Correlation Between Bank Pan and Victoria Care
Can any of the company-specific risk be diversified away by investing in both Bank Pan and Victoria Care 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 Pan and Victoria Care into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Pan Indonesia and Victoria Care Indonesia, you can compare the effects of market volatilities on Bank Pan and Victoria Care 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 Pan with a short position of Victoria Care. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Pan and Victoria Care.
Diversification Opportunities for Bank Pan and Victoria Care
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Victoria is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding Bank Pan Indonesia and Victoria Care Indonesia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Victoria Care Indonesia and Bank Pan 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 Pan Indonesia are associated (or correlated) with Victoria Care. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Victoria Care Indonesia has no effect on the direction of Bank Pan i.e., Bank Pan and Victoria Care go up and down completely randomly.
Pair Corralation between Bank Pan and Victoria Care
Assuming the 90 days trading horizon Bank Pan Indonesia is expected to generate 2.83 times more return on investment than Victoria Care. However, Bank Pan is 2.83 times more volatile than Victoria Care Indonesia. It trades about 0.09 of its potential returns per unit of risk. Victoria Care Indonesia is currently generating about 0.0 per unit of risk. If you would invest 113,000 in Bank Pan Indonesia on October 3, 2024 and sell it today you would earn a total of 73,000 from holding Bank Pan Indonesia or generate 64.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Pan Indonesia vs. Victoria Care Indonesia
Performance |
Timeline |
Bank Pan Indonesia |
Victoria Care Indonesia |
Bank Pan and Victoria Care Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Pan and Victoria Care
The main advantage of trading using opposite Bank Pan and Victoria Care positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Pan position performs unexpectedly, Victoria Care 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 Victoria Care will offset losses from the drop in Victoria Care's long position.Bank Pan vs. Bank Danamon Indonesia | Bank Pan vs. Bank Cimb Niaga | Bank Pan vs. Panin Financial Tbk | Bank Pan vs. Bank Maybank Indonesia |
Victoria Care vs. Garudafood Putra Putri | Victoria Care vs. Uni Charm Indonesia | Victoria Care vs. Provident Agro Tbk | Victoria Care vs. Kino Indonesia 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 Valuation module to check real value of public entities based on technical and fundamental data.
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