Correlation Between AGRICUL BK and EssilorLuxottica
Can any of the company-specific risk be diversified away by investing in both AGRICUL BK and EssilorLuxottica 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 AGRICUL BK and EssilorLuxottica into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AGRICUL BK CHINA H and EssilorLuxottica Socit anonyme, you can compare the effects of market volatilities on AGRICUL BK and EssilorLuxottica 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 AGRICUL BK with a short position of EssilorLuxottica. Check out your portfolio center. Please also check ongoing floating volatility patterns of AGRICUL BK and EssilorLuxottica.
Diversification Opportunities for AGRICUL BK and EssilorLuxottica
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between AGRICUL and EssilorLuxottica is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding AGRICUL BK CHINA H and EssilorLuxottica Socit anonyme in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on EssilorLuxottica Socit and AGRICUL BK 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 AGRICUL BK CHINA H are associated (or correlated) with EssilorLuxottica. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EssilorLuxottica Socit has no effect on the direction of AGRICUL BK i.e., AGRICUL BK and EssilorLuxottica go up and down completely randomly.
Pair Corralation between AGRICUL BK and EssilorLuxottica
Assuming the 90 days trading horizon AGRICUL BK is expected to generate 17.36 times less return on investment than EssilorLuxottica. In addition to that, AGRICUL BK is 1.41 times more volatile than EssilorLuxottica Socit anonyme. It trades about 0.01 of its total potential returns per unit of risk. EssilorLuxottica Socit anonyme is currently generating about 0.24 per unit of volatility. If you would invest 21,950 in EssilorLuxottica Socit anonyme on August 26, 2024 and sell it today you would earn a total of 1,660 from holding EssilorLuxottica Socit anonyme or generate 7.56% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
AGRICUL BK CHINA H vs. EssilorLuxottica Socit anonyme
Performance |
| Timeline |
| AGRICUL BK CHINA |
| EssilorLuxottica Socit |
AGRICUL BK and EssilorLuxottica Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with AGRICUL BK and EssilorLuxottica
The main advantage of trading using opposite AGRICUL BK and EssilorLuxottica positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AGRICUL BK position performs unexpectedly, EssilorLuxottica 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 EssilorLuxottica will offset losses from the drop in EssilorLuxottica's long position.| AGRICUL BK vs. Strategic Investments AS | AGRICUL BK vs. Apollo Investment Corp | AGRICUL BK vs. REGAL ASIAN INVESTMENTS | AGRICUL BK vs. HK Electric Investments |
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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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