Correlation Between KINGBOARD CHEMICAL and ITALIAN WINE
Can any of the company-specific risk be diversified away by investing in both KINGBOARD CHEMICAL and ITALIAN WINE 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 KINGBOARD CHEMICAL and ITALIAN WINE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KINGBOARD CHEMICAL and ITALIAN WINE BRANDS, you can compare the effects of market volatilities on KINGBOARD CHEMICAL and ITALIAN WINE 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 KINGBOARD CHEMICAL with a short position of ITALIAN WINE. Check out your portfolio center. Please also check ongoing floating volatility patterns of KINGBOARD CHEMICAL and ITALIAN WINE.
Diversification Opportunities for KINGBOARD CHEMICAL and ITALIAN WINE
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between KINGBOARD and ITALIAN is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding KINGBOARD CHEMICAL and ITALIAN WINE BRANDS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ITALIAN WINE BRANDS and KINGBOARD CHEMICAL 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 KINGBOARD CHEMICAL are associated (or correlated) with ITALIAN WINE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ITALIAN WINE BRANDS has no effect on the direction of KINGBOARD CHEMICAL i.e., KINGBOARD CHEMICAL and ITALIAN WINE go up and down completely randomly.
Pair Corralation between KINGBOARD CHEMICAL and ITALIAN WINE
Assuming the 90 days trading horizon KINGBOARD CHEMICAL is expected to generate 1.83 times more return on investment than ITALIAN WINE. However, KINGBOARD CHEMICAL is 1.83 times more volatile than ITALIAN WINE BRANDS. It trades about 0.05 of its potential returns per unit of risk. ITALIAN WINE BRANDS is currently generating about -0.01 per unit of risk. If you would invest 131.00 in KINGBOARD CHEMICAL on October 4, 2024 and sell it today you would earn a total of 103.00 from holding KINGBOARD CHEMICAL or generate 78.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
KINGBOARD CHEMICAL vs. ITALIAN WINE BRANDS
Performance |
Timeline |
KINGBOARD CHEMICAL |
ITALIAN WINE BRANDS |
KINGBOARD CHEMICAL and ITALIAN WINE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KINGBOARD CHEMICAL and ITALIAN WINE
The main advantage of trading using opposite KINGBOARD CHEMICAL and ITALIAN WINE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KINGBOARD CHEMICAL position performs unexpectedly, ITALIAN WINE 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 ITALIAN WINE will offset losses from the drop in ITALIAN WINE's long position.KINGBOARD CHEMICAL vs. Shenandoah Telecommunications | KINGBOARD CHEMICAL vs. GRIFFIN MINING LTD | KINGBOARD CHEMICAL vs. MAROC TELECOM | KINGBOARD CHEMICAL vs. Cogent Communications Holdings |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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