Correlation Between Busan Industrial and PNC Technologies
Can any of the company-specific risk be diversified away by investing in both Busan Industrial and PNC Technologies 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 Busan Industrial and PNC Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Busan Industrial Co and PNC Technologies co, you can compare the effects of market volatilities on Busan Industrial and PNC Technologies 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 Busan Industrial with a short position of PNC Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Busan Industrial and PNC Technologies.
Diversification Opportunities for Busan Industrial and PNC Technologies
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Busan and PNC is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding Busan Industrial Co and PNC Technologies co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PNC Technologies and Busan Industrial 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 Busan Industrial Co are associated (or correlated) with PNC Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PNC Technologies has no effect on the direction of Busan Industrial i.e., Busan Industrial and PNC Technologies go up and down completely randomly.
Pair Corralation between Busan Industrial and PNC Technologies
Assuming the 90 days trading horizon Busan Industrial Co is expected to generate 1.82 times more return on investment than PNC Technologies. However, Busan Industrial is 1.82 times more volatile than PNC Technologies co. It trades about -0.04 of its potential returns per unit of risk. PNC Technologies co is currently generating about -0.13 per unit of risk. If you would invest 7,450,000 in Busan Industrial Co on December 30, 2024 and sell it today you would lose (630,000) from holding Busan Industrial Co or give up 8.46% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Busan Industrial Co vs. PNC Technologies co
Performance |
Timeline |
Busan Industrial |
PNC Technologies |
Busan Industrial and PNC Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Busan Industrial and PNC Technologies
The main advantage of trading using opposite Busan Industrial and PNC Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Busan Industrial position performs unexpectedly, PNC Technologies 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 PNC Technologies will offset losses from the drop in PNC Technologies' long position.Busan Industrial vs. PJ Electronics Co | Busan Industrial vs. Digital Power Communications | Busan Industrial vs. Jahwa Electronics Co | Busan Industrial vs. Vissem Electronics Co |
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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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