Correlation Between T M and Dragon Capital
Can any of the company-specific risk be diversified away by investing in both T M and Dragon Capital 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 T M and Dragon Capital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between T M M and Dragon Capital Grp, you can compare the effects of market volatilities on T M and Dragon Capital 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 T M with a short position of Dragon Capital. Check out your portfolio center. Please also check ongoing floating volatility patterns of T M and Dragon Capital.
Diversification Opportunities for T M and Dragon Capital
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between TMMI and Dragon is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding T M M and Dragon Capital Grp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dragon Capital Grp and T M 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 T M M are associated (or correlated) with Dragon Capital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dragon Capital Grp has no effect on the direction of T M i.e., T M and Dragon Capital go up and down completely randomly.
Pair Corralation between T M and Dragon Capital
Given the investment horizon of 90 days T M is expected to generate 1.02 times less return on investment than Dragon Capital. In addition to that, T M is 1.71 times more volatile than Dragon Capital Grp. It trades about 0.07 of its total potential returns per unit of risk. Dragon Capital Grp is currently generating about 0.12 per unit of volatility. If you would invest 0.05 in Dragon Capital Grp on September 30, 2024 and sell it today you would lose (0.02) from holding Dragon Capital Grp or give up 40.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
T M M vs. Dragon Capital Grp
Performance |
Timeline |
T M M |
Dragon Capital Grp |
T M and Dragon Capital Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with T M and Dragon Capital
The main advantage of trading using opposite T M and Dragon Capital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if T M position performs unexpectedly, Dragon Capital 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 Dragon Capital will offset losses from the drop in Dragon Capital's long position.The idea behind T M M and Dragon Capital Grp 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.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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