Correlation Between Tether and DATA

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

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

Diversification Opportunities for Tether and DATA

0.0

Correlation Coefficient

Tether  DATA

Pay attention - limited upside

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

Pair Corralation between Tether and DATA

If you would invest  3.81  in DATA on September 1, 2024 and sell it today you would earn a total of  1.17  from holding DATA or generate 30.71% return on investment over 90 days.

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

Tether  vs.  DATA

Tether

Risk-Adjusted Performance

0 of 100

Very Weak

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

DATA

Risk-Adjusted Performance

8 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in DATA are ranked lower than 8 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, DATA exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with Tether and DATA

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

The idea behind Tether and DATA 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.