Correlation Between Dow Jones and Inverse Nasdaq-100
Can any of the company-specific risk be diversified away by investing in both Dow Jones and Inverse Nasdaq-100 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 Dow Jones and Inverse Nasdaq-100 into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dow Jones Industrial and Inverse Nasdaq 100 Strategy, you can compare the effects of market volatilities on Dow Jones and Inverse Nasdaq-100 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 Dow Jones with a short position of Inverse Nasdaq-100. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Inverse Nasdaq-100.
Diversification Opportunities for Dow Jones and Inverse Nasdaq-100
0.01 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Dow and Inverse is 0.01. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Inverse Nasdaq 100 Strategy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Inverse Nasdaq 100 and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Inverse Nasdaq-100. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Inverse Nasdaq 100 has no effect on the direction of Dow Jones i.e., Dow Jones and Inverse Nasdaq-100 go up and down completely randomly.
Pair Corralation between Dow Jones and Inverse Nasdaq-100
Assuming the 90 days horizon Dow Jones Industrial is expected to under-perform the Inverse Nasdaq-100. But the mutual fund apears to be less risky and, when comparing its historical volatility, Dow Jones Industrial is 213.66 times less risky than Inverse Nasdaq-100. The mutual fund trades about -0.09 of its potential returns per unit of risk. The Inverse Nasdaq 100 Strategy is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 1,082 in Inverse Nasdaq 100 Strategy on November 28, 2024 and sell it today you would earn a total of 9,606 from holding Inverse Nasdaq 100 Strategy or generate 887.8% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Dow Jones Industrial vs. Inverse Nasdaq 100 Strategy
Performance |
Timeline |
Dow Jones Industrial |
Inverse Nasdaq 100 |
Dow Jones and Inverse Nasdaq-100 Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dow Jones and Inverse Nasdaq-100
The main advantage of trading using opposite Dow Jones and Inverse Nasdaq-100 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Inverse Nasdaq-100 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 Inverse Nasdaq-100 will offset losses from the drop in Inverse Nasdaq-100's long position.Dow Jones vs. Sp 500 Pure | Dow Jones vs. Sp Midcap 400 | Dow Jones vs. Sp 500 Pure | Dow Jones vs. Sp 500 Fund |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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