Correlation Between DATA and WGRT

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

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

Diversification Opportunities for DATA and WGRT

0.19

Correlation Coefficient

DATA  WGRT

Average diversification

The 3 months correlation between DATA and WGRT is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding DATA and WGRT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on WGRT and DATA 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 DATA are associated (or correlated) with WGRT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of WGRT has no effect on the direction of DATA i.e., DATA and WGRT go up and down completely randomly.

Pair Corralation between DATA and WGRT

Assuming the 90 days trading horizon DATA is expected to under-perform the WGRT. In addition to that, DATA is 4.37 times more volatile than WGRT. It trades about -0.09 of its total potential returns per unit of risk. WGRT is currently generating about -0.08 per unit of volatility. If you would invest  1.37  in WGRT on February 6, 2024 and sell it today you would lose (0.05) from holding WGRT or give up 3.65% of portfolio value over 90 days.

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

DATA  vs.  WGRT

DATA

Risk-Adjusted Performance

5 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in DATA are ranked lower than 5 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, DATA exhibited solid returns over the last few months and may actually be approaching a breakup point.

WGRT

Risk-Adjusted Performance

22 of 100

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in WGRT are ranked lower than 22 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, WGRT exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with DATA and WGRT

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

The idea behind DATA and WGRT 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.