Correlation Between Food Life and MGIC Investment
Can any of the company-specific risk be diversified away by investing in both Food Life and MGIC Investment 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 Food Life and MGIC Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Food Life Companies and MGIC Investment, you can compare the effects of market volatilities on Food Life and MGIC Investment 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 Food Life with a short position of MGIC Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Food Life and MGIC Investment.
Diversification Opportunities for Food Life and MGIC Investment
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Food and MGIC is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Food Life Companies and MGIC Investment in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MGIC Investment and Food Life 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 Food Life Companies are associated (or correlated) with MGIC Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MGIC Investment has no effect on the direction of Food Life i.e., Food Life and MGIC Investment go up and down completely randomly.
Pair Corralation between Food Life and MGIC Investment
Assuming the 90 days horizon Food Life Companies is expected to generate 1.11 times more return on investment than MGIC Investment. However, Food Life is 1.11 times more volatile than MGIC Investment. It trades about 0.22 of its potential returns per unit of risk. MGIC Investment is currently generating about -0.17 per unit of risk. If you would invest 1,940 in Food Life Companies on September 23, 2024 and sell it today you would earn a total of 160.00 from holding Food Life Companies or generate 8.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Food Life Companies vs. MGIC Investment
Performance |
Timeline |
Food Life Companies |
MGIC Investment |
Food Life and MGIC Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Food Life and MGIC Investment
The main advantage of trading using opposite Food Life and MGIC Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Food Life position performs unexpectedly, MGIC Investment 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 MGIC Investment will offset losses from the drop in MGIC Investment's long position.Food Life vs. HK Electric Investments | Food Life vs. Apollo Investment Corp | Food Life vs. Khiron Life Sciences | Food Life vs. BLUESCOPE STEEL |
MGIC Investment vs. URBAN OUTFITTERS | MGIC Investment vs. Food Life Companies | MGIC Investment vs. CN MODERN DAIRY | MGIC Investment vs. RYU Apparel |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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