Correlation Between Wahana Ottomitra and Mandala Multifinance
Can any of the company-specific risk be diversified away by investing in both Wahana Ottomitra and Mandala Multifinance 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 Wahana Ottomitra and Mandala Multifinance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Wahana Ottomitra Multiartha and Mandala Multifinance Tbk, you can compare the effects of market volatilities on Wahana Ottomitra and Mandala Multifinance 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 Wahana Ottomitra with a short position of Mandala Multifinance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Wahana Ottomitra and Mandala Multifinance.
Diversification Opportunities for Wahana Ottomitra and Mandala Multifinance
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Wahana and Mandala is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding Wahana Ottomitra Multiartha and Mandala Multifinance Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mandala Multifinance Tbk and Wahana Ottomitra 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 Wahana Ottomitra Multiartha are associated (or correlated) with Mandala Multifinance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mandala Multifinance Tbk has no effect on the direction of Wahana Ottomitra i.e., Wahana Ottomitra and Mandala Multifinance go up and down completely randomly.
Pair Corralation between Wahana Ottomitra and Mandala Multifinance
If you would invest 34,800 in Wahana Ottomitra Multiartha on September 13, 2024 and sell it today you would earn a total of 400.00 from holding Wahana Ottomitra Multiartha or generate 1.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Wahana Ottomitra Multiartha vs. Mandala Multifinance Tbk
Performance |
Timeline |
Wahana Ottomitra Mul |
Mandala Multifinance Tbk |
Wahana Ottomitra and Mandala Multifinance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Wahana Ottomitra and Mandala Multifinance
The main advantage of trading using opposite Wahana Ottomitra and Mandala Multifinance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Wahana Ottomitra position performs unexpectedly, Mandala Multifinance 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 Mandala Multifinance will offset losses from the drop in Mandala Multifinance's long position.Wahana Ottomitra vs. Trimegah Securities Tbk | Wahana Ottomitra vs. Clipan Finance Indonesia | Wahana Ottomitra vs. Adira Dinamika Multi | Wahana Ottomitra vs. Paninvest Tbk |
Mandala Multifinance vs. Paninvest Tbk | Mandala Multifinance vs. Maskapai Reasuransi Indonesia | Mandala Multifinance vs. Panin Sekuritas Tbk | Mandala Multifinance vs. Wahana Ottomitra Multiartha |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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