Correlation Between PNC Financial and BANK OF CHINA -H-
Can any of the company-specific risk be diversified away by investing in both PNC Financial and BANK OF CHINA -H- 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 PNC Financial and BANK OF CHINA -H- into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PNC Financial Services and BANK OF CHINA, you can compare the effects of market volatilities on PNC Financial and BANK OF CHINA -H- 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 PNC Financial with a short position of BANK OF CHINA -H-. Check out your portfolio center. Please also check ongoing floating volatility patterns of PNC Financial and BANK OF CHINA -H-.
Diversification Opportunities for PNC Financial and BANK OF CHINA -H-
-0.34 | Correlation Coefficient |
Very good diversification
The 3 months correlation between PNC and BANK is -0.34. Overlapping area represents the amount of risk that can be diversified away by holding PNC Financial Services and BANK OF CHINA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BANK OF CHINA -H- and PNC Financial 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 PNC Financial Services are associated (or correlated) with BANK OF CHINA -H-. 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 CHINA -H- has no effect on the direction of PNC Financial i.e., PNC Financial and BANK OF CHINA -H- go up and down completely randomly.
Pair Corralation between PNC Financial and BANK OF CHINA -H-
Assuming the 90 days trading horizon PNC Financial Services is expected to under-perform the BANK OF CHINA -H-. But the stock apears to be less risky and, when comparing its historical volatility, PNC Financial Services is 2.65 times less risky than BANK OF CHINA -H-. The stock trades about -0.13 of its potential returns per unit of risk. The BANK OF CHINA is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 34.00 in BANK OF CHINA on December 20, 2024 and sell it today you would earn a total of 21.00 from holding BANK OF CHINA or generate 61.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
PNC Financial Services vs. BANK OF CHINA
Performance |
Timeline |
PNC Financial Services |
BANK OF CHINA -H- |
PNC Financial and BANK OF CHINA -H- Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with PNC Financial and BANK OF CHINA -H-
The main advantage of trading using opposite PNC Financial and BANK OF CHINA -H- positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PNC Financial position performs unexpectedly, BANK OF CHINA -H- 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 CHINA -H- will offset losses from the drop in BANK OF CHINA -H-'s long position.PNC Financial vs. CORNISH METALS INC | PNC Financial vs. THAI BEVERAGE | PNC Financial vs. Harmony Gold Mining | PNC Financial vs. Fevertree Drinks PLC |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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