Correlation Between Fine Metal and Ekarat Engineering
Can any of the company-specific risk be diversified away by investing in both Fine Metal and Ekarat Engineering 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 Fine Metal and Ekarat Engineering into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fine Metal Technologies and Ekarat Engineering Public, you can compare the effects of market volatilities on Fine Metal and Ekarat Engineering 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 Fine Metal with a short position of Ekarat Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fine Metal and Ekarat Engineering.
Diversification Opportunities for Fine Metal and Ekarat Engineering
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Fine and Ekarat is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding Fine Metal Technologies and Ekarat Engineering Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ekarat Engineering Public and Fine Metal 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 Fine Metal Technologies are associated (or correlated) with Ekarat Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ekarat Engineering Public has no effect on the direction of Fine Metal i.e., Fine Metal and Ekarat Engineering go up and down completely randomly.
Pair Corralation between Fine Metal and Ekarat Engineering
Assuming the 90 days trading horizon Fine Metal Technologies is expected to under-perform the Ekarat Engineering. In addition to that, Fine Metal is 1.81 times more volatile than Ekarat Engineering Public. It trades about -0.01 of its total potential returns per unit of risk. Ekarat Engineering Public is currently generating about 0.11 per unit of volatility. If you would invest 93.00 in Ekarat Engineering Public on September 25, 2024 and sell it today you would earn a total of 2.00 from holding Ekarat Engineering Public or generate 2.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 95.0% |
Values | Daily Returns |
Fine Metal Technologies vs. Ekarat Engineering Public
Performance |
Timeline |
Fine Metal Technologies |
Ekarat Engineering Public |
Fine Metal and Ekarat Engineering Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fine Metal and Ekarat Engineering
The main advantage of trading using opposite Fine Metal and Ekarat Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fine Metal position performs unexpectedly, Ekarat Engineering 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 Ekarat Engineering will offset losses from the drop in Ekarat Engineering's long position.Fine Metal vs. Land and Houses | Fine Metal vs. CH Karnchang Public | Fine Metal vs. Krung Thai Bank | Fine Metal vs. Bangkok Bank Public |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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