Sangoma Average Payables vs Book Value Per Share Analysis
STC Stock | 8.54 0.05 0.58% |
Sangoma Technologies financial indicator trend analysis is much more than just breaking down Sangoma Technologies Corp prevalent accounting drivers to predict future trends. We encourage investors to analyze account correlations over time for multiple indicators to determine whether Sangoma Technologies Corp is a good investment. Please check the relationship between Sangoma Technologies Average Payables and its Book Value Per Share accounts. Check out World Market Map to better understand how to build diversified portfolios, which includes a position in Sangoma Technologies Corp. 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.
Average Payables vs Book Value Per Share
Average Payables vs Book Value Per Share Correlation Analysis
The overlapping area represents the amount of trend that can be explained by analyzing historical patterns of Sangoma Technologies Corp Average Payables account and Book Value Per Share. At this time, the significance of the direction appears to have weak contrarian relationship.
The correlation between Sangoma Technologies' Average Payables and Book Value Per Share is -0.14. Overlapping area represents the amount of variation of Average Payables that can explain the historical movement of Book Value Per Share in the same time period over historical financial statements of Sangoma Technologies Corp, assuming nothing else is changed. The correlation between historical values of Sangoma Technologies' Average Payables and Book Value Per Share is a relative statistical measure of the degree to which these accounts tend to move together. The correlation coefficient measures the extent to which Average Payables of Sangoma Technologies Corp are associated (or correlated) with its Book Value Per Share. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when Book Value Per Share has no effect on the direction of Average Payables i.e., Sangoma Technologies' Average Payables and Book Value Per Share go up and down completely randomly.
Correlation Coefficient | -0.14 |
Relationship Direction | Negative |
Relationship Strength | Insignificant |
Average Payables
The average amount owed to suppliers and creditors over a specific period, reflecting the company's payment cycle and credit terms with suppliers.Book Value Per Share
The ratio of equity available to common shareholders divided by the number of outstanding shares. This measure represents the value per share of a company according to its financial statements.Most indicators from Sangoma Technologies' fundamental ratios are interrelated and interconnected. However, analyzing fundamental ratios indicators one by one will only give a small insight into Sangoma Technologies Corp 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 Sangoma Technologies Corp. 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, Sangoma Technologies' Selling General Administrative is very stable compared to the past year. As of the 29th of November 2024, Sales General And Administrative To Revenue is likely to grow to 0.26, though Tax Provision is likely to grow to (798 K).
2021 | 2022 | 2023 | 2024 (projected) | Gross Profit | 156.9M | 172.8M | 172.8M | 181.5M | Total Revenue | 224.4M | 252.5M | 247.3M | 259.6M |
Sangoma Technologies fundamental ratios Correlations
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Sangoma Technologies Account Relationship Matchups
High Positive Relationship
High Negative Relationship
Sangoma Technologies fundamental ratios Accounts
2019 | 2020 | 2021 | 2022 | 2023 | 2024 (projected) | ||
Total Assets | 128.7M | 540.1M | 498.5M | 442.7M | 400.6M | 420.7M | |
Short Long Term Debt Total | 61.8M | 89.2M | 122.6M | 115.2M | 132.4M | 139.1M | |
Other Current Liab | 3.6M | 4.4M | 17.0M | 7.8M | 9.0M | 9.4M | |
Total Current Liabilities | 36.4M | 55.1M | 78.4M | 63.2M | 60.1M | 63.1M | |
Total Stockholder Equity | 54.8M | 376.0M | 293.8M | 266.1M | 259.7M | 272.7M | |
Current Deferred Revenue | 7.9M | 11.4M | 11.6M | 10.9M | 12.5M | 13.2M | |
Net Debt | 29.2M | 67.1M | 109.9M | 104M | 61.6M | 64.7M | |
Retained Earnings | 6.2M | 7.4M | (104.3M) | (133.3M) | (141.9M) | (134.8M) | |
Accounts Payable | 10.4M | 22.4M | 28.6M | 24.1M | 21.5M | 22.5M | |
Non Current Assets Total | 88.7M | 486.8M | 437.5M | 381.1M | 343.5M | 360.7M | |
Other Assets | 8.2M | 4.4M | 8.9M | 13.9M | 16.0M | 16.8M | |
Net Receivables | 9.0M | 16.1M | 25.2M | 26.9M | 16.0M | 16.8M | |
Common Stock Shares Outstanding | 10.4M | 29.2M | 31.5M | 33.1M | 33.3M | 35.0M | |
Liabilities And Stockholders Equity | 128.7M | 540.1M | 498.5M | 442.7M | 509.2M | 534.6M | |
Inventory | 9.3M | 11.8M | 17.4M | 18.0M | 14.8M | 15.5M | |
Other Stockholder Equity | 1.8M | 200.4M | 194.2M | 18.1M | 20.9M | 23.7M | |
Total Liab | 73.9M | 164.1M | 204.7M | 176.6M | 140.9M | 148.0M | |
Total Current Assets | 40.0M | 53.3M | 61.0M | 61.6M | 57.1M | 60.0M | |
Short Term Debt | 14.5M | 17.0M | 21.3M | 20.4M | 23.5M | 24.7M | |
Intangible Assets | 38.6M | 195.4M | 194.2M | 164.0M | 131.9M | 138.5M | |
Non Current Liabilities Total | 37.5M | 109.0M | 126.3M | 113.4M | 80.8M | 84.9M | |
Property Plant And Equipment Net | 14.0M | 21.2M | 27.2M | 22.3M | 18.6M | 19.5M | |
Cash | 20.0M | 22.1M | 12.7M | 11.2M | 16.2M | 17.0M | |
Cash And Short Term Investments | 20.0M | 22.1M | 12.7M | 11.2M | 12.8M | 6.9M | |
Other Current Assets | 1.7M | 3.3M | 4.4M | 4.4M | 3.9M | 4.1M | |
Accumulated Other Comprehensive Income | (506.6K) | (14.4M) | 839K | 1.3M | 1.2M | 1.3M | |
Good Will | 32.2M | 267.3M | 210.0M | 187.5M | 215.6M | 226.4M | |
Common Stock | 47.3M | 182.5M | 203.0M | 379.9M | 436.9M | 458.8M | |
Long Term Debt Total | 47.3M | 72.2M | 101.3M | 94.7M | 108.9M | 114.4M | |
Capital Surpluse | 2.4M | 5.4M | 15.1M | 18.1M | 20.9M | 21.9M | |
Property Plant Equipment | 18.9M | 21.1M | 27.2M | 22.3M | 25.6M | 12.9M | |
Other Liab | 4.0M | 36.8M | 25.0M | 18.7M | 21.5M | 16.3M | |
Net Tangible Assets | (19.7M) | (85.3M) | (107.6M) | (78.8M) | (71.0M) | (74.5M) | |
Long Term Debt | 33.6M | 60.4M | 86.9M | 83.1M | 58.0M | 54.1M | |
Deferred Long Term Liab | 2.5M | 1.5M | 2.9M | 6.6M | 7.6M | 7.9M | |
Net Invested Capital | 91.7M | 450.9M | 398.4M | 366.9M | 337.6M | 271.1M | |
Short Long Term Debt | 3.0M | 12.4M | 14.5M | 17.7M | 19.9M | 13.5M | |
Net Working Capital | 3.6M | (1.8M) | (17.4M) | (1.6M) | (3.0M) | (2.8M) |
Pair Trading with Sangoma Technologies
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Sangoma Technologies position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Sangoma Technologies will appreciate offsetting losses from the drop in the long position's value.Moving against Sangoma Stock
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The ability to find closely correlated positions to Sangoma Technologies could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Sangoma Technologies when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Sangoma Technologies - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Sangoma Technologies Corp to buy it.
The correlation of Sangoma Technologies is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Sangoma Technologies moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Sangoma Technologies Corp moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Sangoma Technologies can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out World Market Map to better understand how to build diversified portfolios, which includes a position in Sangoma Technologies Corp. 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. You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.