Correlation Between Seoam Machinery and BNK Financial
Can any of the company-specific risk be diversified away by investing in both Seoam Machinery and BNK Financial 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 Seoam Machinery and BNK Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Seoam Machinery Industry and BNK Financial Group, you can compare the effects of market volatilities on Seoam Machinery and BNK Financial 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 Seoam Machinery with a short position of BNK Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seoam Machinery and BNK Financial.
Diversification Opportunities for Seoam Machinery and BNK Financial
-0.3 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Seoam and BNK is -0.3. Overlapping area represents the amount of risk that can be diversified away by holding Seoam Machinery Industry and BNK Financial Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BNK Financial Group and Seoam Machinery 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 Seoam Machinery Industry are associated (or correlated) with BNK Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BNK Financial Group has no effect on the direction of Seoam Machinery i.e., Seoam Machinery and BNK Financial go up and down completely randomly.
Pair Corralation between Seoam Machinery and BNK Financial
Assuming the 90 days trading horizon Seoam Machinery is expected to generate 1.56 times less return on investment than BNK Financial. But when comparing it to its historical volatility, Seoam Machinery Industry is 1.07 times less risky than BNK Financial. It trades about 0.26 of its potential returns per unit of risk. BNK Financial Group is currently generating about 0.38 of returns per unit of risk over similar time horizon. If you would invest 1,059,000 in BNK Financial Group on October 26, 2024 and sell it today you would earn a total of 132,000 from holding BNK Financial Group or generate 12.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.0% |
Values | Daily Returns |
Seoam Machinery Industry vs. BNK Financial Group
Performance |
Timeline |
Seoam Machinery Industry |
BNK Financial Group |
Seoam Machinery and BNK Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Seoam Machinery and BNK Financial
The main advantage of trading using opposite Seoam Machinery and BNK Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seoam Machinery position performs unexpectedly, BNK Financial 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 BNK Financial will offset losses from the drop in BNK Financial's long position.Seoam Machinery vs. LEENO Industrial | Seoam Machinery vs. DRB Industrial Co | Seoam Machinery vs. Guyoung Technology Co | Seoam Machinery vs. Automobile Pc |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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