Correlation Between KNC and Axie Infinity
Can any of the company-specific risk be diversified away by investing in both KNC and Axie Infinity 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 KNC and Axie Infinity into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KNC and Axie Infinity Shards, you can compare the effects of market volatilities on KNC and Axie Infinity 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 KNC with a short position of Axie Infinity. Check out your portfolio center. Please also check ongoing floating volatility patterns of KNC and Axie Infinity.
Diversification Opportunities for KNC and Axie Infinity
0.98 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between KNC and Axie is 0.98. Overlapping area represents the amount of risk that can be diversified away by holding KNC and Axie Infinity Shards in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Axie Infinity Shards and KNC 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 KNC are associated (or correlated) with Axie Infinity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Axie Infinity Shards has no effect on the direction of KNC i.e., KNC and Axie Infinity go up and down completely randomly.
Pair Corralation between KNC and Axie Infinity
Assuming the 90 days trading horizon KNC is expected to generate 0.92 times more return on investment than Axie Infinity. However, KNC is 1.08 times less risky than Axie Infinity. It trades about -0.11 of its potential returns per unit of risk. Axie Infinity Shards is currently generating about -0.19 per unit of risk. If you would invest 53.00 in KNC on December 28, 2024 and sell it today you would lose (17.00) from holding KNC or give up 32.08% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
KNC vs. Axie Infinity Shards
Performance |
Timeline |
KNC |
Axie Infinity Shards |
KNC and Axie Infinity Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KNC and Axie Infinity
The main advantage of trading using opposite KNC and Axie Infinity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KNC position performs unexpectedly, Axie Infinity 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 Axie Infinity will offset losses from the drop in Axie Infinity's long position.The idea behind KNC and Axie Infinity Shards 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.Axie Infinity vs. Staked Ether | Axie Infinity vs. Phala Network | Axie Infinity vs. EigenLayer | Axie Infinity vs. EOSDAC |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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