Correlation Between FARM FRESH and Malaysia Steel
Can any of the company-specific risk be diversified away by investing in both FARM FRESH and Malaysia Steel 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 FARM FRESH and Malaysia Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FARM FRESH BERHAD and Malaysia Steel Works, you can compare the effects of market volatilities on FARM FRESH and Malaysia Steel 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 FARM FRESH with a short position of Malaysia Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of FARM FRESH and Malaysia Steel.
Diversification Opportunities for FARM FRESH and Malaysia Steel
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between FARM and Malaysia is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding FARM FRESH BERHAD and Malaysia Steel Works in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Malaysia Steel Works and FARM FRESH 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 FARM FRESH BERHAD are associated (or correlated) with Malaysia Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Malaysia Steel Works has no effect on the direction of FARM FRESH i.e., FARM FRESH and Malaysia Steel go up and down completely randomly.
Pair Corralation between FARM FRESH and Malaysia Steel
Assuming the 90 days trading horizon FARM FRESH BERHAD is expected to generate 0.61 times more return on investment than Malaysia Steel. However, FARM FRESH BERHAD is 1.63 times less risky than Malaysia Steel. It trades about 0.11 of its potential returns per unit of risk. Malaysia Steel Works is currently generating about 0.0 per unit of risk. If you would invest 130.00 in FARM FRESH BERHAD on September 4, 2024 and sell it today you would earn a total of 57.00 from holding FARM FRESH BERHAD or generate 43.85% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.59% |
| Values | Daily Returns |
FARM FRESH BERHAD vs. Malaysia Steel Works
Performance |
| Timeline |
| FARM FRESH BERHAD |
| Malaysia Steel Works |
FARM FRESH and Malaysia Steel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with FARM FRESH and Malaysia Steel
The main advantage of trading using opposite FARM FRESH and Malaysia Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FARM FRESH position performs unexpectedly, Malaysia Steel 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 Malaysia Steel will offset losses from the drop in Malaysia Steel's long position.| FARM FRESH vs. Central Industrial Corp | FARM FRESH vs. Sports Toto Berhad | FARM FRESH vs. Mycron Steel Bhd | FARM FRESH vs. Choo Bee Metal |
| Malaysia Steel vs. Cengild Medical Berhad | Malaysia Steel vs. Oriental Food Industries | Malaysia Steel vs. Eversafe Rubber Bhd | Malaysia Steel vs. Lotte Chemical Titan |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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