Correlation Between BLZ and DATA

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

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

Diversification Opportunities for BLZ and DATA

0.76

Correlation Coefficient

BLZ  DATA

Poor diversification

The 3 months correlation between BLZ and DATA is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding BLZ and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and BLZ 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 BLZ 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 BLZ i.e., BLZ and DATA go up and down completely randomly.

Pair Corralation between BLZ and DATA

Assuming the 90 days trading horizon BLZ is expected to generate 1.76 times less return on investment than DATA. In addition to that, BLZ is 1.2 times more volatile than DATA. It trades about 0.05 of its total potential returns per unit of risk. DATA is currently generating about 0.11 per unit of volatility. If you would invest  3.44  in DATA on August 30, 2024 and sell it today you would earn a total of  1.10  from holding DATA or generate 31.98% return on investment over 90 days.

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

BLZ  vs.  DATA

BLZ

Risk-Adjusted Performance

3 of 100

Insignificant

Compared to the overall equity markets, risk-adjusted returns on investments in BLZ are ranked lower than 3 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, BLZ exhibited solid returns over the last few months and may actually be approaching a breakup point.

DATA

Risk-Adjusted Performance

8 of 100

OK

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 BLZ and DATA

The main advantage of trading using opposite BLZ and DATA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BLZ 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 BLZ 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.

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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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.