Correlation Between Bank Negara and Sugarmade
Can any of the company-specific risk be diversified away by investing in both Bank Negara and Sugarmade 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 Negara and Sugarmade into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Negara Indonesia and Sugarmade, you can compare the effects of market volatilities on Bank Negara and Sugarmade 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 Negara with a short position of Sugarmade. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Negara and Sugarmade.
Diversification Opportunities for Bank Negara and Sugarmade
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Sugarmade is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Bank Negara Indonesia and Sugarmade in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sugarmade and Bank Negara 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 Negara Indonesia are associated (or correlated) with Sugarmade. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sugarmade has no effect on the direction of Bank Negara i.e., Bank Negara and Sugarmade go up and down completely randomly.
Pair Corralation between Bank Negara and Sugarmade
Assuming the 90 days horizon Bank Negara Indonesia is expected to under-perform the Sugarmade. But the pink sheet apears to be less risky and, when comparing its historical volatility, Bank Negara Indonesia is 58.73 times less risky than Sugarmade. The pink sheet trades about -0.08 of its potential returns per unit of risk. The Sugarmade is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 0.50 in Sugarmade on September 28, 2024 and sell it today you would lose (0.49) from holding Sugarmade or give up 98.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 92.06% |
Values | Daily Returns |
Bank Negara Indonesia vs. Sugarmade
Performance |
Timeline |
Bank Negara Indonesia |
Sugarmade |
Bank Negara and Sugarmade Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Negara and Sugarmade
The main advantage of trading using opposite Bank Negara and Sugarmade positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Negara position performs unexpectedly, Sugarmade 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 Sugarmade will offset losses from the drop in Sugarmade's long position.Bank Negara vs. Banco Bradesco SA | Bank Negara vs. Itau Unibanco Banco | Bank Negara vs. Deutsche Bank AG | Bank Negara vs. Banco Santander Brasil |
Sugarmade vs. Puma Exploration | Sugarmade vs. Sixty North Gold | Sugarmade vs. Red Pine Exploration | Sugarmade vs. Altamira Gold Corp |
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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