Correlation Between ANT and Kwesst Micro
Can any of the company-specific risk be diversified away by investing in both ANT and Kwesst Micro at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining ANT and Kwesst Micro into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ANT and Kwesst Micro Systems, you can compare the effects of market volatilities on ANT and Kwesst Micro and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in ANT with a short position of Kwesst Micro. Check out your portfolio center. Please also check ongoing floating volatility patterns of ANT and Kwesst Micro.
Diversification Opportunities for ANT and Kwesst Micro
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between ANT and Kwesst is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding ANT and Kwesst Micro Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kwesst Micro Systems and ANT is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on ANT are associated (or correlated) with Kwesst Micro. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kwesst Micro Systems has no effect on the direction of ANT i.e., ANT and Kwesst Micro go up and down completely randomly.
Pair Corralation between ANT and Kwesst Micro
Assuming the 90 days trading horizon ANT is expected to generate 1.11 times more return on investment than Kwesst Micro. However, ANT is 1.11 times more volatile than Kwesst Micro Systems. It trades about 0.06 of its potential returns per unit of risk. Kwesst Micro Systems is currently generating about -0.04 per unit of risk. If you would invest 147.00 in ANT on December 20, 2024 and sell it today you would earn a total of 0.00 from holding ANT or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 95.24% |
Values | Daily Returns |
ANT vs. Kwesst Micro Systems
Performance |
Timeline |
ANT |
Kwesst Micro Systems |
ANT and Kwesst Micro Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ANT and Kwesst Micro
The main advantage of trading using opposite ANT and Kwesst Micro positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ANT position performs unexpectedly, Kwesst Micro 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 Kwesst Micro will offset losses from the drop in Kwesst Micro's long position.The idea behind ANT and Kwesst Micro Systems pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Kwesst Micro vs. AnalytixInsight | Kwesst Micro vs. Baylin Technologies | Kwesst Micro vs. Gatekeeper Systems |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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