Correlation Between Galan Lithium and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Galan Lithium 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 Galan Lithium and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Galan Lithium and Dow Jones Industrial, you can compare the effects of market volatilities on Galan Lithium 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 Galan Lithium with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Galan Lithium and Dow Jones.
Diversification Opportunities for Galan Lithium and Dow Jones
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Galan and Dow is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding Galan Lithium 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 Galan Lithium 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 Galan Lithium 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 Galan Lithium i.e., Galan Lithium and Dow Jones go up and down completely randomly.
Pair Corralation between Galan Lithium and Dow Jones
Assuming the 90 days trading horizon Galan Lithium is expected to generate 9.59 times more return on investment than Dow Jones. However, Galan Lithium is 9.59 times more volatile than Dow Jones Industrial. It trades about 0.01 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about -0.1 per unit of risk. If you would invest 15.00 in Galan Lithium on October 9, 2024 and sell it today you would lose (1.00) from holding Galan Lithium or give up 6.67% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 97.56% |
Values | Daily Returns |
Galan Lithium vs. Dow Jones Industrial
Performance |
Timeline |
Galan Lithium and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Galan Lithium
Pair trading matchups for Galan Lithium
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Galan Lithium and Dow Jones
The main advantage of trading using opposite Galan Lithium and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Galan Lithium 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.Galan Lithium vs. Medibank Private | Galan Lithium vs. Bank of Queensland | Galan Lithium vs. Carnegie Clean Energy | Galan Lithium vs. Insurance Australia Group |
Dow Jones vs. FMC Corporation | Dow Jones vs. Chemours Co | Dow Jones vs. Park Electrochemical | Dow Jones vs. Griffon |
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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