Correlation Between Acset Indonusa and Bekasi Fajar
Can any of the company-specific risk be diversified away by investing in both Acset Indonusa and Bekasi Fajar 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 Acset Indonusa and Bekasi Fajar into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Acset Indonusa Tbk and Bekasi Fajar Industrial, you can compare the effects of market volatilities on Acset Indonusa and Bekasi Fajar 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 Acset Indonusa with a short position of Bekasi Fajar. Check out your portfolio center. Please also check ongoing floating volatility patterns of Acset Indonusa and Bekasi Fajar.
Diversification Opportunities for Acset Indonusa and Bekasi Fajar
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Acset and Bekasi is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Acset Indonusa Tbk and Bekasi Fajar Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bekasi Fajar Industrial and Acset Indonusa 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 Acset Indonusa Tbk are associated (or correlated) with Bekasi Fajar. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bekasi Fajar Industrial has no effect on the direction of Acset Indonusa i.e., Acset Indonusa and Bekasi Fajar go up and down completely randomly.
Pair Corralation between Acset Indonusa and Bekasi Fajar
Assuming the 90 days trading horizon Acset Indonusa Tbk is expected to under-perform the Bekasi Fajar. But the stock apears to be less risky and, when comparing its historical volatility, Acset Indonusa Tbk is 1.25 times less risky than Bekasi Fajar. The stock trades about -0.22 of its potential returns per unit of risk. The Bekasi Fajar Industrial is currently generating about -0.15 of returns per unit of risk over similar time horizon. If you would invest 12,800 in Bekasi Fajar Industrial on September 20, 2024 and sell it today you would lose (2,600) from holding Bekasi Fajar Industrial or give up 20.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Acset Indonusa Tbk vs. Bekasi Fajar Industrial
Performance |
Timeline |
Acset Indonusa Tbk |
Bekasi Fajar Industrial |
Acset Indonusa and Bekasi Fajar Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Acset Indonusa and Bekasi Fajar
The main advantage of trading using opposite Acset Indonusa and Bekasi Fajar positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Acset Indonusa position performs unexpectedly, Bekasi Fajar 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 Bekasi Fajar will offset losses from the drop in Bekasi Fajar's long position.Acset Indonusa vs. PT Indonesia Kendaraan | Acset Indonusa vs. Surya Toto Indonesia | Acset Indonusa vs. Mitra Pinasthika Mustika | Acset Indonusa vs. Integra Indocabinet Tbk |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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