Correlation Between Hanwha Life and ABCO Electronics
Can any of the company-specific risk be diversified away by investing in both Hanwha Life and ABCO Electronics 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 Hanwha Life and ABCO Electronics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hanwha Life Insurance and ABCO Electronics Co, you can compare the effects of market volatilities on Hanwha Life and ABCO Electronics 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 Hanwha Life with a short position of ABCO Electronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hanwha Life and ABCO Electronics.
Diversification Opportunities for Hanwha Life and ABCO Electronics
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hanwha and ABCO is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Hanwha Life Insurance and ABCO Electronics Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ABCO Electronics and Hanwha Life 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 Hanwha Life Insurance are associated (or correlated) with ABCO Electronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ABCO Electronics has no effect on the direction of Hanwha Life i.e., Hanwha Life and ABCO Electronics go up and down completely randomly.
Pair Corralation between Hanwha Life and ABCO Electronics
Assuming the 90 days trading horizon Hanwha Life Insurance is expected to under-perform the ABCO Electronics. But the stock apears to be less risky and, when comparing its historical volatility, Hanwha Life Insurance is 1.46 times less risky than ABCO Electronics. The stock trades about -0.09 of its potential returns per unit of risk. The ABCO Electronics Co is currently generating about 0.32 of returns per unit of risk over similar time horizon. If you would invest 445,000 in ABCO Electronics Co on October 12, 2024 and sell it today you would earn a total of 75,000 from holding ABCO Electronics Co or generate 16.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hanwha Life Insurance vs. ABCO Electronics Co
Performance |
Timeline |
Hanwha Life Insurance |
ABCO Electronics |
Hanwha Life and ABCO Electronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hanwha Life and ABCO Electronics
The main advantage of trading using opposite Hanwha Life and ABCO Electronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hanwha Life position performs unexpectedly, ABCO Electronics 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 ABCO Electronics will offset losses from the drop in ABCO Electronics' long position.Hanwha Life vs. ABCO Electronics Co | Hanwha Life vs. Daejung Chemicals Metals | Hanwha Life vs. Samji Electronics Co | Hanwha Life vs. iNtRON Biotechnology |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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