Correlation Between CHIBA BANK and AAC TECHNOLOGHLDGADR
Can any of the company-specific risk be diversified away by investing in both CHIBA BANK and AAC TECHNOLOGHLDGADR 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 CHIBA BANK and AAC TECHNOLOGHLDGADR into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CHIBA BANK and AAC TECHNOLOGHLDGADR, you can compare the effects of market volatilities on CHIBA BANK and AAC TECHNOLOGHLDGADR 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 CHIBA BANK with a short position of AAC TECHNOLOGHLDGADR. Check out your portfolio center. Please also check ongoing floating volatility patterns of CHIBA BANK and AAC TECHNOLOGHLDGADR.
Diversification Opportunities for CHIBA BANK and AAC TECHNOLOGHLDGADR
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between CHIBA and AAC is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding CHIBA BANK and AAC TECHNOLOGHLDGADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AAC TECHNOLOGHLDGADR and CHIBA BANK 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 CHIBA BANK are associated (or correlated) with AAC TECHNOLOGHLDGADR. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AAC TECHNOLOGHLDGADR has no effect on the direction of CHIBA BANK i.e., CHIBA BANK and AAC TECHNOLOGHLDGADR go up and down completely randomly.
Pair Corralation between CHIBA BANK and AAC TECHNOLOGHLDGADR
Assuming the 90 days trading horizon CHIBA BANK is expected to generate 7.73 times less return on investment than AAC TECHNOLOGHLDGADR. But when comparing it to its historical volatility, CHIBA BANK is 1.89 times less risky than AAC TECHNOLOGHLDGADR. It trades about 0.05 of its potential returns per unit of risk. AAC TECHNOLOGHLDGADR is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 362.00 in AAC TECHNOLOGHLDGADR on October 7, 2024 and sell it today you would earn a total of 96.00 from holding AAC TECHNOLOGHLDGADR or generate 26.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
CHIBA BANK vs. AAC TECHNOLOGHLDGADR
Performance |
Timeline |
CHIBA BANK |
AAC TECHNOLOGHLDGADR |
CHIBA BANK and AAC TECHNOLOGHLDGADR Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CHIBA BANK and AAC TECHNOLOGHLDGADR
The main advantage of trading using opposite CHIBA BANK and AAC TECHNOLOGHLDGADR positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CHIBA BANK position performs unexpectedly, AAC TECHNOLOGHLDGADR 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 AAC TECHNOLOGHLDGADR will offset losses from the drop in AAC TECHNOLOGHLDGADR's long position.CHIBA BANK vs. Salesforce | CHIBA BANK vs. GRIFFIN MINING LTD | CHIBA BANK vs. FIREWEED METALS P | CHIBA BANK vs. ARDAGH METAL PACDL 0001 |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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