Correlation Between IDX 30 and NFC Indonesia

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

Diversification Opportunities for IDX 30 and NFC Indonesia

-0.07
  Correlation Coefficient

Good diversification

The 3 months correlation between IDX and NFC is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding IDX 30 Jakarta and NFC Indonesia PT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NFC Indonesia PT 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 NFC Indonesia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NFC Indonesia PT has no effect on the direction of IDX 30 i.e., IDX 30 and NFC Indonesia go up and down completely randomly.
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Pair Corralation between IDX 30 and NFC Indonesia

Assuming the 90 days trading horizon IDX 30 Jakarta is expected to under-perform the NFC Indonesia. But the index apears to be less risky and, when comparing its historical volatility, IDX 30 Jakarta is 7.64 times less risky than NFC Indonesia. The index trades about -0.6 of its potential returns per unit of risk. The NFC Indonesia PT is currently generating about 0.24 of returns per unit of risk over similar time horizon. If you would invest  109,000  in NFC Indonesia PT on August 24, 2024 and sell it today you would earn a total of  36,000  from holding NFC Indonesia PT or generate 33.03% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

IDX 30 Jakarta  vs.  NFC Indonesia PT

 Performance 
       Timeline  

IDX 30 and NFC Indonesia Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with IDX 30 and NFC Indonesia

The main advantage of trading using opposite IDX 30 and NFC Indonesia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IDX 30 position performs unexpectedly, NFC 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 NFC Indonesia will offset losses from the drop in NFC Indonesia's long position.
The idea behind IDX 30 Jakarta and NFC Indonesia PT 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.

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