Correlation Between Bicycle Therapeutics and IGM Biosciences
Can any of the company-specific risk be diversified away by investing in both Bicycle Therapeutics and IGM Biosciences 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 Bicycle Therapeutics and IGM Biosciences into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bicycle Therapeutics and IGM Biosciences, you can compare the effects of market volatilities on Bicycle Therapeutics and IGM Biosciences 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 Bicycle Therapeutics with a short position of IGM Biosciences. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bicycle Therapeutics and IGM Biosciences.
Diversification Opportunities for Bicycle Therapeutics and IGM Biosciences
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bicycle and IGM is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Bicycle Therapeutics and IGM Biosciences in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on IGM Biosciences and Bicycle Therapeutics 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 Bicycle Therapeutics are associated (or correlated) with IGM Biosciences. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IGM Biosciences has no effect on the direction of Bicycle Therapeutics i.e., Bicycle Therapeutics and IGM Biosciences go up and down completely randomly.
Pair Corralation between Bicycle Therapeutics and IGM Biosciences
Given the investment horizon of 90 days Bicycle Therapeutics is expected to generate 0.46 times more return on investment than IGM Biosciences. However, Bicycle Therapeutics is 2.15 times less risky than IGM Biosciences. It trades about -0.28 of its potential returns per unit of risk. IGM Biosciences is currently generating about -0.43 per unit of risk. If you would invest 2,403 in Bicycle Therapeutics on August 31, 2024 and sell it today you would lose (363.00) from holding Bicycle Therapeutics or give up 15.11% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bicycle Therapeutics vs. IGM Biosciences
Performance |
Timeline |
Bicycle Therapeutics |
IGM Biosciences |
Bicycle Therapeutics and IGM Biosciences Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bicycle Therapeutics and IGM Biosciences
The main advantage of trading using opposite Bicycle Therapeutics and IGM Biosciences positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bicycle Therapeutics position performs unexpectedly, IGM Biosciences 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 IGM Biosciences will offset losses from the drop in IGM Biosciences' long position.Bicycle Therapeutics vs. Ideaya Biosciences | Bicycle Therapeutics vs. AnaptysBio | Bicycle Therapeutics vs. MeiraGTx Holdings PLC | Bicycle Therapeutics vs. Keros Therapeutics |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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