Correlation Between Merida Industry and San Shing
Can any of the company-specific risk be diversified away by investing in both Merida Industry and San Shing 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 Merida Industry and San Shing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Merida Industry Co and San Shing Fastech, you can compare the effects of market volatilities on Merida Industry and San Shing 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 Merida Industry with a short position of San Shing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Merida Industry and San Shing.
Diversification Opportunities for Merida Industry and San Shing
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Merida and San is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Merida Industry Co and San Shing Fastech in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on San Shing Fastech and Merida Industry 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 Merida Industry Co are associated (or correlated) with San Shing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of San Shing Fastech has no effect on the direction of Merida Industry i.e., Merida Industry and San Shing go up and down completely randomly.
Pair Corralation between Merida Industry and San Shing
Assuming the 90 days trading horizon Merida Industry Co is expected to under-perform the San Shing. In addition to that, Merida Industry is 3.12 times more volatile than San Shing Fastech. It trades about -0.1 of its total potential returns per unit of risk. San Shing Fastech is currently generating about -0.12 per unit of volatility. If you would invest 5,600 in San Shing Fastech on September 7, 2024 and sell it today you would lose (110.00) from holding San Shing Fastech or give up 1.96% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 95.65% |
Values | Daily Returns |
Merida Industry Co vs. San Shing Fastech
Performance |
Timeline |
Merida Industry |
San Shing Fastech |
Merida Industry and San Shing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Merida Industry and San Shing
The main advantage of trading using opposite Merida Industry and San Shing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Merida Industry position performs unexpectedly, San Shing 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 San Shing will offset losses from the drop in San Shing's long position.Merida Industry vs. Giant Manufacturing Co | Merida Industry vs. Cheng Shin Rubber | Merida Industry vs. Feng Tay Enterprises | Merida Industry vs. President Chain Store |
San Shing vs. Topco Scientific Co | San Shing vs. WPG Holdings | San Shing vs. Charoen Pokphand Enterprise | San Shing vs. Merida Industry Co |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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