Correlation Between Ming Le and SCIENCE IN
Can any of the company-specific risk be diversified away by investing in both Ming Le and SCIENCE IN 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 Ming Le and SCIENCE IN into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ming Le Sports and SCIENCE IN SPORT, you can compare the effects of market volatilities on Ming Le and SCIENCE IN 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 Ming Le with a short position of SCIENCE IN. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ming Le and SCIENCE IN.
Diversification Opportunities for Ming Le and SCIENCE IN
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Ming and SCIENCE is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Ming Le Sports and SCIENCE IN SPORT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SCIENCE IN SPORT and Ming Le 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 Ming Le Sports are associated (or correlated) with SCIENCE IN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SCIENCE IN SPORT has no effect on the direction of Ming Le i.e., Ming Le and SCIENCE IN go up and down completely randomly.
Pair Corralation between Ming Le and SCIENCE IN
Assuming the 90 days trading horizon Ming Le Sports is expected to generate 3.16 times more return on investment than SCIENCE IN. However, Ming Le is 3.16 times more volatile than SCIENCE IN SPORT. It trades about 0.23 of its potential returns per unit of risk. SCIENCE IN SPORT is currently generating about 0.15 per unit of risk. If you would invest 100.00 in Ming Le Sports on August 31, 2024 and sell it today you would earn a total of 39.00 from holding Ming Le Sports or generate 39.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ming Le Sports vs. SCIENCE IN SPORT
Performance |
| Timeline |
| Ming Le Sports |
| SCIENCE IN SPORT |
Ming Le and SCIENCE IN Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ming Le and SCIENCE IN
The main advantage of trading using opposite Ming Le and SCIENCE IN positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ming Le position performs unexpectedly, SCIENCE IN 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 SCIENCE IN will offset losses from the drop in SCIENCE IN's long position.The idea behind Ming Le Sports and SCIENCE IN SPORT 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.| SCIENCE IN vs. Danone SA | SCIENCE IN vs. Superior Plus Corp | SCIENCE IN vs. NMI Holdings | SCIENCE IN vs. Origin Agritech |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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