Extreme Net Borrowings from 2010 to 2024
| EXTR Stock | USD 16.03 0.37 2.36% |
Net Borrowings | First Reported 2013-12-31 | Previous Quarter -15.2 M | Current Value -27.5 M | Quarterly Volatility 38.2 M |
Check Extreme Networks financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Extreme Networks' main balance sheet or income statement drivers, such as Depreciation And Amortization of 30.1 M, Interest Expense of 17.8 M or Total Revenue of 601.8 M, as well as many indicators such as Price To Sales Ratio of 2.82, Dividend Yield of 0.0 or PTB Ratio of 70.5. Extreme financial statements analysis is a perfect complement when working with Extreme Networks Valuation or Volatility modules.
Extreme | Net Borrowings |
Latest Extreme Networks' Net Borrowings Growth Pattern
Below is the plot of the Net Borrowings of Extreme Networks over the last few years. It is the difference between the amount of new debt a company has taken on and the amount of debt it has paid off during a given period. Extreme Networks' Net Borrowings historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Extreme Networks' overall financial position and show how it may be relating to other accounts over time.
| Net Borrowings | 10 Years Trend |
|
Net Borrowings |
| Timeline |
Extreme Net Borrowings Regression Statistics
| Arithmetic Mean | 27,535,922 | |
| Geometric Mean | 68,613,336 | |
| Coefficient Of Variation | 361.20 | |
| Mean Deviation | 87,731,006 | |
| Median | (11,375,000) | |
| Standard Deviation | 99,459,361 | |
| Sample Variance | 9892.2T | |
| Range | 306.8M | |
| R-Value | (0.63) | |
| Mean Square Error | 6468.8T | |
| R-Squared | 0.39 | |
| Significance | 0.01 | |
| Slope | (13,938,134) | |
| Total Sum of Squares | 138490.3T |
Extreme Net Borrowings History
About Extreme Networks Financial Statements
Extreme Networks shareholders use historical fundamental indicators, such as Net Borrowings, to determine how well the company is positioned to perform in the future. Although Extreme Networks investors may analyze each financial statement separately, they are all interrelated. The changes in Extreme Networks' assets and liabilities, for example, are also reflected in the revenues and expenses on on Extreme Networks' income statement. Understanding these patterns can help investors time the market effectively. Please read more on our fundamental analysis page.
| Last Reported | Projected for Next Year | ||
| Net Borrowings | -78.1 M | -74.2 M |
Pair Trading with Extreme Networks
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 Extreme Networks 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 Extreme Networks will appreciate offsetting losses from the drop in the long position's value.Moving together with Extreme Stock
| 0.61 | CSCO | Cisco Systems Aggressive Push | PairCorr |
Moving against Extreme Stock
| 0.44 | CDW | CDW Corp | PairCorr |
| 0.37 | TER | Teradyne | PairCorr |
| 0.37 | ACLS | Axcelis Technologies | PairCorr |
| 0.37 | AEHR | Aehr Test Systems | PairCorr |
| 0.35 | ASYS | Amtech Systems Fiscal Year End 12th of December 2024 | PairCorr |
The ability to find closely correlated positions to Extreme Networks could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Extreme Networks 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 Extreme Networks - 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 Extreme Networks to buy it.
The correlation of Extreme Networks 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 Extreme Networks moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Extreme Networks 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 Extreme Networks 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.Additional Tools for Extreme Stock Analysis
When running Extreme Networks' price analysis, check to measure Extreme Networks' market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Extreme Networks is operating at the current time. Most of Extreme Networks' value examination focuses on studying past and present price action to predict the probability of Extreme Networks' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Extreme Networks' price. Additionally, you may evaluate how the addition of Extreme Networks to your portfolios can decrease your overall portfolio volatility.