Correlation Between Giant Manufacturing and GlobalWafers
Can any of the company-specific risk be diversified away by investing in both Giant Manufacturing and GlobalWafers 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 Giant Manufacturing and GlobalWafers into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Giant Manufacturing Co and GlobalWafers Co, you can compare the effects of market volatilities on Giant Manufacturing and GlobalWafers 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 Giant Manufacturing with a short position of GlobalWafers. Check out your portfolio center. Please also check ongoing floating volatility patterns of Giant Manufacturing and GlobalWafers.
Diversification Opportunities for Giant Manufacturing and GlobalWafers
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Giant and GlobalWafers is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Giant Manufacturing Co and GlobalWafers Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GlobalWafers and Giant Manufacturing 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 Giant Manufacturing Co are associated (or correlated) with GlobalWafers. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GlobalWafers has no effect on the direction of Giant Manufacturing i.e., Giant Manufacturing and GlobalWafers go up and down completely randomly.
Pair Corralation between Giant Manufacturing and GlobalWafers
Assuming the 90 days trading horizon Giant Manufacturing Co is expected to under-perform the GlobalWafers. In addition to that, Giant Manufacturing is 1.48 times more volatile than GlobalWafers Co. It trades about -0.24 of its total potential returns per unit of risk. GlobalWafers Co is currently generating about -0.11 per unit of volatility. If you would invest 46,000 in GlobalWafers Co on September 12, 2024 and sell it today you would lose (4,700) from holding GlobalWafers Co or give up 10.22% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Giant Manufacturing Co vs. GlobalWafers Co
Performance |
Timeline |
Giant Manufacturing |
GlobalWafers |
Giant Manufacturing and GlobalWafers Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Giant Manufacturing and GlobalWafers
The main advantage of trading using opposite Giant Manufacturing and GlobalWafers positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Giant Manufacturing position performs unexpectedly, GlobalWafers 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 GlobalWafers will offset losses from the drop in GlobalWafers' long position.Giant Manufacturing vs. Feng Tay Enterprises | Giant Manufacturing vs. Ruentex Development Co | Giant Manufacturing vs. WiseChip Semiconductor | Giant Manufacturing vs. Novatek Microelectronics Corp |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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