Correlation Between Guangdong Marubi and Shenzhen Transsion
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By analyzing existing cross correlation between Guangdong Marubi Biotechnology and Shenzhen Transsion Holdings, you can compare the effects of market volatilities on Guangdong Marubi and Shenzhen Transsion 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 Guangdong Marubi with a short position of Shenzhen Transsion. Check out your portfolio center. Please also check ongoing floating volatility patterns of Guangdong Marubi and Shenzhen Transsion.
Diversification Opportunities for Guangdong Marubi and Shenzhen Transsion
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Guangdong and Shenzhen is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Guangdong Marubi Biotechnology and Shenzhen Transsion Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenzhen Transsion and Guangdong Marubi 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 Guangdong Marubi Biotechnology are associated (or correlated) with Shenzhen Transsion. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenzhen Transsion has no effect on the direction of Guangdong Marubi i.e., Guangdong Marubi and Shenzhen Transsion go up and down completely randomly.
Pair Corralation between Guangdong Marubi and Shenzhen Transsion
Assuming the 90 days trading horizon Guangdong Marubi Biotechnology is expected to under-perform the Shenzhen Transsion. But the stock apears to be less risky and, when comparing its historical volatility, Guangdong Marubi Biotechnology is 1.47 times less risky than Shenzhen Transsion. The stock trades about -0.01 of its potential returns per unit of risk. The Shenzhen Transsion Holdings is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 7,864 in Shenzhen Transsion Holdings on September 3, 2024 and sell it today you would earn a total of 1,608 from holding Shenzhen Transsion Holdings or generate 20.45% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Guangdong Marubi Biotechnology vs. Shenzhen Transsion Holdings
Performance |
| Timeline |
| Guangdong Marubi Bio |
| Shenzhen Transsion |
Guangdong Marubi and Shenzhen Transsion Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Guangdong Marubi and Shenzhen Transsion
The main advantage of trading using opposite Guangdong Marubi and Shenzhen Transsion positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Guangdong Marubi position performs unexpectedly, Shenzhen Transsion 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 Shenzhen Transsion will offset losses from the drop in Shenzhen Transsion's long position.| Guangdong Marubi vs. Beijing Wantai Biological | Guangdong Marubi vs. Aluminum Corp of | Guangdong Marubi vs. COL Digital Publishing | Guangdong Marubi vs. Shaanxi Meineng Clean |
| Shenzhen Transsion vs. Qumei Furniture Group | Shenzhen Transsion vs. Shuhua Sports Co | Shenzhen Transsion vs. Xilinmen Furniture Co | Shenzhen Transsion vs. Sportsoul Co Ltd |
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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