Correlation Between TAMBANG BATUBARA-B- and Lithia Motors
Can any of the company-specific risk be diversified away by investing in both TAMBANG BATUBARA-B- and Lithia Motors 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 TAMBANG BATUBARA-B- and Lithia Motors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between TAMBANG BATUBARA B and Lithia Motors, you can compare the effects of market volatilities on TAMBANG BATUBARA-B- and Lithia Motors 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 TAMBANG BATUBARA-B- with a short position of Lithia Motors. Check out your portfolio center. Please also check ongoing floating volatility patterns of TAMBANG BATUBARA-B- and Lithia Motors.
Diversification Opportunities for TAMBANG BATUBARA-B- and Lithia Motors
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between TAMBANG and Lithia is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding TAMBANG BATUBARA B and Lithia Motors in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lithia Motors and TAMBANG BATUBARA-B- 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 TAMBANG BATUBARA B are associated (or correlated) with Lithia Motors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lithia Motors has no effect on the direction of TAMBANG BATUBARA-B- i.e., TAMBANG BATUBARA-B- and Lithia Motors go up and down completely randomly.
Pair Corralation between TAMBANG BATUBARA-B- and Lithia Motors
Assuming the 90 days trading horizon TAMBANG BATUBARA B is expected to under-perform the Lithia Motors. But the stock apears to be less risky and, when comparing its historical volatility, TAMBANG BATUBARA B is 1.6 times less risky than Lithia Motors. The stock trades about -0.18 of its potential returns per unit of risk. The Lithia Motors is currently generating about -0.1 of returns per unit of risk over similar time horizon. If you would invest 36,800 in Lithia Motors on December 3, 2024 and sell it today you would lose (3,800) from holding Lithia Motors or give up 10.33% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
TAMBANG BATUBARA B vs. Lithia Motors
Performance |
Timeline |
TAMBANG BATUBARA-B- |
Lithia Motors |
TAMBANG BATUBARA-B- and Lithia Motors Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with TAMBANG BATUBARA-B- and Lithia Motors
The main advantage of trading using opposite TAMBANG BATUBARA-B- and Lithia Motors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if TAMBANG BATUBARA-B- position performs unexpectedly, Lithia Motors 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 Lithia Motors will offset losses from the drop in Lithia Motors' long position.TAMBANG BATUBARA-B- vs. Gladstone Investment | TAMBANG BATUBARA-B- vs. ATRESMEDIA | TAMBANG BATUBARA-B- vs. MidCap Financial Investment | TAMBANG BATUBARA-B- vs. ZINC MEDIA GR |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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