Correlation Between CBOE SP and Cedar Realty

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Can any of the company-specific risk be diversified away by investing in both CBOE SP and Cedar Realty 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 CBOE SP and Cedar Realty into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CBOE SP 500 and Cedar Realty Trust, you can compare the effects of market volatilities on CBOE SP and Cedar Realty 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 CBOE SP with a short position of Cedar Realty. Check out your portfolio center. Please also check ongoing floating volatility patterns of CBOE SP and Cedar Realty.

Diversification Opportunities for CBOE SP and Cedar Realty

0.21
  Correlation Coefficient

Modest diversification

The 3 months correlation between CBOE and Cedar is 0.21. Overlapping area represents the amount of risk that can be diversified away by holding CBOE SP 500 and Cedar Realty Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cedar Realty Trust and CBOE SP 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 CBOE SP 500 are associated (or correlated) with Cedar Realty. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cedar Realty Trust has no effect on the direction of CBOE SP i.e., CBOE SP and Cedar Realty go up and down completely randomly.
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Pair Corralation between CBOE SP and Cedar Realty

Assuming the 90 days trading horizon CBOE SP is expected to generate 1.56 times less return on investment than Cedar Realty. But when comparing it to its historical volatility, CBOE SP 500 is 4.76 times less risky than Cedar Realty. It trades about 0.12 of its potential returns per unit of risk. Cedar Realty Trust is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest  1,198  in Cedar Realty Trust on October 23, 2024 and sell it today you would earn a total of  387.00  from holding Cedar Realty Trust or generate 32.3% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

CBOE SP 500  vs.  Cedar Realty Trust

 Performance 
       Timeline  

CBOE SP and Cedar Realty Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with CBOE SP and Cedar Realty

The main advantage of trading using opposite CBOE SP and Cedar Realty positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CBOE SP position performs unexpectedly, Cedar Realty 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 Cedar Realty will offset losses from the drop in Cedar Realty's long position.
The idea behind CBOE SP 500 and Cedar Realty Trust 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.
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.

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