Deutsche Equity 500 Fund Statistic Functions Beta
| BTIIX Fund | USD 189.49 1.07 0.57% |
| Symbol |
The output start index for this execution was thirty-six with a total number of output elements of twenty-five. The Beta measures systematic risk based on how returns on Deutsche Equity 500 correlated with the market. If Beta is less than 0 Deutsche Equity generally moves in the opposite direction as compared to the market. If Deutsche Equity Beta is about zero movement of price series is uncorrelated with the movement of the benchmark. if Beta is between zero and one Deutsche Equity 500 is generally moves in the same direction as, but less than the movement of the market. For Beta = 1 movement of Deutsche Equity is generally in the same direction as the market. If Beta > 1 Deutsche Equity moves generally in the same direction as, but more than the movement of the benchmark.
Deutsche Equity Technical Analysis Modules
Most technical analysis of Deutsche Equity help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Deutsche from various momentum indicators to cycle indicators. When you analyze Deutsche charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Deutsche Equity Predictive Technical Analysis
Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Deutsche Equity 500. We use our internally-developed statistical techniques to arrive at the intrinsic value of Deutsche Equity 500 based on widely used predictive technical indicators. In general, we focus on analyzing Deutsche Mutual Fund price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Deutsche Equity's daily price indicators and compare them against related drivers, such as statistic functions and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Deutsche Equity's intrinsic value. In addition to deriving basic predictive indicators for Deutsche Equity, we also check how macroeconomic factors affect Deutsche Equity price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Be your own money manager
As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.Generate Optimal Portfolios
Align your risk and return expectations
Other Information on Investing in Deutsche Mutual Fund
Deutsche Equity financial ratios help investors to determine whether Deutsche Mutual Fund 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 Deutsche with respect to the benefits of owning Deutsche Equity security.
| Idea Breakdown Analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes | |
| Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity | |
| Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |