Correlation Between Hang Seng and Bank of the Philippine Is
Can any of the company-specific risk be diversified away by investing in both Hang Seng and Bank of the Philippine Is 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 Hang Seng and Bank of the Philippine Is into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hang Seng Bank and Bank of the, you can compare the effects of market volatilities on Hang Seng and Bank of the Philippine Is 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 Hang Seng with a short position of Bank of the Philippine Is. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hang Seng and Bank of the Philippine Is.
Diversification Opportunities for Hang Seng and Bank of the Philippine Is
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hang and Bank is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Hang Seng Bank and Bank of the in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of the Philippine Is and Hang Seng 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 Hang Seng Bank are associated (or correlated) with Bank of the Philippine Is. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of the Philippine Is has no effect on the direction of Hang Seng i.e., Hang Seng and Bank of the Philippine Is go up and down completely randomly.
Pair Corralation between Hang Seng and Bank of the Philippine Is
Assuming the 90 days horizon Hang Seng Bank is expected to generate 0.43 times more return on investment than Bank of the Philippine Is. However, Hang Seng Bank is 2.35 times less risky than Bank of the Philippine Is. It trades about -0.1 of its potential returns per unit of risk. Bank of the is currently generating about -0.21 per unit of risk. If you would invest 1,231 in Hang Seng Bank on August 31, 2024 and sell it today you would lose (39.00) from holding Hang Seng Bank or give up 3.17% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.65% |
| Values | Daily Returns |
Hang Seng Bank vs. Bank of the
Performance |
| Timeline |
| Hang Seng Bank |
| Bank of the Philippine Is |
Hang Seng and Bank of the Philippine Is Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hang Seng and Bank of the Philippine Is
The main advantage of trading using opposite Hang Seng and Bank of the Philippine Is positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hang Seng position performs unexpectedly, Bank of the Philippine Is 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 Bank of the Philippine Is will offset losses from the drop in Bank of the Philippine Is' long position.| Hang Seng vs. Bank Mandiri Persero | Hang Seng vs. Piraeus Bank SA | Hang Seng vs. Kasikornbank Public Co | Hang Seng vs. Turkiye Garanti Bankasi |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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