Data#3 (Germany) Market Value
| 20Y Stock | EUR 4.72 0.04 0.85% |
| Symbol | Data#3 |
Data#3 '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 Data#3's stock 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 Data#3.
| 05/27/2024 |
| 11/23/2024 |
If you would invest 0.00 in Data#3 on May 27, 2024 and sell it all today you would earn a total of 0.00 from holding Data3 Limited or generate 0.0% return on investment in Data#3 over 180 days. Data#3 is related to or competes with Accenture Plc, Cognizant Technology, Superior Plus, NMI Holdings, Origin Agritech, SIVERS SEMICONDUCTORS, and Talanx AG. Data3 Limited, together with its subsidiaries, provides information technology solutions and services in Australia and F... More
Data#3 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 Data#3's stock 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 Data3 Limited upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.19 | |||
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 11.26 | |||
| Value At Risk | (3.00) | |||
| Potential Upside | 3.18 |
Data#3 Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data#3's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data#3's standard deviation. In reality, there are many statistical measures that can use Data#3 historical prices to predict the future Data#3's volatility.| Risk Adjusted Performance | 0.0067 | |||
| Jensen Alpha | 0.0442 | |||
| Total Risk Alpha | (0.33) | |||
| Sortino Ratio | (0.06) | |||
| Treynor Ratio | 0.02 |
Data3 Limited Backtested Returns
At this point, Data#3 is slightly risky. Data3 Limited secures Sharpe Ratio (or Efficiency) of 0.0385, which denotes the company had a 0.0385% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Data3 Limited, which you can use to evaluate the volatility of the firm. Please confirm Data#3's Coefficient Of Variation of 164206.97, downside deviation of 2.19, and Mean Deviation of 1.56 to check if the risk estimate we provide is consistent with the expected return of 0.0762%. Data#3 has a performance score of 3 on a scale of 0 to 100. The firm shows a Beta (market volatility) of -0.44, which means possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Data#3 are expected to decrease at a much lower rate. During the bear market, Data#3 is likely to outperform the market. Data3 Limited right now shows a risk of 1.98%. Please confirm Data3 Limited total risk alpha, treynor ratio, and the relationship between the jensen alpha and sortino ratio , to decide if Data3 Limited will be following its price patterns.
Auto-correlation | -0.03 |
Very weak reverse predictability
Data3 Limited has very weak reverse predictability. Overlapping area represents the amount of predictability between Data#3 time series from 27th of May 2024 to 25th of August 2024 and 25th of August 2024 to 23rd 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 Data3 Limited price movement. The serial correlation of -0.03 indicates that only 3.0% of current Data#3 price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.03 | |
| Spearman Rank Test | 0.16 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Data3 Limited lagged returns against current returns
Autocorrelation, which is Data#3 stock'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 Data#3's stock expected returns. We can calculate the autocorrelation of Data#3 returns to help us make a trade decision. For example, suppose you find that Data#3 has exhibited high autocorrelation historically, and you observe that the stock 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 |
Data#3 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 Data#3 stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Data#3 stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Data#3 stock over time.
Current vs Lagged Prices |
| Timeline |
Data#3 Lagged Returns
When evaluating Data#3's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Data#3 stock have on its future price. Data#3 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, Data#3 autocorrelation shows the relationship between Data#3 stock current value and its past values and can show if there is a momentum factor associated with investing in Data3 Limited.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Other Information on Investing in Data#3 Stock
Data#3 financial ratios help investors to determine whether Data#3 Stock 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 Data#3 with respect to the benefits of owning Data#3 security.