Correlation Between Dai and Stellar

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

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

Diversification Opportunities for Dai and Stellar

0.0

Correlation Coefficient

Dai  Stellar

Pay attention - limited upside

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

Pair Corralation between Dai and Stellar

If you would invest  100.00  in Dai on December 29, 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 Period	3 Months [change]
Direction	Flat
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

Dai  vs.  Stellar

Dai

Risk-Adjusted Performance

Very Weak

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.

Stellar

Risk-Adjusted Performance

Very Weak

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

Pair Trading with Dai and Stellar

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

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