Correlation Between SENECA FOODS-A and SANOK RUBBER
Can any of the company-specific risk be diversified away by investing in both SENECA FOODS-A and SANOK RUBBER 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-A and SANOK RUBBER 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 SANOK RUBBER ZY, you can compare the effects of market volatilities on SENECA FOODS-A and SANOK RUBBER 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-A with a short position of SANOK RUBBER. Check out your portfolio center. Please also check ongoing floating volatility patterns of SENECA FOODS-A and SANOK RUBBER.
Diversification Opportunities for SENECA FOODS-A and SANOK RUBBER
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between SENECA and SANOK is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding SENECA FOODS A and SANOK RUBBER ZY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SANOK RUBBER ZY and SENECA FOODS-A 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 SANOK RUBBER. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SANOK RUBBER ZY has no effect on the direction of SENECA FOODS-A i.e., SENECA FOODS-A and SANOK RUBBER go up and down completely randomly.
Pair Corralation between SENECA FOODS-A and SANOK RUBBER
Assuming the 90 days trading horizon SENECA FOODS A is expected to generate 0.82 times more return on investment than SANOK RUBBER. However, SENECA FOODS A is 1.22 times less risky than SANOK RUBBER. It trades about 0.09 of its potential returns per unit of risk. SANOK RUBBER ZY is currently generating about 0.06 per unit of risk. If you would invest 5,050 in SENECA FOODS A on October 12, 2024 and sell it today you would earn a total of 2,000 from holding SENECA FOODS A or generate 39.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
SENECA FOODS A vs. SANOK RUBBER ZY
Performance |
| Timeline |
| SENECA FOODS A |
| SANOK RUBBER ZY |
SENECA FOODS-A and SANOK RUBBER Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SENECA FOODS-A and SANOK RUBBER
The main advantage of trading using opposite SENECA FOODS-A and SANOK RUBBER positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SENECA FOODS-A position performs unexpectedly, SANOK RUBBER 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 SANOK RUBBER will offset losses from the drop in SANOK RUBBER's long position.| SENECA FOODS-A vs. Commonwealth Bank of | SENECA FOODS-A vs. Perdoceo Education | SENECA FOODS-A vs. Major Drilling Group | SENECA FOODS-A vs. American Public Education |
| SANOK RUBBER vs. Jacquet Metal Service | SANOK RUBBER vs. Lendlease Group | SANOK RUBBER vs. Perseus Mining Limited | SANOK RUBBER vs. Gladstone 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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