Correlation Between Digital Power and Mercury
Can any of the company-specific risk be diversified away by investing in both Digital Power and Mercury 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 Digital Power and Mercury into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Digital Power Communications and Mercury, you can compare the effects of market volatilities on Digital Power and Mercury 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 Digital Power with a short position of Mercury. Check out your portfolio center. Please also check ongoing floating volatility patterns of Digital Power and Mercury.
Diversification Opportunities for Digital Power and Mercury
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Digital and Mercury is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding Digital Power Communications and Mercury in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mercury and Digital Power 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 Digital Power Communications are associated (or correlated) with Mercury. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mercury has no effect on the direction of Digital Power i.e., Digital Power and Mercury go up and down completely randomly.
Pair Corralation between Digital Power and Mercury
Assuming the 90 days trading horizon Digital Power Communications is expected to generate 0.69 times more return on investment than Mercury. However, Digital Power Communications is 1.46 times less risky than Mercury. It trades about 0.06 of its potential returns per unit of risk. Mercury is currently generating about -0.02 per unit of risk. If you would invest 520,582 in Digital Power Communications on September 12, 2024 and sell it today you would earn a total of 331,418 from holding Digital Power Communications or generate 63.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 99.79% |
| Values | Daily Returns |
Digital Power Communications vs. Mercury
Performance |
| Timeline |
| Digital Power Commun |
| Mercury |
Digital Power and Mercury Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Digital Power and Mercury
The main advantage of trading using opposite Digital Power and Mercury positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Digital Power position performs unexpectedly, Mercury 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 Mercury will offset losses from the drop in Mercury's long position.| Digital Power vs. Dongwon Metal Co | Digital Power vs. Samsung Publishing Co | Digital Power vs. Miwon Chemicals Co | Digital Power vs. PJ Metal Co |
| Mercury vs. Eagon Industrial Co | Mercury vs. CG Hi Tech | Mercury vs. Daishin Information Communications | Mercury vs. Nice Information Telecommunication |
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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