Correlation Between Real Good and Treehouse Foods
Can any of the company-specific risk be diversified away by investing in both Real Good and Treehouse Foods 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 Real Good and Treehouse Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Real Good Food and Treehouse Foods, you can compare the effects of market volatilities on Real Good and Treehouse Foods 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 Real Good with a short position of Treehouse Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Real Good and Treehouse Foods.
Diversification Opportunities for Real Good and Treehouse Foods
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Real and Treehouse is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Real Good Food and Treehouse Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Treehouse Foods and Real Good 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 Real Good Food are associated (or correlated) with Treehouse Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Treehouse Foods has no effect on the direction of Real Good i.e., Real Good and Treehouse Foods go up and down completely randomly.
Pair Corralation between Real Good and Treehouse Foods
Considering the 90-day investment horizon Real Good Food is expected to under-perform the Treehouse Foods. In addition to that, Real Good is 1.18 times more volatile than Treehouse Foods. It trades about -0.22 of its total potential returns per unit of risk. Treehouse Foods is currently generating about -0.05 per unit of volatility. If you would invest 3,663 in Treehouse Foods on August 31, 2024 and sell it today you would lose (196.00) from holding Treehouse Foods or give up 5.35% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Real Good Food vs. Treehouse Foods
Performance |
Timeline |
Real Good Food |
Treehouse Foods |
Real Good and Treehouse Foods Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Real Good and Treehouse Foods
The main advantage of trading using opposite Real Good and Treehouse Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Real Good position performs unexpectedly, Treehouse Foods 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 Treehouse Foods will offset losses from the drop in Treehouse Foods' long position.Real Good vs. Seneca Foods Corp | Real Good vs. Central Garden Pet | Real Good vs. Central Garden Pet | Real Good vs. Natures Sunshine Products |
Treehouse Foods vs. Lancaster Colony | Treehouse Foods vs. John B Sanfilippo | Treehouse Foods vs. Seneca Foods Corp | Treehouse Foods vs. Seneca Foods Corp |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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