Correlation Between Kaman and Moog

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

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

Diversification Opportunities for Kaman and Moog

0.66

Correlation Coefficient

Kaman  Moog

Poor diversification

The 3 months correlation between Kaman and Moog is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Kaman and Moog Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Moog Inc and Kaman 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 Kaman are associated (or correlated) with Moog. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Moog Inc has no effect on the direction of Kaman i.e., Kaman and Moog go up and down completely randomly.

Pair Corralation between Kaman and Moog

If you would invest  19,715  in Moog Inc on August 30, 2024 and sell it today you would earn a total of  2,283  from holding Moog Inc or generate 11.58% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	1.59%
Values	Daily Returns

Kaman  vs.  Moog Inc

Kaman

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days Kaman has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of very healthy primary indicators, Kaman is not utilizing all of its potentials. The recent stock price disarray, may contribute to short-term losses for the investors.

Moog Inc

Risk-Adjusted Performance

6 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in Moog Inc are ranked lower than 6 (%) of all global equities and portfolios over the last 90 days. Despite somewhat weak basic indicators, Moog may actually be approaching a critical reversion point that can send shares even higher in December 2024.

Pair Trading with Kaman and Moog

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

The idea behind Kaman and Moog Inc 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.

Check out your portfolio center.

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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.