Correlation Between Dai and UMA

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Can any of the company-specific risk be diversified away by investing in both Dai and UMA 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 Dai and UMA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dai and UMA, you can compare the effects of market volatilities on Dai and UMA 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 Dai with a short position of UMA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dai and UMA.

Diversification Opportunities for Dai and UMA

0.0
  Correlation Coefficient
 Dai
 UMA

Pay attention - limited upside

The 3 months correlation between Dai and UMA is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Dai and UMA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UMA and Dai 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 Dai are associated (or correlated) with UMA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UMA has no effect on the direction of Dai i.e., Dai and UMA go up and down completely randomly.

Pair Corralation between Dai and UMA

If you would invest  100.00  in Dai on December 28, 2024 and sell it today you would earn a total of  0.00  from holding Dai or generate 0.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

Dai  vs.  UMA

 Performance 
       Timeline  
Dai 

Risk-Adjusted Performance

Very Weak

 
Weak
 
Strong
Over the last 90 days Dai has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound forward indicators, Dai is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.
UMA 

Risk-Adjusted Performance

Very Weak

 
Weak
 
Strong
Over the last 90 days UMA 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 basic indicators remain rather sound which may send shares a bit higher in April 2025. The latest tumult may also be a sign of longer-term up-swing for UMA shareholders.

Dai and UMA Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dai and UMA

The main advantage of trading using opposite Dai and UMA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dai position performs unexpectedly, UMA 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 UMA will offset losses from the drop in UMA's long position.
The idea behind Dai and UMA 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.

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