Correlation Between Auto Trader and IMPERIAL TOBACCO
Can any of the company-specific risk be diversified away by investing in both Auto Trader and IMPERIAL TOBACCO 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 Auto Trader and IMPERIAL TOBACCO into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Auto Trader Group and IMPERIAL TOBACCO , you can compare the effects of market volatilities on Auto Trader and IMPERIAL TOBACCO 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 Auto Trader with a short position of IMPERIAL TOBACCO. Check out your portfolio center. Please also check ongoing floating volatility patterns of Auto Trader and IMPERIAL TOBACCO.
Diversification Opportunities for Auto Trader and IMPERIAL TOBACCO
-0.16 | Correlation Coefficient |
Good diversification
The 3 months correlation between Auto and IMPERIAL is -0.16. Overlapping area represents the amount of risk that can be diversified away by holding Auto Trader Group and IMPERIAL TOBACCO in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on IMPERIAL TOBACCO and Auto Trader 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 Auto Trader Group are associated (or correlated) with IMPERIAL TOBACCO. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IMPERIAL TOBACCO has no effect on the direction of Auto Trader i.e., Auto Trader and IMPERIAL TOBACCO go up and down completely randomly.
Pair Corralation between Auto Trader and IMPERIAL TOBACCO
Assuming the 90 days trading horizon Auto Trader Group is expected to generate 1.42 times more return on investment than IMPERIAL TOBACCO. However, Auto Trader is 1.42 times more volatile than IMPERIAL TOBACCO . It trades about 0.05 of its potential returns per unit of risk. IMPERIAL TOBACCO is currently generating about -0.01 per unit of risk. If you would invest 875.00 in Auto Trader Group on April 20, 2025 and sell it today you would earn a total of 40.00 from holding Auto Trader Group or generate 4.57% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Auto Trader Group vs. IMPERIAL TOBACCO
Performance |
Timeline |
Auto Trader Group |
IMPERIAL TOBACCO |
Auto Trader and IMPERIAL TOBACCO Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Auto Trader and IMPERIAL TOBACCO
The main advantage of trading using opposite Auto Trader and IMPERIAL TOBACCO positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Auto Trader position performs unexpectedly, IMPERIAL TOBACCO 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 IMPERIAL TOBACCO will offset losses from the drop in IMPERIAL TOBACCO's long position.Auto Trader vs. BII Railway Transportation | Auto Trader vs. Columbia Sportswear | Auto Trader vs. Transport International Holdings | Auto Trader vs. BROADSTNET LEADL 00025 |
IMPERIAL TOBACCO vs. Apple Inc | IMPERIAL TOBACCO vs. Apple Inc | IMPERIAL TOBACCO vs. Apple Inc | IMPERIAL TOBACCO vs. Apple Inc |
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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