Correlation Between Samsung Special and DSC Investment
Can any of the company-specific risk be diversified away by investing in both Samsung Special and DSC Investment 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 Samsung Special and DSC Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Special Purpose and DSC Investment, you can compare the effects of market volatilities on Samsung Special and DSC Investment 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 Samsung Special with a short position of DSC Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Special and DSC Investment.
Diversification Opportunities for Samsung Special and DSC Investment
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Samsung and DSC is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Special Purpose and DSC Investment in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DSC Investment and Samsung Special 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 Samsung Special Purpose are associated (or correlated) with DSC Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DSC Investment has no effect on the direction of Samsung Special i.e., Samsung Special and DSC Investment go up and down completely randomly.
Pair Corralation between Samsung Special and DSC Investment
Assuming the 90 days trading horizon Samsung Special Purpose is expected to generate 0.29 times more return on investment than DSC Investment. However, Samsung Special Purpose is 3.4 times less risky than DSC Investment. It trades about -0.17 of its potential returns per unit of risk. DSC Investment is currently generating about -0.06 per unit of risk. If you would invest 219,500 in Samsung Special Purpose on September 3, 2024 and sell it today you would lose (10,000) from holding Samsung Special Purpose or give up 4.56% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Special Purpose vs. DSC Investment
Performance |
Timeline |
Samsung Special Purpose |
DSC Investment |
Samsung Special and DSC Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Special and DSC Investment
The main advantage of trading using opposite Samsung Special and DSC Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Special position performs unexpectedly, DSC Investment 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 DSC Investment will offset losses from the drop in DSC Investment's long position.Samsung Special vs. Daelim Industrial Co | Samsung Special vs. Samhyun Steel Co | Samsung Special vs. Daehan Steel | Samsung Special vs. Hankook Steel 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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