Correlation Between Merida Industry and Yulon Nissan
Can any of the company-specific risk be diversified away by investing in both Merida Industry and Yulon Nissan 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 Merida Industry and Yulon Nissan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Merida Industry Co and Yulon Nissan Motor, you can compare the effects of market volatilities on Merida Industry and Yulon Nissan 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 Merida Industry with a short position of Yulon Nissan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Merida Industry and Yulon Nissan.
Diversification Opportunities for Merida Industry and Yulon Nissan
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Merida and Yulon is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Merida Industry Co and Yulon Nissan Motor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Yulon Nissan Motor and Merida Industry 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 Merida Industry Co are associated (or correlated) with Yulon Nissan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Yulon Nissan Motor has no effect on the direction of Merida Industry i.e., Merida Industry and Yulon Nissan go up and down completely randomly.
Pair Corralation between Merida Industry and Yulon Nissan
Assuming the 90 days trading horizon Merida Industry Co is expected to generate 1.27 times more return on investment than Yulon Nissan. However, Merida Industry is 1.27 times more volatile than Yulon Nissan Motor. It trades about -0.1 of its potential returns per unit of risk. Yulon Nissan Motor is currently generating about -0.23 per unit of risk. If you would invest 22,100 in Merida Industry Co on September 22, 2024 and sell it today you would lose (6,600) from holding Merida Industry Co or give up 29.86% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Merida Industry Co vs. Yulon Nissan Motor
Performance |
Timeline |
Merida Industry |
Yulon Nissan Motor |
Merida Industry and Yulon Nissan Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Merida Industry and Yulon Nissan
The main advantage of trading using opposite Merida Industry and Yulon Nissan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Merida Industry position performs unexpectedly, Yulon Nissan 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 Yulon Nissan will offset losses from the drop in Yulon Nissan's long position.Merida Industry vs. Cheng Shin Rubber | Merida Industry vs. Uni President Enterprises Corp | Merida Industry vs. Pou Chen Corp |
Yulon Nissan vs. Merida Industry Co | Yulon Nissan vs. Cheng Shin Rubber | Yulon Nissan vs. Uni President Enterprises Corp | Yulon Nissan vs. Pou Chen 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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