Correlation Between DATA and CMT

Can any of the company-specific risk be diversified away by investing in both DATA and CMT 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 CMT into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between DATA and CMT, you can compare the effects of market volatilities on DATA and CMT 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 CMT. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATA and CMT.

Diversification Opportunities for DATA and CMT

0.06

Correlation Coefficient

DATA  CMT

Significant diversification

The 3 months correlation between DATA and CMT is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding DATA and CMT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CMT 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 CMT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CMT has no effect on the direction of DATA i.e., DATA and CMT go up and down completely randomly.

Pair Corralation between DATA and CMT

Assuming the 90 days trading horizon DATA is expected to under-perform the CMT. In addition to that, DATA is 2.78 times more volatile than CMT. It trades about -0.27 of its total potential returns per unit of risk. CMT is currently generating about -0.29 per unit of volatility. If you would invest  0.81  in CMT on November 27, 2024 and sell it today you would lose (0.11) from holding CMT or give up 13.99% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

DATA  vs.  CMT

DATA

Risk-Adjusted Performance

Very Weak

Over the last 90 days DATA has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's fundamental indicators remain rather sound which may send shares a bit higher in March 2025. The latest tumult may also be a sign of longer-term up-swing for DATA shareholders.

CMT

Risk-Adjusted Performance

Very Weak

Over the last 90 days CMT has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of latest unsteady performance, the Crypto's basic indicators remain sound and the latest tumult on Wall Street may also be a sign of longer-term gains for CMT shareholders.

Pair Trading with DATA and CMT

The main advantage of trading using opposite DATA and CMT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DATA position performs unexpectedly, CMT 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 CMT will offset losses from the drop in CMT's long position.

The idea behind DATA and CMT 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.

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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.