Correlation Between DAX Index and SENECA FOODS-A

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

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

Diversification Opportunities for DAX Index and SENECA FOODS-A

0.48

Correlation Coefficient

DAX Index  SENECA FOODS-A

Very weak diversification

The 3 months correlation between DAX and SENECA is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and SENECA FOODS A in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SENECA FOODS A and DAX Index 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 DAX Index are associated (or correlated) with SENECA FOODS-A. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SENECA FOODS A has no effect on the direction of DAX Index i.e., DAX Index and SENECA FOODS-A go up and down completely randomly.

Pair Corralation between DAX Index and SENECA FOODS-A

Assuming the 90 days trading horizon DAX Index is expected to generate 3.63 times less return on investment than SENECA FOODS-A. But when comparing it to its historical volatility, DAX Index is 3.29 times less risky than SENECA FOODS-A. It trades about 0.12 of its potential returns per unit of risk. SENECA FOODS A is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest  5,250  in SENECA FOODS A on September 3, 2024 and sell it today you would earn a total of  1,200  from holding SENECA FOODS A or generate 22.86% return on investment over 90 days.

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

DAX Index  vs.  SENECA FOODS A

Pair Trading with DAX Index and SENECA FOODS-A

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

The idea behind DAX Index and SENECA FOODS A 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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.