Correlation Between Atlas Insurance and National Foods
Can any of the company-specific risk be diversified away by investing in both Atlas Insurance and National Foods 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 Atlas Insurance and National Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Atlas Insurance and National Foods, you can compare the effects of market volatilities on Atlas Insurance and National Foods 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 Atlas Insurance with a short position of National Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Atlas Insurance and National Foods.
Diversification Opportunities for Atlas Insurance and National Foods
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Atlas and National is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Atlas Insurance and National Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on National Foods and Atlas Insurance 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 Atlas Insurance are associated (or correlated) with National Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of National Foods has no effect on the direction of Atlas Insurance i.e., Atlas Insurance and National Foods go up and down completely randomly.
Pair Corralation between Atlas Insurance and National Foods
Assuming the 90 days trading horizon Atlas Insurance is expected to generate 2.14 times more return on investment than National Foods. However, Atlas Insurance is 2.14 times more volatile than National Foods. It trades about 0.0 of its potential returns per unit of risk. National Foods is currently generating about -0.26 per unit of risk. If you would invest 5,819 in Atlas Insurance on November 7, 2024 and sell it today you would lose (18.00) from holding Atlas Insurance or give up 0.31% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Atlas Insurance vs. National Foods
Performance |
| Timeline |
| Atlas Insurance |
| National Foods |
Atlas Insurance and National Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Atlas Insurance and National Foods
The main advantage of trading using opposite Atlas Insurance and National Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Atlas Insurance position performs unexpectedly, National Foods 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 National Foods will offset losses from the drop in National Foods' long position.| Atlas Insurance vs. Masood Textile Mills | Atlas Insurance vs. Fauji Foods | Atlas Insurance vs. KSB Pumps | Atlas Insurance vs. Mari Petroleum |
| National Foods vs. Packages | National Foods vs. Fauji Foods | National Foods vs. The Organic Meat | National Foods vs. WorldCall Telecom |
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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