Correlation Between Bank of China and SUN ART
Can any of the company-specific risk be diversified away by investing in both Bank of China and SUN ART 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 Bank of China and SUN ART into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of China and SUN ART RETAIL, you can compare the effects of market volatilities on Bank of China and SUN ART 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 China with a short position of SUN ART. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of China and SUN ART.
Diversification Opportunities for Bank of China and SUN ART
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and SUN is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Bank of China and SUN ART RETAIL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SUN ART RETAIL and Bank of China 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 China are associated (or correlated) with SUN ART. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SUN ART RETAIL has no effect on the direction of Bank of China i.e., Bank of China and SUN ART go up and down completely randomly.
Pair Corralation between Bank of China and SUN ART
Assuming the 90 days horizon Bank of China is expected to generate 4.4 times less return on investment than SUN ART. But when comparing it to its historical volatility, Bank of China is 1.41 times less risky than SUN ART. It trades about 0.08 of its potential returns per unit of risk. SUN ART RETAIL is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 25.00 in SUN ART RETAIL on September 20, 2024 and sell it today you would earn a total of 6.00 from holding SUN ART RETAIL or generate 24.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of China vs. SUN ART RETAIL
Performance |
| Timeline |
| Bank of China |
| SUN ART RETAIL |
Bank of China and SUN ART Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of China and SUN ART
The main advantage of trading using opposite Bank of China and SUN ART positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of China position performs unexpectedly, SUN ART 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 SUN ART will offset losses from the drop in SUN ART's long position.| Bank of China vs. Commonwealth Bank of | Bank of China vs. Superior Plus Corp | Bank of China vs. SIVERS SEMICONDUCTORS AB | Bank of China vs. CHINA HUARONG ENERHD 50 |
| SUN ART vs. SENECA FOODS A | SUN ART vs. Suntory Beverage Food | SUN ART vs. China Resources Beer | SUN ART vs. ScanSource |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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