Correlation Between Bank of America and AI/ML Innovations
Can any of the company-specific risk be diversified away by investing in both Bank of America and AI/ML Innovations 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 Bank of America and AI/ML Innovations into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of America and AIML Innovations, you can compare the effects of market volatilities on Bank of America and AI/ML Innovations 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 Bank of America with a short position of AI/ML Innovations. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and AI/ML Innovations.
Diversification Opportunities for Bank of America and AI/ML Innovations
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between Bank and AI/ML is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and AIML Innovations in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AI/ML Innovations and Bank of America 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 Bank of America are associated (or correlated) with AI/ML Innovations. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AI/ML Innovations has no effect on the direction of Bank of America i.e., Bank of America and AI/ML Innovations go up and down completely randomly.
Pair Corralation between Bank of America and AI/ML Innovations
Considering the 90-day investment horizon Bank of America is expected to generate 9.68 times less return on investment than AI/ML Innovations. But when comparing it to its historical volatility, Bank of America is 8.95 times less risky than AI/ML Innovations. It trades about 0.1 of its potential returns per unit of risk. AIML Innovations is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 3.22 in AIML Innovations on September 1, 2024 and sell it today you would earn a total of 3.38 from holding AIML Innovations or generate 104.97% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.21% |
Values | Daily Returns |
Bank of America vs. AIML Innovations
Performance |
Timeline |
Bank of America |
AI/ML Innovations |
Bank of America and AI/ML Innovations Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and AI/ML Innovations
The main advantage of trading using opposite Bank of America and AI/ML Innovations positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, AI/ML Innovations 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 AI/ML Innovations will offset losses from the drop in AI/ML Innovations' long position.Bank of America vs. Citigroup | Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal |
AI/ML Innovations vs. GE HealthCare Technologies | AI/ML Innovations vs. Veeva Systems Class | AI/ML Innovations vs. Solventum Corp | AI/ML Innovations vs. Doximity |
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.
Other Complementary Tools
Commodity Channel Use Commodity Channel Index to analyze current equity momentum | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
Portfolio Rebalancing Analyze risk-adjusted returns against different time horizons to find asset-allocation targets | |
Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
USA ETFs Find actively traded Exchange Traded Funds (ETF) in USA |