Correlation Between Intrasense and BIO UV
Can any of the company-specific risk be diversified away by investing in both Intrasense and BIO UV 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 Intrasense and BIO UV into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Intrasense and BIO UV Group, you can compare the effects of market volatilities on Intrasense and BIO UV 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 Intrasense with a short position of BIO UV. Check out your portfolio center. Please also check ongoing floating volatility patterns of Intrasense and BIO UV.
Diversification Opportunities for Intrasense and BIO UV
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Intrasense and BIO is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Intrasense and BIO UV Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BIO UV Group and Intrasense 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 Intrasense are associated (or correlated) with BIO UV. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BIO UV Group has no effect on the direction of Intrasense i.e., Intrasense and BIO UV go up and down completely randomly.
Pair Corralation between Intrasense and BIO UV
Assuming the 90 days trading horizon Intrasense is expected to generate 2.26 times more return on investment than BIO UV. However, Intrasense is 2.26 times more volatile than BIO UV Group. It trades about 0.02 of its potential returns per unit of risk. BIO UV Group is currently generating about -0.07 per unit of risk. If you would invest 32.00 in Intrasense on September 3, 2024 and sell it today you would lose (5.00) from holding Intrasense or give up 15.62% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Intrasense vs. BIO UV Group
Performance |
| Timeline |
| Intrasense |
| BIO UV Group |
Intrasense and BIO UV Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Intrasense and BIO UV
The main advantage of trading using opposite Intrasense and BIO UV positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Intrasense position performs unexpectedly, BIO UV 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 BIO UV will offset losses from the drop in BIO UV's long position.The idea behind Intrasense and BIO UV Group pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| BIO UV vs. Veolia Environnement VE | BIO UV vs. Derichebourg | BIO UV vs. Groupe Pizzorno Environnement | BIO UV vs. Aurea SA |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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