Correlation Between POCC and DATA

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

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

Diversification Opportunities for POCC and DATA

0.53

Correlation Coefficient

POCC  DATA

Very weak diversification

The 3 months correlation between POCC and DATA is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding POCC and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and POCC 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 POCC 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 POCC i.e., POCC and DATA go up and down completely randomly.

Pair Corralation between POCC and DATA

Assuming the 90 days trading horizon POCC is expected to generate 0.7 times more return on investment than DATA. However, POCC is 1.42 times less risky than DATA. It trades about 0.18 of its potential returns per unit of risk. DATA is currently generating about 0.1 per unit of risk. If you would invest  0.01  in POCC on September 1, 2024 and sell it today you would earn a total of  0.01  from holding POCC or generate 48.76% return on investment over 90 days.

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

POCC  vs.  DATA

POCC

Risk-Adjusted Performance

14 of 100

Good

Compared to the overall equity markets, risk-adjusted returns on investments in POCC are ranked lower than 14 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, POCC exhibited solid returns over the last few months and may actually be approaching a breakup point.

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 POCC and DATA

The main advantage of trading using opposite POCC and DATA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POCC 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 POCC 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 Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.