Correlation Between BCE and Pinterest
Can any of the company-specific risk be diversified away by investing in both BCE and Pinterest 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 BCE and Pinterest into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BCE Inc and Pinterest, you can compare the effects of market volatilities on BCE and Pinterest 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 BCE with a short position of Pinterest. Check out your portfolio center. Please also check ongoing floating volatility patterns of BCE and Pinterest.
Diversification Opportunities for BCE and Pinterest
Modest diversification
The 3 months correlation between BCE and Pinterest is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding BCE Inc and Pinterest in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pinterest and BCE 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 BCE Inc are associated (or correlated) with Pinterest. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pinterest has no effect on the direction of BCE i.e., BCE and Pinterest go up and down completely randomly.
Pair Corralation between BCE and Pinterest
Considering the 90-day investment horizon BCE Inc is expected to under-perform the Pinterest. But the stock apears to be less risky and, when comparing its historical volatility, BCE Inc is 1.64 times less risky than Pinterest. The stock trades about -0.24 of its potential returns per unit of risk. The Pinterest is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 3,131 in Pinterest on September 2, 2024 and sell it today you would lose (99.00) from holding Pinterest or give up 3.16% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
BCE Inc vs. Pinterest
Performance |
Timeline |
BCE Inc |
BCE and Pinterest Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BCE and Pinterest
The main advantage of trading using opposite BCE and Pinterest positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BCE position performs unexpectedly, Pinterest 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 Pinterest will offset losses from the drop in Pinterest's long position.The idea behind BCE Inc and Pinterest 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.Pinterest vs. MediaAlpha | Pinterest vs. Asset Entities Class | Pinterest vs. Shutterstock | Pinterest vs. Match Group |
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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