Correlation Between Giant Manufacturing and O TA
Can any of the company-specific risk be diversified away by investing in both Giant Manufacturing and O TA 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 O TA 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 O TA Precision Industry, you can compare the effects of market volatilities on Giant Manufacturing and O TA 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 O TA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Giant Manufacturing and O TA.
Diversification Opportunities for Giant Manufacturing and O TA
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Giant and 8924 is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Giant Manufacturing Co and O TA Precision Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on O TA Precision 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 O TA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of O TA Precision has no effect on the direction of Giant Manufacturing i.e., Giant Manufacturing and O TA go up and down completely randomly.
Pair Corralation between Giant Manufacturing and O TA
Assuming the 90 days trading horizon Giant Manufacturing Co is expected to under-perform the O TA. In addition to that, Giant Manufacturing is 6.0 times more volatile than O TA Precision Industry. It trades about -0.37 of its total potential returns per unit of risk. O TA Precision Industry is currently generating about -0.37 per unit of volatility. If you would invest 8,310 in O TA Precision Industry on August 29, 2024 and sell it today you would lose (230.00) from holding O TA Precision Industry or give up 2.77% 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. O TA Precision Industry
Performance |
| Timeline |
| Giant Manufacturing |
| O TA Precision |
Giant Manufacturing and O TA Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Giant Manufacturing and O TA
The main advantage of trading using opposite Giant Manufacturing and O TA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Giant Manufacturing position performs unexpectedly, O TA 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 O TA will offset losses from the drop in O TA's long position.| Giant Manufacturing vs. Merida Industry Co | Giant Manufacturing vs. President Chain Store | Giant Manufacturing vs. Cheng Shin Rubber | Giant Manufacturing vs. Uni President Enterprises Corp |
| O TA vs. Advanced International Multitech | O TA vs. Dynamic Precision Industry | O TA vs. Greatek Electronics | O TA vs. Qisda Corp |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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