Correlation Between Food Moments and Saksiam Leasing
Can any of the company-specific risk be diversified away by investing in both Food Moments and Saksiam Leasing 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 Food Moments and Saksiam Leasing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Food Moments PCL and Saksiam Leasing Public, you can compare the effects of market volatilities on Food Moments and Saksiam Leasing 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 Food Moments with a short position of Saksiam Leasing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Food Moments and Saksiam Leasing.
Diversification Opportunities for Food Moments and Saksiam Leasing
-0.14 | Correlation Coefficient |
Good diversification
The 3 months correlation between Food and Saksiam is -0.14. Overlapping area represents the amount of risk that can be diversified away by holding Food Moments PCL and Saksiam Leasing Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Saksiam Leasing Public and Food Moments 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 Food Moments PCL are associated (or correlated) with Saksiam Leasing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Saksiam Leasing Public has no effect on the direction of Food Moments i.e., Food Moments and Saksiam Leasing go up and down completely randomly.
Pair Corralation between Food Moments and Saksiam Leasing
Assuming the 90 days horizon Food Moments PCL is expected to under-perform the Saksiam Leasing. But the stock apears to be less risky and, when comparing its historical volatility, Food Moments PCL is 1.7 times less risky than Saksiam Leasing. The stock trades about -0.27 of its potential returns per unit of risk. The Saksiam Leasing Public is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 505.00 in Saksiam Leasing Public on August 25, 2024 and sell it today you would earn a total of 35.00 from holding Saksiam Leasing Public or generate 6.93% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Food Moments PCL vs. Saksiam Leasing Public
Performance |
| Timeline |
| Food Moments PCL |
| Saksiam Leasing Public |
Food Moments and Saksiam Leasing Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Food Moments and Saksiam Leasing
The main advantage of trading using opposite Food Moments and Saksiam Leasing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Food Moments position performs unexpectedly, Saksiam Leasing 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 Saksiam Leasing will offset losses from the drop in Saksiam Leasing's long position.| Food Moments vs. Delta Electronics Public | Food Moments vs. Delta Electronics Public | Food Moments vs. Airports of Thailand | Food Moments vs. Airports of Thailand |
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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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