Correlation Between Aju IB and Daou Data
Can any of the company-specific risk be diversified away by investing in both Aju IB and Daou Data 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 Aju IB and Daou Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aju IB Investment and Daou Data Corp, you can compare the effects of market volatilities on Aju IB and Daou Data 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 Aju IB with a short position of Daou Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aju IB and Daou Data.
Diversification Opportunities for Aju IB and Daou Data
Very good diversification
The 3 months correlation between Aju and Daou is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Aju IB Investment and Daou Data Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daou Data Corp and Aju IB 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 Aju IB Investment are associated (or correlated) with Daou Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daou Data Corp has no effect on the direction of Aju IB i.e., Aju IB and Daou Data go up and down completely randomly.
Pair Corralation between Aju IB and Daou Data
Assuming the 90 days trading horizon Aju IB Investment is expected to under-perform the Daou Data. In addition to that, Aju IB is 2.42 times more volatile than Daou Data Corp. It trades about -0.14 of its total potential returns per unit of risk. Daou Data Corp is currently generating about -0.31 per unit of volatility. If you would invest 1,060,000 in Daou Data Corp on October 22, 2024 and sell it today you would lose (61,000) from holding Daou Data Corp or give up 5.75% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Aju IB Investment vs. Daou Data Corp
Performance |
Timeline |
Aju IB Investment |
Daou Data Corp |
Aju IB and Daou Data Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aju IB and Daou Data
The main advantage of trading using opposite Aju IB and Daou Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aju IB position performs unexpectedly, Daou Data 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 Daou Data will offset losses from the drop in Daou Data's long position.The idea behind Aju IB Investment and Daou Data Corp 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.Daou Data vs. Dongjin Semichem Co | Daou Data vs. AhnLab Inc | Daou Data vs. Posco ICT | Daou Data vs. CJ ENM |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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