Correlation Between Flora Growth and China SXT
Can any of the company-specific risk be diversified away by investing in both Flora Growth and China SXT 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 Flora Growth and China SXT into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Flora Growth Corp and China SXT Pharmaceuticals, you can compare the effects of market volatilities on Flora Growth and China SXT 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 Flora Growth with a short position of China SXT. Check out your portfolio center. Please also check ongoing floating volatility patterns of Flora Growth and China SXT.
Diversification Opportunities for Flora Growth and China SXT
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Flora and China is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Flora Growth Corp and China SXT Pharmaceuticals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China SXT Pharmaceuticals and Flora Growth 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 Flora Growth Corp are associated (or correlated) with China SXT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China SXT Pharmaceuticals has no effect on the direction of Flora Growth i.e., Flora Growth and China SXT go up and down completely randomly.
Pair Corralation between Flora Growth and China SXT
Given the investment horizon of 90 days Flora Growth Corp is expected to generate 0.96 times more return on investment than China SXT. However, Flora Growth Corp is 1.04 times less risky than China SXT. It trades about 0.0 of its potential returns per unit of risk. China SXT Pharmaceuticals is currently generating about -0.04 per unit of risk. If you would invest 890.00 in Flora Growth Corp on August 29, 2024 and sell it today you would lose (733.00) from holding Flora Growth Corp or give up 82.36% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Flora Growth Corp vs. China SXT Pharmaceuticals
Performance |
| Timeline |
| Flora Growth Corp |
| China SXT Pharmaceuticals |
Flora Growth and China SXT Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Flora Growth and China SXT
The main advantage of trading using opposite Flora Growth and China SXT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Flora Growth position performs unexpectedly, China SXT 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 China SXT will offset losses from the drop in China SXT's long position.| Flora Growth vs. Phibro Animal Health | Flora Growth vs. Procaps Group SA | Flora Growth vs. Amphastar P | Flora Growth vs. Alkermes Plc |
| China SXT vs. Akanda Corp | China SXT vs. Petros Pharmaceuticals | China SXT vs. GelStat Corp | China SXT vs. Shuttle Pharmaceuticals |
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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