Correlation Between ANGANG STEEL and Pure Storage
Can any of the company-specific risk be diversified away by investing in both ANGANG STEEL and Pure Storage 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 ANGANG STEEL and Pure Storage into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ANGANG STEEL H and Pure Storage, you can compare the effects of market volatilities on ANGANG STEEL and Pure Storage 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 ANGANG STEEL with a short position of Pure Storage. Check out your portfolio center. Please also check ongoing floating volatility patterns of ANGANG STEEL and Pure Storage.
Diversification Opportunities for ANGANG STEEL and Pure Storage
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between ANGANG and Pure is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding ANGANG STEEL H and Pure Storage in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pure Storage and ANGANG STEEL 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 ANGANG STEEL H are associated (or correlated) with Pure Storage. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pure Storage has no effect on the direction of ANGANG STEEL i.e., ANGANG STEEL and Pure Storage go up and down completely randomly.
Pair Corralation between ANGANG STEEL and Pure Storage
Assuming the 90 days trading horizon ANGANG STEEL H is expected to generate 1.21 times more return on investment than Pure Storage. However, ANGANG STEEL is 1.21 times more volatile than Pure Storage. It trades about 0.09 of its potential returns per unit of risk. Pure Storage is currently generating about 0.08 per unit of risk. If you would invest 13.00 in ANGANG STEEL H on November 3, 2024 and sell it today you would earn a total of 6.00 from holding ANGANG STEEL H or generate 46.15% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
ANGANG STEEL H vs. Pure Storage
Performance |
| Timeline |
| ANGANG STEEL H |
| Pure Storage |
ANGANG STEEL and Pure Storage Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ANGANG STEEL and Pure Storage
The main advantage of trading using opposite ANGANG STEEL and Pure Storage positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ANGANG STEEL position performs unexpectedly, Pure Storage 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 Pure Storage will offset losses from the drop in Pure Storage's long position.| ANGANG STEEL vs. G III Apparel Group | ANGANG STEEL vs. BORR DRILLING NEW | ANGANG STEEL vs. CN MODERN DAIRY | ANGANG STEEL vs. SENECA FOODS A |
| Pure Storage vs. ARDAGH METAL PACDL 0001 | Pure Storage vs. Zijin Mining Group | Pure Storage vs. MAGNUM MINING EXP | Pure Storage vs. Jacquet Metal Service |
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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