Correlation Between Whitehaven Coal and Kkr Credit
Can any of the company-specific risk be diversified away by investing in both Whitehaven Coal and Kkr Credit 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 Whitehaven Coal and Kkr Credit into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Whitehaven Coal and Kkr Credit Income, you can compare the effects of market volatilities on Whitehaven Coal and Kkr Credit 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 Whitehaven Coal with a short position of Kkr Credit. Check out your portfolio center. Please also check ongoing floating volatility patterns of Whitehaven Coal and Kkr Credit.
Diversification Opportunities for Whitehaven Coal and Kkr Credit
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Whitehaven and Kkr is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Whitehaven Coal and Kkr Credit Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kkr Credit Income and Whitehaven Coal 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 Whitehaven Coal are associated (or correlated) with Kkr Credit. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kkr Credit Income has no effect on the direction of Whitehaven Coal i.e., Whitehaven Coal and Kkr Credit go up and down completely randomly.
Pair Corralation between Whitehaven Coal and Kkr Credit
Assuming the 90 days trading horizon Whitehaven Coal is expected to under-perform the Kkr Credit. In addition to that, Whitehaven Coal is 2.08 times more volatile than Kkr Credit Income. It trades about -0.09 of its total potential returns per unit of risk. Kkr Credit Income is currently generating about -0.02 per unit of volatility. If you would invest 232.00 in Kkr Credit Income on September 1, 2024 and sell it today you would lose (1.00) from holding Kkr Credit Income or give up 0.43% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Whitehaven Coal vs. Kkr Credit Income
Performance |
| Timeline |
| Whitehaven Coal |
| Kkr Credit Income |
Whitehaven Coal and Kkr Credit Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Whitehaven Coal and Kkr Credit
The main advantage of trading using opposite Whitehaven Coal and Kkr Credit positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Whitehaven Coal position performs unexpectedly, Kkr Credit 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 Kkr Credit will offset losses from the drop in Kkr Credit's long position.| Whitehaven Coal vs. Kkr Credit Income | Whitehaven Coal vs. Queste Communications | Whitehaven Coal vs. Bank of Queensland | Whitehaven Coal vs. Magellan Financial Group |
| Kkr Credit vs. Iron Road | Kkr Credit vs. Phoslock Environmental Technologies | Kkr Credit vs. Green Technology Metals | Kkr Credit vs. Legacy Iron Ore |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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