Correlation Between IDX 30 and Acset Indonusa

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Can any of the company-specific risk be diversified away by investing in both IDX 30 and Acset Indonusa 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 IDX 30 and Acset Indonusa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between IDX 30 Jakarta and Acset Indonusa Tbk, you can compare the effects of market volatilities on IDX 30 and Acset Indonusa 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 IDX 30 with a short position of Acset Indonusa. Check out your portfolio center. Please also check ongoing floating volatility patterns of IDX 30 and Acset Indonusa.

Diversification Opportunities for IDX 30 and Acset Indonusa

0.86
  Correlation Coefficient

Very poor diversification

The 3 months correlation between IDX and Acset is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding IDX 30 Jakarta and Acset Indonusa Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Acset Indonusa Tbk and IDX 30 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 IDX 30 Jakarta are associated (or correlated) with Acset Indonusa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Acset Indonusa Tbk has no effect on the direction of IDX 30 i.e., IDX 30 and Acset Indonusa go up and down completely randomly.
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Pair Corralation between IDX 30 and Acset Indonusa

Assuming the 90 days trading horizon IDX 30 Jakarta is expected to generate 0.76 times more return on investment than Acset Indonusa. However, IDX 30 Jakarta is 1.32 times less risky than Acset Indonusa. It trades about -0.09 of its potential returns per unit of risk. Acset Indonusa Tbk is currently generating about -0.21 per unit of risk. If you would invest  44,351  in IDX 30 Jakarta on September 18, 2024 and sell it today you would lose (1,334) from holding IDX 30 Jakarta or give up 3.01% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthStrong
Accuracy100.0%
ValuesDaily Returns

IDX 30 Jakarta  vs.  Acset Indonusa Tbk

 Performance 
       Timeline  

IDX 30 and Acset Indonusa Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with IDX 30 and Acset Indonusa

The main advantage of trading using opposite IDX 30 and Acset Indonusa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IDX 30 position performs unexpectedly, Acset Indonusa 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 Acset Indonusa will offset losses from the drop in Acset Indonusa's long position.
The idea behind IDX 30 Jakarta and Acset Indonusa Tbk pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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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