Correlation Between DATA and PAY
Can any of the company-specific risk be diversified away by investing in both DATA and PAY 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 PAY into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DATA and PAY, you can compare the effects of market volatilities on DATA and PAY 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 PAY. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATA and PAY.
Diversification Opportunities for DATA and PAY
Weak diversification
The 3 months correlation between DATA and PAY is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding DATA and PAY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PAY 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 PAY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PAY has no effect on the direction of DATA i.e., DATA and PAY go up and down completely randomly.
Pair Corralation between DATA and PAY
Assuming the 90 days trading horizon DATA is expected to generate 0.77 times more return on investment than PAY. However, DATA is 1.3 times less risky than PAY. It trades about 0.23 of its potential returns per unit of risk. PAY is currently generating about 0.14 per unit of risk. If you would invest 3.32 in DATA on August 25, 2024 and sell it today you would earn a total of 0.77 from holding DATA or generate 23.19% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
DATA vs. PAY
Performance |
| Timeline |
| DATA |
| PAY |
DATA and PAY Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DATA and PAY
The main advantage of trading using opposite DATA and PAY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DATA position performs unexpectedly, PAY 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 PAY will offset losses from the drop in PAY's long position.The idea behind DATA and PAY 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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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