Correlation Between Panin Financial and Bukit Uluwatu
Can any of the company-specific risk be diversified away by investing in both Panin Financial and Bukit Uluwatu 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 Panin Financial and Bukit Uluwatu into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Panin Financial Tbk and Bukit Uluwatu Villa, you can compare the effects of market volatilities on Panin Financial and Bukit Uluwatu 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 Panin Financial with a short position of Bukit Uluwatu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Panin Financial and Bukit Uluwatu.
Diversification Opportunities for Panin Financial and Bukit Uluwatu
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Panin and Bukit is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Panin Financial Tbk and Bukit Uluwatu Villa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bukit Uluwatu Villa and Panin Financial 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 Panin Financial Tbk are associated (or correlated) with Bukit Uluwatu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bukit Uluwatu Villa has no effect on the direction of Panin Financial i.e., Panin Financial and Bukit Uluwatu go up and down completely randomly.
Pair Corralation between Panin Financial and Bukit Uluwatu
Assuming the 90 days trading horizon Panin Financial is expected to generate 1.31 times less return on investment than Bukit Uluwatu. But when comparing it to its historical volatility, Panin Financial Tbk is 1.57 times less risky than Bukit Uluwatu. It trades about 0.08 of its potential returns per unit of risk. Bukit Uluwatu Villa is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 5,400 in Bukit Uluwatu Villa on September 5, 2024 and sell it today you would earn a total of 700.00 from holding Bukit Uluwatu Villa or generate 12.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Panin Financial Tbk vs. Bukit Uluwatu Villa
Performance |
Timeline |
Panin Financial Tbk |
Bukit Uluwatu Villa |
Panin Financial and Bukit Uluwatu Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Panin Financial and Bukit Uluwatu
The main advantage of trading using opposite Panin Financial and Bukit Uluwatu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Panin Financial position performs unexpectedly, Bukit Uluwatu 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 Bukit Uluwatu will offset losses from the drop in Bukit Uluwatu's long position.Panin Financial vs. Paninvest Tbk | Panin Financial vs. Mitra Pinasthika Mustika | Panin Financial vs. Jakarta Int Hotels | Panin Financial vs. Asuransi Harta Aman |
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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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