Correlation Between Coreshares Index and IDX 30

Can any of the company-specific risk be diversified away by investing in both Coreshares Index and IDX 30 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 Coreshares Index and IDX 30 into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Coreshares Index Tracker and IDX 30 Jakarta, you can compare the effects of market volatilities on Coreshares Index and IDX 30 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 Coreshares Index with a short position of IDX 30. Check out your portfolio center. Please also check ongoing floating volatility patterns of Coreshares Index and IDX 30.

Diversification Opportunities for Coreshares Index and IDX 30

-0.04

Correlation Coefficient

Coreshares Index  IDX 30

Good diversification

The 3 months correlation between Coreshares and IDX is -0.04. Overlapping area represents the amount of risk that can be diversified away by holding Coreshares Index Tracker and IDX 30 Jakarta in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on IDX 30 Jakarta and Coreshares Index 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 Coreshares Index Tracker are associated (or correlated) with IDX 30. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IDX 30 Jakarta has no effect on the direction of Coreshares Index i.e., Coreshares Index and IDX 30 go up and down completely randomly.

Pair Corralation between Coreshares Index and IDX 30

Assuming the 90 days trading horizon Coreshares Index Tracker is expected to generate 1.03 times more return on investment than IDX 30. However, Coreshares Index is 1.03 times more volatile than IDX 30 Jakarta. It trades about 0.01 of its potential returns per unit of risk. IDX 30 Jakarta is currently generating about -0.16 per unit of risk. If you would invest  107,500  in Coreshares Index Tracker on September 1, 2024 and sell it today you would earn a total of  500.00  from holding Coreshares Index Tracker or generate 0.47% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Insignificant
Accuracy	98.44%
Values	Daily Returns

Coreshares Index Tracker  vs.  IDX 30 Jakarta

Pair Trading with Coreshares Index and IDX 30

The main advantage of trading using opposite Coreshares Index and IDX 30 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Coreshares Index position performs unexpectedly, IDX 30 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 IDX 30 will offset losses from the drop in IDX 30's long position.

The idea behind Coreshares Index Tracker and IDX 30 Jakarta 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.