Sensen Networks financial indicator trend analysis is much more than just breaking down Sensen Networks prevalent accounting drivers to predict future trends. We encourage investors to analyze account correlations over time for multiple indicators to determine whether Sensen Networks is a good investment. Please check the relationship between Sensen Networks Long Term Debt and its Net Receivables accounts. Check out
World Market Map to better understand how to build diversified portfolios, which includes a position in Sensen Networks. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as
signals in board of governors.
Long Term Debt vs Net Receivables
Long Term Debt vs Net Receivables Correlation Analysis
The overlapping area represents the amount of trend that can be explained by analyzing historical patterns of
Sensen Networks Long Term Debt account and
Net Receivables. At this time, the significance of the direction appears to have very week relationship.
The correlation between Sensen Networks' Long Term Debt and Net Receivables is 0.2. Overlapping area represents the amount of variation of Long Term Debt that can explain the historical movement of Net Receivables in the same time period over historical financial statements of Sensen Networks, assuming nothing else is changed. The correlation between historical values of Sensen Networks' Long Term Debt and Net Receivables is a relative statistical measure of the degree to which these accounts tend to move together. The correlation coefficient measures the extent to which Long Term Debt of Sensen Networks are associated (or correlated) with its Net Receivables. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when Net Receivables has no effect on the direction of Long Term Debt i.e., Sensen Networks' Long Term Debt and Net Receivables go up and down completely randomly.
Correlation Coefficient | 0.2 |
| Relationship Direction | Positive |
| Relationship Strength | Very Weak |
Long Term Debt
Long-term debt is a debt that Sensen Networks has held for over one year. Long-term debt appears on Sensen Networks balance sheet and also includes long-term leases. The most common forms of long term debt are bonds payable, long-term notes payable, mortgage payable, pension liabilities, and lease liabilities. In the corporate world, long-term debt is generally used to fund big-ticket items, such as machinery, buildings, and land. The total of long-term debt reported on Sensen Networks balance sheet is the sum of the balances of all categories of long-term debt. Debt that is not due within the current year and is often considered to be financing activities that are to be repaid over several years.
Net Receivables
Most indicators from Sensen Networks' fundamental ratios are interrelated and interconnected. However, analyzing fundamental ratios indicators one by one will only give a small insight into Sensen Networks current financial condition. On the other hand, looking into the entire matrix of fundamental ratios indicators, and analyzing their relationships over time can provide a more complete picture of the company financial strength now and in the future. Check out
World Market Map to better understand how to build diversified portfolios, which includes a position in Sensen Networks. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as
signals in board of governors.
At this time, Sensen Networks'
Selling General Administrative is comparatively stable compared to the past year.
Tax Provision is likely to gain to about 44.8
K in 2024, whereas
Issuance Of Capital Stock is likely to drop slightly above 1.8
M in 2024.
Sensen Networks fundamental ratios Correlations
Click cells to compare fundamentals
Sensen Networks Account Relationship Matchups
High Positive Relationship
High Negative Relationship
Sensen Networks fundamental ratios Accounts
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Additional Tools for Sensen Stock Analysis
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