Correlation Between MGIC INVESTMENT and Keck Seng
Can any of the company-specific risk be diversified away by investing in both MGIC INVESTMENT and Keck Seng 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 MGIC INVESTMENT and Keck Seng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MGIC INVESTMENT and Keck Seng Investments, you can compare the effects of market volatilities on MGIC INVESTMENT and Keck Seng 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 MGIC INVESTMENT with a short position of Keck Seng. Check out your portfolio center. Please also check ongoing floating volatility patterns of MGIC INVESTMENT and Keck Seng.
Diversification Opportunities for MGIC INVESTMENT and Keck Seng
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between MGIC and Keck is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding MGIC INVESTMENT and Keck Seng Investments in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Keck Seng Investments and MGIC INVESTMENT 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 MGIC INVESTMENT are associated (or correlated) with Keck Seng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Keck Seng Investments has no effect on the direction of MGIC INVESTMENT i.e., MGIC INVESTMENT and Keck Seng go up and down completely randomly.
Pair Corralation between MGIC INVESTMENT and Keck Seng
Assuming the 90 days trading horizon MGIC INVESTMENT is expected to generate 1.13 times less return on investment than Keck Seng. But when comparing it to its historical volatility, MGIC INVESTMENT is 3.15 times less risky than Keck Seng. It trades about 0.15 of its potential returns per unit of risk. Keck Seng Investments is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 24.00 in Keck Seng Investments on November 6, 2024 and sell it today you would earn a total of 2.00 from holding Keck Seng Investments or generate 8.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
MGIC INVESTMENT vs. Keck Seng Investments
Performance |
Timeline |
MGIC INVESTMENT |
Keck Seng Investments |
MGIC INVESTMENT and Keck Seng Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MGIC INVESTMENT and Keck Seng
The main advantage of trading using opposite MGIC INVESTMENT and Keck Seng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MGIC INVESTMENT position performs unexpectedly, Keck Seng 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 Keck Seng will offset losses from the drop in Keck Seng's long position.MGIC INVESTMENT vs. Taiwan Semiconductor Manufacturing | MGIC INVESTMENT vs. SBM OFFSHORE | MGIC INVESTMENT vs. Semiconductor Manufacturing International | MGIC INVESTMENT vs. ON SEMICONDUCTOR |
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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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