Correlation Between Big Time and DATA

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

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

Diversification Opportunities for Big Time and DATA

-0.1

Correlation Coefficient

Big Time  DATA

Good diversification

The 3 months correlation between Big and DATA is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Big Time and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and Big Time 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 Big Time 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 Big Time i.e., Big Time and DATA go up and down completely randomly.

Pair Corralation between Big Time and DATA

Assuming the 90 days trading horizon Big Time is expected to generate 1.94 times more return on investment than DATA. However, Big Time is 1.94 times more volatile than DATA. It trades about 0.17 of its potential returns per unit of risk. DATA is currently generating about 0.11 per unit of risk. If you would invest  6.96  in Big Time on August 30, 2024 and sell it today you would earn a total of  9.04  from holding Big Time or generate 129.89% return on investment over 90 days.

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

Big Time  vs.  DATA

Big Time

Risk-Adjusted Performance

13 of 100

Good

Compared to the overall equity markets, risk-adjusted returns on investments in Big Time are ranked lower than 13 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, Big Time 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 Big Time and DATA

The main advantage of trading using opposite Big Time and DATA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Big Time 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 Big Time 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.