Correlation Between CMT and Phala Network

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

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

Diversification Opportunities for CMT and Phala Network

0.84

Correlation Coefficient

CMT  Phala Network

Very poor diversification

The 3 months correlation between CMT and Phala is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding CMT and Phala Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Phala Network and CMT 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 CMT are associated (or correlated) with Phala Network. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Phala Network has no effect on the direction of CMT i.e., CMT and Phala Network go up and down completely randomly.

Pair Corralation between CMT and Phala Network

Assuming the 90 days trading horizon CMT is expected to generate 0.35 times more return on investment than Phala Network. However, CMT is 2.88 times less risky than Phala Network. It trades about -0.05 of its potential returns per unit of risk. Phala Network is currently generating about -0.15 per unit of risk. If you would invest  0.52  in CMT on January 30, 2024 and sell it today you would lose (0.02) from holding CMT or give up 3.09% of portfolio value over 90 days.

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

CMT  vs.  Phala Network

CMT

Risk-Adjusted Performance

15 of 100

Good

Compared to the overall equity markets, risk-adjusted returns on investments in CMT are ranked lower than 15 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, CMT exhibited solid returns over the last few months and may actually be approaching a breakup point.

Phala Network

Risk-Adjusted Performance

13 of 100

Good

Compared to the overall equity markets, risk-adjusted returns on investments in Phala Network are ranked lower than 13 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, Phala Network exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with CMT and Phala Network

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

The idea behind CMT and Phala Network 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.