Correlation Between Bank Yudha and Bank Dinar
Can any of the company-specific risk be diversified away by investing in both Bank Yudha and Bank Dinar 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 Yudha and Bank Dinar into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Yudha Bhakti and Bank Dinar Indonesia, you can compare the effects of market volatilities on Bank Yudha and Bank Dinar 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 Yudha with a short position of Bank Dinar. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Yudha and Bank Dinar.
Diversification Opportunities for Bank Yudha and Bank Dinar
-0.5 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Bank is -0.5. Overlapping area represents the amount of risk that can be diversified away by holding Bank Yudha Bhakti and Bank Dinar Indonesia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Dinar Indonesia and Bank Yudha 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 Yudha Bhakti are associated (or correlated) with Bank Dinar. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Dinar Indonesia has no effect on the direction of Bank Yudha i.e., Bank Yudha and Bank Dinar go up and down completely randomly.
Pair Corralation between Bank Yudha and Bank Dinar
Assuming the 90 days trading horizon Bank Yudha Bhakti is expected to under-perform the Bank Dinar. But the stock apears to be less risky and, when comparing its historical volatility, Bank Yudha Bhakti is 2.12 times less risky than Bank Dinar. The stock trades about -0.08 of its potential returns per unit of risk. The Bank Dinar Indonesia is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 8,500 in Bank Dinar Indonesia on September 16, 2024 and sell it today you would earn a total of 4,100 from holding Bank Dinar Indonesia or generate 48.24% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Yudha Bhakti vs. Bank Dinar Indonesia
Performance |
Timeline |
Bank Yudha Bhakti |
Bank Dinar Indonesia |
Bank Yudha and Bank Dinar Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Yudha and Bank Dinar
The main advantage of trading using opposite Bank Yudha and Bank Dinar positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Yudha position performs unexpectedly, Bank Dinar 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 Bank Dinar will offset losses from the drop in Bank Dinar's long position.Bank Yudha vs. Paninvest Tbk | Bank Yudha vs. Maskapai Reasuransi Indonesia | Bank Yudha vs. Panin Sekuritas Tbk | Bank Yudha vs. Wahana Ottomitra Multiartha |
Bank Dinar vs. Bank Agris Tbk | Bank Dinar vs. Bank Yudha Bhakti | Bank Dinar vs. Bank Qnb Indonesia | Bank Dinar vs. Bank Ganesha Tbk |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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