Correlation Between TT Electronics and Samsung Electronics
Can any of the company-specific risk be diversified away by investing in both TT Electronics and Samsung Electronics 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 TT Electronics and Samsung Electronics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between TT Electronics PLC and Samsung Electronics Co, you can compare the effects of market volatilities on TT Electronics and Samsung Electronics 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 TT Electronics with a short position of Samsung Electronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of TT Electronics and Samsung Electronics.
Diversification Opportunities for TT Electronics and Samsung Electronics
-0.21 | Correlation Coefficient |
Very good diversification
The 3 months correlation between 7TT and Samsung is -0.21. Overlapping area represents the amount of risk that can be diversified away by holding TT Electronics PLC and Samsung Electronics Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Samsung Electronics and TT Electronics 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 TT Electronics PLC are associated (or correlated) with Samsung Electronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Samsung Electronics has no effect on the direction of TT Electronics i.e., TT Electronics and Samsung Electronics go up and down completely randomly.
Pair Corralation between TT Electronics and Samsung Electronics
Assuming the 90 days trading horizon TT Electronics PLC is expected to generate 1.91 times more return on investment than Samsung Electronics. However, TT Electronics is 1.91 times more volatile than Samsung Electronics Co. It trades about 0.17 of its potential returns per unit of risk. Samsung Electronics Co is currently generating about -0.05 per unit of risk. If you would invest 90.00 in TT Electronics PLC on October 6, 2024 and sell it today you would earn a total of 32.00 from holding TT Electronics PLC or generate 35.56% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
TT Electronics PLC vs. Samsung Electronics Co
Performance |
Timeline |
TT Electronics PLC |
Samsung Electronics |
TT Electronics and Samsung Electronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with TT Electronics and Samsung Electronics
The main advantage of trading using opposite TT Electronics and Samsung Electronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if TT Electronics position performs unexpectedly, Samsung Electronics 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 Samsung Electronics will offset losses from the drop in Samsung Electronics' long position.TT Electronics vs. FONIX MOBILE PLC | TT Electronics vs. Shenandoah Telecommunications | TT Electronics vs. MOLSON RS BEVERAGE | TT Electronics vs. BOSTON BEER A |
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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