Correlation Between Lotte Data and Automobile
Can any of the company-specific risk be diversified away by investing in both Lotte Data and Automobile 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 Lotte Data and Automobile into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lotte Data Communication and Automobile Pc, you can compare the effects of market volatilities on Lotte Data and Automobile 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 Lotte Data with a short position of Automobile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lotte Data and Automobile.
Diversification Opportunities for Lotte Data and Automobile
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Lotte and Automobile is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Lotte Data Communication and Automobile Pc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Automobile Pc and Lotte Data 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 Lotte Data Communication are associated (or correlated) with Automobile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Automobile Pc has no effect on the direction of Lotte Data i.e., Lotte Data and Automobile go up and down completely randomly.
Pair Corralation between Lotte Data and Automobile
Assuming the 90 days trading horizon Lotte Data Communication is expected to under-perform the Automobile. But the stock apears to be less risky and, when comparing its historical volatility, Lotte Data Communication is 1.71 times less risky than Automobile. The stock trades about -0.19 of its potential returns per unit of risk. The Automobile Pc is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 68,000 in Automobile Pc on August 28, 2024 and sell it today you would lose (600.00) from holding Automobile Pc or give up 0.88% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lotte Data Communication vs. Automobile Pc
Performance |
| Timeline |
| Lotte Data Communication |
| Automobile Pc |
Lotte Data and Automobile Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lotte Data and Automobile
The main advantage of trading using opposite Lotte Data and Automobile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lotte Data position performs unexpectedly, Automobile 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 Automobile will offset losses from the drop in Automobile's long position.| Lotte Data vs. Daeduck Electronics Co | Lotte Data vs. Anam Electronics Co | Lotte Data vs. Nable Communications | Lotte Data vs. Samwha Electronics Co |
| Automobile vs. Busan Industrial Co | Automobile vs. Busan Ind | Automobile vs. Mirae Asset Daewoo | Automobile vs. UNISEM Co |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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