Correlation Between Okta and BMO Equal
Can any of the company-specific risk be diversified away by investing in both Okta and BMO Equal 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 Okta and BMO Equal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Okta Inc and BMO Equal Weight, you can compare the effects of market volatilities on Okta and BMO Equal 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 Okta with a short position of BMO Equal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Okta and BMO Equal.
Diversification Opportunities for Okta and BMO Equal
Average diversification
The 3 months correlation between Okta and BMO is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Okta Inc and BMO Equal Weight in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BMO Equal Weight and Okta 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 Okta Inc are associated (or correlated) with BMO Equal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BMO Equal Weight has no effect on the direction of Okta i.e., Okta and BMO Equal go up and down completely randomly.
Pair Corralation between Okta and BMO Equal
Given the investment horizon of 90 days Okta is expected to generate 1.67 times less return on investment than BMO Equal. But when comparing it to its historical volatility, Okta Inc is 1.62 times less risky than BMO Equal. It trades about 0.22 of its potential returns per unit of risk. BMO Equal Weight is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 3,485 in BMO Equal Weight on September 1, 2024 and sell it today you would earn a total of 509.00 from holding BMO Equal Weight or generate 14.61% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 91.3% |
| Values | Daily Returns |
Okta Inc vs. BMO Equal Weight
Performance |
| Timeline |
| Okta Inc |
| BMO Equal Weight |
Okta and BMO Equal Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Okta and BMO Equal
The main advantage of trading using opposite Okta and BMO Equal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Okta position performs unexpectedly, BMO Equal 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 BMO Equal will offset losses from the drop in BMO Equal's long position.The idea behind Okta Inc and BMO Equal Weight 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.| BMO Equal vs. BMO Canadian Dividend | BMO Equal vs. BMO Covered Call | BMO Equal vs. BMO Canadian High | BMO Equal vs. BMO NASDAQ 100 |
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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