Correlation Between DATA and DigiByte
Can any of the company-specific risk be diversified away by investing in both DATA and DigiByte 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 DATA and DigiByte into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DATA and DigiByte, you can compare the effects of market volatilities on DATA and DigiByte 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 DATA with a short position of DigiByte. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATA and DigiByte.
Diversification Opportunities for DATA and DigiByte
Poor diversification
The 3 months correlation between DATA and DigiByte is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding DATA and DigiByte in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DigiByte and DATA 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 DATA are associated (or correlated) with DigiByte. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DigiByte has no effect on the direction of DATA i.e., DATA and DigiByte go up and down completely randomly.
Pair Corralation between DATA and DigiByte
Assuming the 90 days trading horizon DATA is expected to generate 1.33 times more return on investment than DigiByte. However, DATA is 1.33 times more volatile than DigiByte. It trades about -0.04 of its potential returns per unit of risk. DigiByte is currently generating about -0.26 per unit of risk. If you would invest 7.17 in DATA on January 30, 2024 and sell it today you would lose (0.91) from holding DATA or give up 12.69% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
DATA vs. DigiByte
Performance |
Timeline |
DATA |
DigiByte |
DATA and DigiByte Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with DATA and DigiByte
The main advantage of trading using opposite DATA and DigiByte positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DATA position performs unexpectedly, DigiByte 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 DigiByte will offset losses from the drop in DigiByte's long position.The idea behind DATA and DigiByte pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.
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