Correlation Between Famous Brands and CA Sales
Can any of the company-specific risk be diversified away by investing in both Famous Brands and CA Sales 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 Famous Brands and CA Sales into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Famous Brands and CA Sales Holdings, you can compare the effects of market volatilities on Famous Brands and CA Sales 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 Famous Brands with a short position of CA Sales. Check out your portfolio center. Please also check ongoing floating volatility patterns of Famous Brands and CA Sales.
Diversification Opportunities for Famous Brands and CA Sales
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Famous and CAA is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Famous Brands and CA Sales Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CA Sales Holdings and Famous Brands 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 Famous Brands are associated (or correlated) with CA Sales. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CA Sales Holdings has no effect on the direction of Famous Brands i.e., Famous Brands and CA Sales go up and down completely randomly.
Pair Corralation between Famous Brands and CA Sales
Assuming the 90 days trading horizon Famous Brands is expected to under-perform the CA Sales. But the stock apears to be less risky and, when comparing its historical volatility, Famous Brands is 1.87 times less risky than CA Sales. The stock trades about -0.17 of its potential returns per unit of risk. The CA Sales Holdings is currently generating about -0.05 of returns per unit of risk over similar time horizon. If you would invest 161,600 in CA Sales Holdings on October 9, 2024 and sell it today you would lose (4,800) from holding CA Sales Holdings or give up 2.97% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Famous Brands vs. CA Sales Holdings
Performance |
Timeline |
Famous Brands |
CA Sales Holdings |
Famous Brands and CA Sales Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Famous Brands and CA Sales
The main advantage of trading using opposite Famous Brands and CA Sales positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Famous Brands position performs unexpectedly, CA Sales 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 CA Sales will offset losses from the drop in CA Sales' long position.Famous Brands vs. AfroCentric Investment Corp | Famous Brands vs. Frontier Transport Holdings | Famous Brands vs. Safari Investments RSA | Famous Brands vs. City Lodge Hotels |
CA Sales vs. AfroCentric Investment Corp | CA Sales vs. Ascendis Health | CA Sales vs. Kumba Iron Ore | CA Sales vs. Deneb Investments |
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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