted Performance | 0.0066 | |||
| Jensen Alpha | (0.05) | |||
| Total Risk Alpha | (0.18) | |||
| Sortino Ratio | (0.08) | |||
| Treynor Ratio | (0.01) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Deutsche Boerse'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.
Deutsche Boerse AG Backtested Returns
Deutsche Boerse AG secures Sharpe Ratio (or Efficiency) of -0.0259, which denotes the company had a -0.0259% return per unit of risk over the last 3 months. Deutsche Boerse AG exposes twenty-eight different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Deutsche Boerse's Coefficient Of Variation of 26425.87, downside deviation of 1.3, and Mean Deviation of 0.7189 to check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.41, which means possible diversification benefits within a given portfolio. As returns on the market increase, Deutsche Boerse's returns are expected to increase less than the market. However, during the bear market, the loss of holding Deutsche Boerse is expected to be smaller as well. Deutsche Boerse AG has an expected return of -0.0277%. Please make sure to confirm Deutsche Boerse AG potential upside, as well as the relationship between the accumulation distribution and period momentum indicator , to decide if Deutsche Boerse AG performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.29 |
Weak reverse predictability
Deutsche Boerse AG has weak reverse predictability. Overlapping area represents the amount of predictability between Deutsche Boerse time series from 18th of March 2024 to 17th of April 2024 and 17th of April 2024 to 17th of May 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 Deutsche Boerse AG price movement. The serial correlation of -0.29 indicates that nearly 29.0% of current Deutsche Boerse price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.29 | |
| Spearman Rank Test | 0.19 | |
| Residual Average | 0.0 | |
| Price Variance | 0.09 |
Deutsche Boerse AG lagged returns against current returns
Autocorrelation, which is Deutsche Boerse pink sheet'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 Deutsche Boerse's pink sheet expected returns. We can calculate the autocorrelation of Deutsche Boerse returns to help us make a trade decision. For example, suppose you find that Deutsche Boerse has exhibited high autocorrelation historically, and you observe that the pink sheet 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 |
Deutsche Boerse 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 Deutsche Boerse pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Deutsche Boerse pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Deutsche Boerse pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Deutsche Boerse Lagged Returns
When evaluating Deutsche Boerse's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Deutsche Boerse pink sheet have on its future price. Deutsche Boerse 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, Deutsche Boerse autocorrelation shows the relationship between Deutsche Boerse pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Deutsche Boerse AG.
Regressed Prices |
| Timeline |
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Check out Deutsche Boerse Correlation, Deutsche Boerse Volatility and Deutsche Boerse Alpha and Beta module to complement your research on Deutsche Boerse. Note that the Deutsche Boerse AG information on this page should be used as a complementary analysis to other Deutsche Boerse's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.
Complementary Tools for Deutsche Pink Sheet analysis
When running Deutsche Boerse's price analysis, check to measure Deutsche Boerse's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Deutsche Boerse is operating at the current time. Most of Deutsche Boerse's value examination focuses on studying past and present price action to predict the probability of Deutsche Boerse's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Deutsche Boerse's price. Additionally, you may evaluate how the addition of Deutsche Boerse to your portfolios can decrease your overall portfolio volatility.
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Deutsche Boerse technical pink sheet 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, pink sheet market cycles, or different charting patterns.