Correlation Between Bank of Communications and Nanjing Medlander
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By analyzing existing cross correlation between Bank of Communications and Nanjing Medlander Medical, you can compare the effects of market volatilities on Bank of Communications and Nanjing Medlander 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 Bank of Communications with a short position of Nanjing Medlander. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Communications and Nanjing Medlander.
Diversification Opportunities for Bank of Communications and Nanjing Medlander
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between Bank and Nanjing is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Communications and Nanjing Medlander Medical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nanjing Medlander Medical and Bank of Communications 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 Bank of Communications are associated (or correlated) with Nanjing Medlander. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nanjing Medlander Medical has no effect on the direction of Bank of Communications i.e., Bank of Communications and Nanjing Medlander go up and down completely randomly.
Pair Corralation between Bank of Communications and Nanjing Medlander
Assuming the 90 days trading horizon Bank of Communications is expected to generate 0.46 times more return on investment than Nanjing Medlander. However, Bank of Communications is 2.17 times less risky than Nanjing Medlander. It trades about 0.05 of its potential returns per unit of risk. Nanjing Medlander Medical is currently generating about -0.03 per unit of risk. If you would invest 554.00 in Bank of Communications on August 26, 2024 and sell it today you would earn a total of 154.00 from holding Bank of Communications or generate 27.8% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of Communications vs. Nanjing Medlander Medical
Performance |
| Timeline |
| Bank of Communications |
| Nanjing Medlander Medical |
Bank of Communications and Nanjing Medlander Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of Communications and Nanjing Medlander
The main advantage of trading using opposite Bank of Communications and Nanjing Medlander positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Communications position performs unexpectedly, Nanjing Medlander 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 Nanjing Medlander will offset losses from the drop in Nanjing Medlander's long position.| Bank of Communications vs. Changchun Faway Automobile | Bank of Communications vs. Iat Automobile Technology | Bank of Communications vs. CIMC Vehicles Co | Bank of Communications vs. MayAir Technology Co |
| Nanjing Medlander vs. Bank of China | Nanjing Medlander vs. Kweichow Moutai Co | Nanjing Medlander vs. PetroChina Co Ltd | Nanjing Medlander vs. Bank of Communications |
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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