Correlation Between Visa and MegaStudy
Can any of the company-specific risk be diversified away by investing in both Visa and MegaStudy 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 Visa and MegaStudy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Visa Class A and MegaStudy Co, you can compare the effects of market volatilities on Visa and MegaStudy 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 Visa with a short position of MegaStudy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Visa and MegaStudy.
Diversification Opportunities for Visa and MegaStudy
Very weak diversification
The 3 months correlation between Visa and MegaStudy is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Visa Class A and MegaStudy Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MegaStudy and Visa 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 Visa Class A are associated (or correlated) with MegaStudy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MegaStudy has no effect on the direction of Visa i.e., Visa and MegaStudy go up and down completely randomly.
Pair Corralation between Visa and MegaStudy
Taking into account the 90-day investment horizon Visa is expected to generate 1.45 times less return on investment than MegaStudy. In addition to that, Visa is 1.16 times more volatile than MegaStudy Co. It trades about 0.13 of its total potential returns per unit of risk. MegaStudy Co is currently generating about 0.23 per unit of volatility. If you would invest 1,124,000 in MegaStudy Co on September 20, 2024 and sell it today you would earn a total of 36,000 from holding MegaStudy Co or generate 3.2% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 95.45% |
Values | Daily Returns |
Visa Class A vs. MegaStudy Co
Performance |
Timeline |
Visa Class A |
MegaStudy |
Visa and MegaStudy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Visa and MegaStudy
The main advantage of trading using opposite Visa and MegaStudy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Visa position performs unexpectedly, MegaStudy 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 MegaStudy will offset losses from the drop in MegaStudy's long position.The idea behind Visa Class A and MegaStudy Co 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.MegaStudy vs. DB Financial Investment | MegaStudy vs. Foodnamoo | MegaStudy vs. Samick Musical Instruments | MegaStudy vs. Hwangkum Steel Technology |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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