Correlation Between DATA and MONA

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

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

Diversification Opportunities for DATA and MONA

0.47

Correlation Coefficient

DATA  MONA

Very weak diversification

The 3 months correlation between DATA and MONA is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding DATA and MONA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MONA 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 MONA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MONA has no effect on the direction of DATA i.e., DATA and MONA go up and down completely randomly.

Pair Corralation between DATA and MONA

Assuming the 90 days trading horizon DATA is expected to generate 1.21 times more return on investment than MONA. However, DATA is 1.21 times more volatile than MONA. It trades about 0.11 of its potential returns per unit of risk. MONA is currently generating about 0.08 per unit of risk. 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	Weak
Accuracy	100.0%
Values	Daily Returns

DATA  vs.  MONA

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.

MONA

Risk-Adjusted Performance

6 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in MONA are ranked lower than 6 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, MONA exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with DATA and MONA

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

The idea behind DATA and MONA 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 Valuation module to check real value of public entities based on technical and fundamental data.