Cadiz Share Based Compensation Trend

CDZI -- USA Stock  

USD 10.70  0.10  0.93%

This module enables investors to look at Cadiz 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 392.9 K, Gross Profit of 437 K or Interest Expense of 11.8 M, but also many exotic indicators such as Long Term Debt to Equity of 31.7172, PPandE Turnover of 0.0081 or Receivables Turnover of 1.6791. This module is a perfect complement to use when analyzing Cadiz Valuation or Volatility. It can also complement various Cadiz Technical models. Check also analysis of Cadiz Correlation with competitors.
Showing smoothed Share Based Compensation of Cadiz with missing and latest data points interpolated. A component of Net Cash Flow from Operations representing the total amount of noncash; equity-based employee remuneration. This may include the value of stock or unit options; amortization of restricted stock or units; and adjustment for officers' compensation. As noncash; this element is an add back when calculating net cash generated by operating activities using the indirect method.
Share Based Compensation10 Years Trend
Slightly volatile
 Share Based Compensation 

Cadiz Regression Statistics

Arithmetic Mean 3,081,245
Geometric Mean 1,739,819
Coefficient Of Variation 145.52
Mean Deviation 2,657,544
Median 1,312,941
Standard Deviation 4,483,852
Range 16,304,000
R Value(0.64)
R Squared 0.42
Significance 0.023586

Cadiz Share Based Compensation Over Time

2016-12-31  1,116,000 
2017-12-31  1,116,000 
2018-12-31  1,312,941 

Other Fundumenentals of Cadiz

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Cadiz Upcoming Events

Cadiz Upcoming Company Events

Upcoming Quarterly ReportMarch 13, 2017
Next Earnings ReportMay 8, 2017
Check also analysis of Cadiz 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.