Correlation Between MNW and AGVC

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

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

Diversification Opportunities for MNW and AGVC

0.14

Correlation Coefficient

MNW  AGVC

Average diversification

The 3 months correlation between MNW and AGVC is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding MNW and AGVC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AGVC and MNW 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 MNW are associated (or correlated) with AGVC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AGVC has no effect on the direction of MNW i.e., MNW and AGVC go up and down completely randomly.

Pair Corralation between MNW and AGVC

If you would invest  40.00  in MNW on August 30, 2024 and sell it today you would earn a total of  0.00  from holding MNW or generate 0.0% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	1.56%
Values	Daily Returns

MNW  vs.  AGVC

MNW

Risk-Adjusted Performance

8 of 100

OK

Compared to the overall equity markets, risk-adjusted returns on investments in MNW are ranked lower than 8 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, MNW exhibited solid returns over the last few months and may actually be approaching a breakup point.

AGVC

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days AGVC has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental indicators, AGVC is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

Pair Trading with MNW and AGVC

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

The idea behind MNW and AGVC 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.