Correlation Between Bell Food and InterContinental
Can any of the company-specific risk be diversified away by investing in both Bell Food and InterContinental 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 Bell Food and InterContinental into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bell Food Group and InterContinental Hotels Group, you can compare the effects of market volatilities on Bell Food and InterContinental 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 Bell Food with a short position of InterContinental. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bell Food and InterContinental.
Diversification Opportunities for Bell Food and InterContinental
0.05 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Bell and InterContinental is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding Bell Food Group and InterContinental Hotels Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on InterContinental Hotels and Bell Food 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 Bell Food Group are associated (or correlated) with InterContinental. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of InterContinental Hotels has no effect on the direction of Bell Food i.e., Bell Food and InterContinental go up and down completely randomly.
Pair Corralation between Bell Food and InterContinental
Assuming the 90 days trading horizon Bell Food is expected to generate 9.78 times less return on investment than InterContinental. But when comparing it to its historical volatility, Bell Food Group is 1.49 times less risky than InterContinental. It trades about 0.03 of its potential returns per unit of risk. InterContinental Hotels Group is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 937,400 in InterContinental Hotels Group on September 12, 2024 and sell it today you would earn a total of 38,400 from holding InterContinental Hotels Group or generate 4.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bell Food Group vs. InterContinental Hotels Group
Performance |
| Timeline |
| Bell Food Group |
| InterContinental Hotels |
Bell Food and InterContinental Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bell Food and InterContinental
The main advantage of trading using opposite Bell Food and InterContinental positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bell Food position performs unexpectedly, InterContinental 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 InterContinental will offset losses from the drop in InterContinental's long position.| Bell Food vs. Hong Kong Land | Bell Food vs. Neometals | Bell Food vs. Coor Service Management | Bell Food vs. Fidelity Sustainable USD |
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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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