Correlation Between Samsung Electronics and Toyota
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and Toyota 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 Samsung Electronics and Toyota into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Electronics Co and Toyota Motor Corp, you can compare the effects of market volatilities on Samsung Electronics and Toyota 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 Samsung Electronics with a short position of Toyota. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and Toyota.
Diversification Opportunities for Samsung Electronics and Toyota
-0.48 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Samsung and Toyota is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and Toyota Motor Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Toyota Motor Corp and Samsung 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 Samsung Electronics Co are associated (or correlated) with Toyota. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Toyota Motor Corp has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and Toyota go up and down completely randomly.
Pair Corralation between Samsung Electronics and Toyota
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the Toyota. But the stock apears to be less risky and, when comparing its historical volatility, Samsung Electronics Co is 1.16 times less risky than Toyota. The stock trades about -0.06 of its potential returns per unit of risk. The Toyota Motor Corp is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 273,050 in Toyota Motor Corp on November 19, 2024 and sell it today you would earn a total of 6,950 from holding Toyota Motor Corp or generate 2.55% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.39% |
Values | Daily Returns |
Samsung Electronics Co vs. Toyota Motor Corp
Performance |
Timeline |
Samsung Electronics |
Toyota Motor Corp |
Samsung Electronics and Toyota Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and Toyota
The main advantage of trading using opposite Samsung Electronics and Toyota positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, Toyota 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 Toyota will offset losses from the drop in Toyota's long position.Samsung Electronics vs. United Internet AG | Samsung Electronics vs. Zoom Video Communications | Samsung Electronics vs. Take Two Interactive Software | Samsung Electronics vs. Spirent Communications plc |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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