Correlation Between Industrial Bank and Woorim Machinery
Can any of the company-specific risk be diversified away by investing in both Industrial Bank and Woorim Machinery 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 Industrial Bank and Woorim Machinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Industrial Bank and Woorim Machinery Co, you can compare the effects of market volatilities on Industrial Bank and Woorim Machinery 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 Industrial Bank with a short position of Woorim Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of Industrial Bank and Woorim Machinery.
Diversification Opportunities for Industrial Bank and Woorim Machinery
-0.36 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Industrial and Woorim is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding Industrial Bank and Woorim Machinery Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Woorim Machinery and Industrial 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 Industrial Bank are associated (or correlated) with Woorim Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Woorim Machinery has no effect on the direction of Industrial Bank i.e., Industrial Bank and Woorim Machinery go up and down completely randomly.
Pair Corralation between Industrial Bank and Woorim Machinery
Assuming the 90 days trading horizon Industrial Bank is expected to generate 0.26 times more return on investment than Woorim Machinery. However, Industrial Bank is 3.87 times less risky than Woorim Machinery. It trades about 0.26 of its potential returns per unit of risk. Woorim Machinery Co is currently generating about -0.03 per unit of risk. If you would invest 1,410,000 in Industrial Bank on September 1, 2024 and sell it today you would earn a total of 78,000 from holding Industrial Bank or generate 5.53% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Industrial Bank vs. Woorim Machinery Co
Performance |
| Timeline |
| Industrial Bank |
| Woorim Machinery |
Industrial Bank and Woorim Machinery Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Industrial Bank and Woorim Machinery
The main advantage of trading using opposite Industrial Bank and Woorim Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Industrial Bank position performs unexpectedly, Woorim Machinery 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 Woorim Machinery will offset losses from the drop in Woorim Machinery's long position.| Industrial Bank vs. Samsung Electronics Co | Industrial Bank vs. Samsung Electronics Co | Industrial Bank vs. KB Financial Group | Industrial Bank vs. Shinhan Financial Group |
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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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