Correlation Between Bank Rakyat and Hotel Fitra
Can any of the company-specific risk be diversified away by investing in both Bank Rakyat and Hotel Fitra 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 Bank Rakyat and Hotel Fitra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Rakyat Indonesia and Hotel Fitra International, you can compare the effects of market volatilities on Bank Rakyat and Hotel Fitra 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 Bank Rakyat with a short position of Hotel Fitra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Rakyat and Hotel Fitra.
Diversification Opportunities for Bank Rakyat and Hotel Fitra
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Bank and Hotel is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding Bank Rakyat Indonesia and Hotel Fitra International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hotel Fitra International and Bank Rakyat 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 Bank Rakyat Indonesia are associated (or correlated) with Hotel Fitra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hotel Fitra International has no effect on the direction of Bank Rakyat i.e., Bank Rakyat and Hotel Fitra go up and down completely randomly.
Pair Corralation between Bank Rakyat and Hotel Fitra
Assuming the 90 days trading horizon Bank Rakyat is expected to generate 26.82 times less return on investment than Hotel Fitra. But when comparing it to its historical volatility, Bank Rakyat Indonesia is 1.68 times less risky than Hotel Fitra. It trades about 0.01 of its potential returns per unit of risk. Hotel Fitra International is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 9,700 in Hotel Fitra International on December 29, 2024 and sell it today you would earn a total of 5,500 from holding Hotel Fitra International or generate 56.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Rakyat Indonesia vs. Hotel Fitra International
Performance |
Timeline |
Bank Rakyat Indonesia |
Hotel Fitra International |
Bank Rakyat and Hotel Fitra Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Rakyat and Hotel Fitra
The main advantage of trading using opposite Bank Rakyat and Hotel Fitra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Rakyat position performs unexpectedly, Hotel Fitra 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 Hotel Fitra will offset losses from the drop in Hotel Fitra's long position.Bank Rakyat vs. Bank Central Asia | Bank Rakyat vs. Bank Mandiri Persero | Bank Rakyat vs. Bank Negara Indonesia | Bank Rakyat vs. Telkom Indonesia Tbk |
Hotel Fitra vs. Eastparc Hotel Tbk | Hotel Fitra vs. Menteng Heritage Realty | Hotel Fitra vs. Sanurhasta Mitra PT | Hotel Fitra vs. Sentra Food Indonesia |
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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