Correlation Between Land and MFEC PCL
Can any of the company-specific risk be diversified away by investing in both Land and MFEC PCL 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 Land and MFEC PCL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Land and Houses and MFEC PCL, you can compare the effects of market volatilities on Land and MFEC PCL 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 Land with a short position of MFEC PCL. Check out your portfolio center. Please also check ongoing floating volatility patterns of Land and MFEC PCL.
Diversification Opportunities for Land and MFEC PCL
Good diversification
The 3 months correlation between Land and MFEC is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding Land and Houses and MFEC PCL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MFEC PCL and Land 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 Land and Houses are associated (or correlated) with MFEC PCL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MFEC PCL has no effect on the direction of Land i.e., Land and MFEC PCL go up and down completely randomly.
Pair Corralation between Land and MFEC PCL
Assuming the 90 days horizon Land and Houses is expected to under-perform the MFEC PCL. But the stock apears to be less risky and, when comparing its historical volatility, Land and Houses is 37.84 times less risky than MFEC PCL. The stock trades about -0.07 of its potential returns per unit of risk. The MFEC PCL is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 735.00 in MFEC PCL on September 1, 2024 and sell it today you would lose (105.00) from holding MFEC PCL or give up 14.29% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.73% |
| Values | Daily Returns |
Land and Houses vs. MFEC PCL
Performance |
| Timeline |
| Land and Houses |
| MFEC PCL |
Land and MFEC PCL Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Land and MFEC PCL
The main advantage of trading using opposite Land and MFEC PCL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Land position performs unexpectedly, MFEC PCL 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 MFEC PCL will offset losses from the drop in MFEC PCL's long position.The idea behind Land and Houses and MFEC PCL 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.| MFEC PCL vs. AP Public | MFEC PCL vs. Jasmine International Public | MFEC PCL vs. Asia Plus Group | MFEC PCL vs. Bangchak Public |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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