Correlation Between NYSE Composite and Farmers Merchants

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

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

Diversification Opportunities for NYSE Composite and Farmers Merchants

0.08

Correlation Coefficient

NYSE Composite  Farmers Merchants

Significant diversification

The 3 months correlation between NYSE and Farmers is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Farmers Merchants Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Farmers Merchants Bancorp and NYSE Composite 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 NYSE Composite are associated (or correlated) with Farmers Merchants. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Farmers Merchants Bancorp has no effect on the direction of NYSE Composite i.e., NYSE Composite and Farmers Merchants go up and down completely randomly.

Pair Corralation between NYSE Composite and Farmers Merchants

Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.39 times less return on investment than Farmers Merchants. But when comparing it to its historical volatility, NYSE Composite is 4.17 times less risky than Farmers Merchants. It trades about 0.09 of its potential returns per unit of risk. Farmers Merchants Bancorp is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest  2,074  in Farmers Merchants Bancorp on December 4, 2024 and sell it today you would earn a total of  469.00  from holding Farmers Merchants Bancorp or generate 22.61% return on investment over 90 days.

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

NYSE Composite  vs.  Farmers Merchants Bancorp

Pair Trading with NYSE Composite and Farmers Merchants

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

The idea behind NYSE Composite and Farmers Merchants Bancorp 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.