Correlation Between Internet Thailand and Hua Hong
Can any of the company-specific risk be diversified away by investing in both Internet Thailand and Hua Hong 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 Internet Thailand and Hua Hong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Internet Thailand PCL and Hua Hong Semiconductor, you can compare the effects of market volatilities on Internet Thailand and Hua Hong 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 Internet Thailand with a short position of Hua Hong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Internet Thailand and Hua Hong.
Diversification Opportunities for Internet Thailand and Hua Hong
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Internet and Hua is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding Internet Thailand PCL and Hua Hong Semiconductor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hua Hong Semiconductor and Internet Thailand 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 Internet Thailand PCL are associated (or correlated) with Hua Hong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hua Hong Semiconductor has no effect on the direction of Internet Thailand i.e., Internet Thailand and Hua Hong go up and down completely randomly.
Pair Corralation between Internet Thailand and Hua Hong
Assuming the 90 days trading horizon Internet Thailand PCL is expected to generate 1.37 times more return on investment than Hua Hong. However, Internet Thailand is 1.37 times more volatile than Hua Hong Semiconductor. It trades about 0.12 of its potential returns per unit of risk. Hua Hong Semiconductor is currently generating about -0.08 per unit of risk. If you would invest 12.00 in Internet Thailand PCL on October 8, 2024 and sell it today you would earn a total of 4.00 from holding Internet Thailand PCL or generate 33.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Internet Thailand PCL vs. Hua Hong Semiconductor
Performance |
Timeline |
Internet Thailand PCL |
Hua Hong Semiconductor |
Internet Thailand and Hua Hong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Internet Thailand and Hua Hong
The main advantage of trading using opposite Internet Thailand and Hua Hong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Internet Thailand position performs unexpectedly, Hua Hong 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 Hua Hong will offset losses from the drop in Hua Hong's long position.Internet Thailand vs. Scottish Mortgage Investment | Internet Thailand vs. Japan Asia Investment | Internet Thailand vs. SLR Investment Corp | Internet Thailand vs. NIGHTINGALE HEALTH EO |
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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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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