Correlation Between IOTA and Dow Jones
Can any of the company-specific risk be diversified away by investing in both IOTA 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 IOTA and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between IOTA and Dow Jones Industrial, you can compare the effects of market volatilities on IOTA 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 IOTA with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of IOTA and Dow Jones.
Diversification Opportunities for IOTA and Dow Jones
Poor diversification
The 3 months correlation between IOTA and Dow is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding IOTA 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 IOTA 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 IOTA 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 IOTA i.e., IOTA and Dow Jones go up and down completely randomly.
Pair Corralation between IOTA and Dow Jones
Assuming the 90 days trading horizon IOTA is expected to generate 9.17 times more return on investment than Dow Jones. However, IOTA is 9.17 times more volatile than Dow Jones Industrial. It trades about 0.5 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.37 per unit of risk. If you would invest 11.00 in IOTA on September 1, 2024 and sell it today you would earn a total of 15.00 from holding IOTA or generate 136.36% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.45% |
| Values | Daily Returns |
IOTA vs. Dow Jones Industrial
Performance |
| Timeline |
IOTA and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
IOTA
Pair trading matchups for IOTA
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with IOTA and Dow Jones
The main advantage of trading using opposite IOTA and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IOTA 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.The idea behind IOTA and Dow Jones Industrial 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.| Dow Jones vs. Catalyst Pharmaceuticals | Dow Jones vs. Sphere Entertainment Co | Dow Jones vs. National CineMedia | Dow Jones vs. Mink Therapeutics |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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