Correlation Between Snap and Nova Fund
Can any of the company-specific risk be diversified away by investing in both Snap and Nova Fund 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 Snap and Nova Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Snap Inc and Nova Fund Class, you can compare the effects of market volatilities on Snap and Nova Fund 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 Snap with a short position of Nova Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Snap and Nova Fund.
Diversification Opportunities for Snap and Nova Fund
Poor diversification
The 3 months correlation between Snap and Nova is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Snap Inc and Nova Fund Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nova Fund Class and Snap 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 Snap Inc are associated (or correlated) with Nova Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nova Fund Class has no effect on the direction of Snap i.e., Snap and Nova Fund go up and down completely randomly.
Pair Corralation between Snap and Nova Fund
Given the investment horizon of 90 days Snap Inc is expected to generate 3.49 times more return on investment than Nova Fund. However, Snap is 3.49 times more volatile than Nova Fund Class. It trades about 0.03 of its potential returns per unit of risk. Nova Fund Class is currently generating about 0.11 per unit of risk. If you would invest 1,004 in Snap Inc on August 31, 2024 and sell it today you would earn a total of 177.00 from holding Snap Inc or generate 17.63% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 99.73% |
| Values | Daily Returns |
Snap Inc vs. Nova Fund Class
Performance |
| Timeline |
| Snap Inc |
| Nova Fund Class |
Snap and Nova Fund Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Snap and Nova Fund
The main advantage of trading using opposite Snap and Nova Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Snap position performs unexpectedly, Nova Fund 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 Nova Fund will offset losses from the drop in Nova Fund's long position.The idea behind Snap Inc and Nova Fund Class 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.| Nova Fund vs. Nasdaq 100 2x Strategy | Nova Fund vs. Nasdaq 100 2x Strategy | Nova Fund vs. Nasdaq 100 2x Strategy | Nova Fund vs. Ultra Nasdaq 100 Profunds |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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