Deutsche Bank Net Cash Flow Investment Acquisitions and Disposals Trend

DB -- USA Stock  

USD 11.01  0.12  1.10%

This module enables investors to look at Deutsche Bank various fundamental indicators over time in order to gain insight into the company future performance. Macroaxis historical fundamental analysis tools allow evaluation of not only typical financial statement drivers such as Cost of Revenue of 301.2 M, Gross Profit of 25.9 B or Net Income to Non Controlling Interests of 24.7 M, but also many exotic indicators such as Asset Turnover of 0.0235, Book Value per Share of 53.1294 or Debt to Equity Ratio of 24.913. This module is a perfect complement to use when analyzing Deutsche Bank Valuation or Volatility. It can also complement various Deutsche Bank Technical models. Additionally see analysis of Deutsche Bank Correlation with competitors.
Showing smoothed Net Cash Flow Investment Acquisitions and Disposals of Deutsche Bank Aktiengesellschaft with missing and latest data points interpolated. A component of Net Cash Flow from Investing representing the net cash inflow (outflow) associated with the acquisition & disposal of investments, including marketable securities and loan originations.
Net Cash Flow Investment Acquisitions and Disposals10 Years Trend
Decreasing
Slightly volatile
 Net Cash Flow Investment Acquisitions and Disposals 
      Timeline 

Regression Statistics

Arithmetic Mean (3,634,307,692)
Coefficient Of Variation (189.19)
Mean Deviation  5,335,207,101
Median (4,515,000,000)
Standard Deviation  6,875,684,516
Range  26,104,000,000
R Value (0.34)
R Squared  0.12
Significance  0.25
Slope (606,846,154)

Deutsche Bank Net Cash Flow Investment Acquisitions and Disposals Over Time

2016-12-31 (7,582,000,000) 
2017-12-31 (7,582,000,000) 
2018-12-31 (8,920,000,000) 

Other Fundumenentals

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Additionally see analysis of Deutsche Bank Correlation with competitors. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.