Correlation Between Indara Insurance and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Indara Insurance and Dow Jones 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 Indara Insurance and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Indara Insurance Public and Dow Jones Industrial, you can compare the effects of market volatilities on Indara Insurance and Dow Jones 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 Indara Insurance with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Indara Insurance and Dow Jones.
Diversification Opportunities for Indara Insurance and Dow Jones
-0.69 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Indara and Dow is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding Indara Insurance Public and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Indara Insurance 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 Indara Insurance Public are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Indara Insurance i.e., Indara Insurance and Dow Jones go up and down completely randomly.
Pair Corralation between Indara Insurance and Dow Jones
Assuming the 90 days trading horizon Indara Insurance Public is expected to under-perform the Dow Jones. In addition to that, Indara Insurance is 4.04 times more volatile than Dow Jones Industrial. It trades about -0.05 of its total potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.11 per unit of volatility. If you would invest 4,162,208 in Dow Jones Industrial on September 16, 2024 and sell it today you would earn a total of 220,598 from holding Dow Jones Industrial or generate 5.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 95.38% |
Values | Daily Returns |
Indara Insurance Public vs. Dow Jones Industrial
Performance |
Timeline |
Indara Insurance and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Indara Insurance Public
Pair trading matchups for Indara Insurance
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Indara Insurance and Dow Jones
The main advantage of trading using opposite Indara Insurance and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Indara Insurance position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.Indara Insurance vs. IFS Capital Public | Indara Insurance vs. Internet Thailand Public | Indara Insurance vs. Hwa Fong Rubber | Indara Insurance vs. Haad Thip Public |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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