Correlation Between IDX 30 and Bank Victoria

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

Diversification Opportunities for IDX 30 and Bank Victoria

0.84

Correlation Coefficient

IDX 30  Bank Victoria

Very poor diversification

The 3 months correlation between IDX and Bank is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding IDX 30 Jakarta and Bank Victoria International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Victoria Intern 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 Bank Victoria. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Victoria Intern has no effect on the direction of IDX 30 i.e., IDX 30 and Bank Victoria go up and down completely randomly.

Pair Corralation between IDX 30 and Bank Victoria

Assuming the 90 days trading horizon IDX 30 Jakarta is expected to under-perform the Bank Victoria. But the index apears to be less risky and, when comparing its historical volatility, IDX 30 Jakarta is 1.94 times less risky than Bank Victoria. The index trades about -0.08 of its potential returns per unit of risk. The Bank Victoria International is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest  8,900  in Bank Victoria International on December 30, 2024 and sell it today you would lose (700.00) from holding Bank Victoria International or give up 7.87% 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.  Bank Victoria International

Pair Trading with IDX 30 and Bank Victoria

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

The idea behind IDX 30 Jakarta and Bank Victoria International 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.