Correlation Between EM and GAIA

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

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

Diversification Opportunities for EM and GAIA

0.0

Correlation Coefficient

EM  GAIA

Pay attention - limited upside

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

Pair Corralation between EM and GAIA

If you would invest  0.01  in EM on September 1, 2024 and sell it today you would earn a total of  0.00  from holding EM 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

EM  vs.  GAIA

EM

Risk-Adjusted Performance

0 of 100

Very Weak

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

GAIA

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days GAIA 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 December 2024. The latest tumult may also be a sign of longer-term up-swing for GAIA shareholders.

Pair Trading with EM and GAIA

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

The idea behind EM and GAIA 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.