Correlation Between IDX 30 and Polychem Indonesia

Can any of the company-specific risk be diversified away by investing in both IDX 30 and Polychem Indonesia 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 Polychem Indonesia 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 Polychem Indonesia Tbk, you can compare the effects of market volatilities on IDX 30 and Polychem Indonesia 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 Polychem Indonesia. Check out your portfolio center. Please also check ongoing floating volatility patterns of IDX 30 and Polychem Indonesia.

Diversification Opportunities for IDX 30 and Polychem Indonesia

0.8

Correlation Coefficient

IDX 30  Polychem Indonesia

Very poor diversification

The 3 months correlation between IDX and Polychem is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding IDX 30 Jakarta and Polychem Indonesia Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Polychem Indonesia 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 Polychem Indonesia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Polychem Indonesia Tbk has no effect on the direction of IDX 30 i.e., IDX 30 and Polychem Indonesia go up and down completely randomly.

Pair Corralation between IDX 30 and Polychem Indonesia

Assuming the 90 days trading horizon IDX 30 Jakarta is expected to generate 0.7 times more return on investment than Polychem Indonesia. However, IDX 30 Jakarta is 1.42 times less risky than Polychem Indonesia. It trades about -0.09 of its potential returns per unit of risk. Polychem Indonesia Tbk is currently generating about -0.13 per unit of risk. If you would invest  48,815  in IDX 30 Jakarta on September 12, 2024 and sell it today you would lose (3,136) from holding IDX 30 Jakarta or give up 6.42% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Strong
Accuracy	100.0%
Values	Daily Returns

IDX 30 Jakarta  vs.  Polychem Indonesia Tbk

Pair Trading with IDX 30 and Polychem Indonesia

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

The idea behind IDX 30 Jakarta and Polychem Indonesia 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.

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.