QQQN Financial Statements From 2010 to 2025
QQQN financial statements provide useful quarterly and yearly information to potential QQQN investors about the company's current and past financial position, as well as its overall management performance and changes in financial position over time. Historical trend examination of various income statement and balance sheet accounts found on QQQN financial statements helps investors assess QQQN's valuation, profitability, and current liquidity needs. Key fundamental drivers impacting QQQN's valuation are summarized below:QQQN does not currently have any trending fundamental ratios for analysis.
This module can also supplement various QQQN Technical models . Check out Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in producer price index.
Check QQQN financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among QQQN's main balance sheet or income statement drivers, such as , as well as many indicators such as . QQQN financial statements analysis is a perfect complement when working with QQQN Valuation or Volatility modules.
QQQN |
QQQN ETF Beta Analysis
QQQN's Beta is one of the most important measures of equity market volatility. Beta can be thought of as asset elasticity or sensitivity to market. In other words, it is a number that shows the relationship of an equity instrument to the financial market in which this instrument is traded. For example, if Beta of equity is 2, it is expected to significantly outperform market when the market is going up and significantly underperform when the market is going down. Similarly, Beta of 1 indicates that an asset and market will generate similar returns over time.
Current QQQN Beta | 1.16 |
Most of QQQN's fundamental indicators, such as Beta, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, QQQN is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
In a nutshell, Beta is a measure of individual stock risk relative to the overall volatility of the stock market. and is calculated based on very sound finance theory - Capital Assets Pricing Model (CAPM).However, since Beta is calculated based on historical price movements it may not predict how a firm's stock is going to perform in the future.
CompetitionIn accordance with the recently published financial statements, QQQN has a Beta of 1.16. This is much higher than that of the Victory Capital family and significantly higher than that of the Mid-Cap Growth category. The beta for all United States etfs is notably lower than that of the firm.
Pair Trading with QQQN
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 QQQN 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 QQQN will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Microsoft could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Microsoft 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 Microsoft - 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 Microsoft to buy it.
The correlation of Microsoft 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 Microsoft moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Microsoft 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 Microsoft 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 Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in producer price index. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
Other Tools for QQQN Etf
When running QQQN's price analysis, check to measure QQQN's 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 QQQN is operating at the current time. Most of QQQN's value examination focuses on studying past and present price action to predict the probability of QQQN's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move QQQN's price. Additionally, you may evaluate how the addition of QQQN to your portfolios can decrease your overall portfolio volatility.
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