Correlation Between SENECA FOODS and QBE Insurance
Can any of the company-specific risk be diversified away by investing in both SENECA FOODS and QBE Insurance 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 SENECA FOODS and QBE Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SENECA FOODS A and QBE Insurance Group, you can compare the effects of market volatilities on SENECA FOODS and QBE Insurance 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 SENECA FOODS with a short position of QBE Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of SENECA FOODS and QBE Insurance.
Diversification Opportunities for SENECA FOODS and QBE Insurance
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between SENECA and QBE is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding SENECA FOODS A and QBE Insurance Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on QBE Insurance Group and SENECA FOODS 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 SENECA FOODS A are associated (or correlated) with QBE Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of QBE Insurance Group has no effect on the direction of SENECA FOODS i.e., SENECA FOODS and QBE Insurance go up and down completely randomly.
Pair Corralation between SENECA FOODS and QBE Insurance
Assuming the 90 days trading horizon SENECA FOODS is expected to generate 1.3 times less return on investment than QBE Insurance. In addition to that, SENECA FOODS is 1.9 times more volatile than QBE Insurance Group. It trades about 0.03 of its total potential returns per unit of risk. QBE Insurance Group is currently generating about 0.07 per unit of volatility. If you would invest 731.00 in QBE Insurance Group on September 12, 2024 and sell it today you would earn a total of 449.00 from holding QBE Insurance Group or generate 61.42% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
SENECA FOODS A vs. QBE Insurance Group
Performance |
Timeline |
SENECA FOODS A |
QBE Insurance Group |
SENECA FOODS and QBE Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SENECA FOODS and QBE Insurance
The main advantage of trading using opposite SENECA FOODS and QBE Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SENECA FOODS position performs unexpectedly, QBE Insurance 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 QBE Insurance will offset losses from the drop in QBE Insurance's long position.SENECA FOODS vs. Xenia Hotels Resorts | SENECA FOODS vs. COSTCO WHOLESALE CDR | SENECA FOODS vs. Hyatt Hotels | SENECA FOODS vs. Ross Stores |
QBE Insurance vs. Insurance Australia Group | QBE Insurance vs. Superior Plus Corp | QBE Insurance vs. SIVERS SEMICONDUCTORS AB | QBE Insurance vs. CHINA HUARONG ENERHD 50 |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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