Correlation Between Petronas Chemicals and ViTrox Bhd
Can any of the company-specific risk be diversified away by investing in both Petronas Chemicals and ViTrox Bhd 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 Petronas Chemicals and ViTrox Bhd into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Petronas Chemicals Group and ViTrox Bhd, you can compare the effects of market volatilities on Petronas Chemicals and ViTrox Bhd 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 Petronas Chemicals with a short position of ViTrox Bhd. Check out your portfolio center. Please also check ongoing floating volatility patterns of Petronas Chemicals and ViTrox Bhd.
Diversification Opportunities for Petronas Chemicals and ViTrox Bhd
-0.48 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Petronas and ViTrox is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Petronas Chemicals Group and ViTrox Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ViTrox Bhd and Petronas Chemicals 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 Petronas Chemicals Group are associated (or correlated) with ViTrox Bhd. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ViTrox Bhd has no effect on the direction of Petronas Chemicals i.e., Petronas Chemicals and ViTrox Bhd go up and down completely randomly.
Pair Corralation between Petronas Chemicals and ViTrox Bhd
Assuming the 90 days trading horizon Petronas Chemicals Group is expected to under-perform the ViTrox Bhd. But the stock apears to be less risky and, when comparing its historical volatility, Petronas Chemicals Group is 1.18 times less risky than ViTrox Bhd. The stock trades about -0.04 of its potential returns per unit of risk. The ViTrox Bhd is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 335.00 in ViTrox Bhd on September 12, 2024 and sell it today you would earn a total of 22.00 from holding ViTrox Bhd or generate 6.57% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Petronas Chemicals Group vs. ViTrox Bhd
Performance |
Timeline |
Petronas Chemicals |
ViTrox Bhd |
Petronas Chemicals and ViTrox Bhd Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Petronas Chemicals and ViTrox Bhd
The main advantage of trading using opposite Petronas Chemicals and ViTrox Bhd positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Petronas Chemicals position performs unexpectedly, ViTrox Bhd 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 ViTrox Bhd will offset losses from the drop in ViTrox Bhd's long position.Petronas Chemicals vs. Lotte Chemical Titan | Petronas Chemicals vs. Ancom Berhad | Petronas Chemicals vs. Techbond Group Bhd |
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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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