Correlation Between SPTSX Dividend and PX Prague

Can any of the company-specific risk be diversified away by investing in both SPTSX Dividend and PX Prague 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 SPTSX Dividend and PX Prague into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between SPTSX Dividend Aristocrats and PX Prague Stock, you can compare the effects of market volatilities on SPTSX Dividend and PX Prague 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 SPTSX Dividend with a short position of PX Prague. Check out your portfolio center. Please also check ongoing floating volatility patterns of SPTSX Dividend and PX Prague.

Diversification Opportunities for SPTSX Dividend and PX Prague

0.78

Correlation Coefficient

SPTSX Dividend  PX Prague

Poor diversification

The 3 months correlation between SPTSX and PX Prague is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding SPTSX Dividend Aristocrats and PX Prague Stock in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PX Prague Stock and SPTSX Dividend 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 SPTSX Dividend Aristocrats are associated (or correlated) with PX Prague. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PX Prague Stock has no effect on the direction of SPTSX Dividend i.e., SPTSX Dividend and PX Prague go up and down completely randomly.

Pair Corralation between SPTSX Dividend and PX Prague

Assuming the 90 days trading horizon SPTSX Dividend Aristocrats is expected to generate 0.94 times more return on investment than PX Prague. However, SPTSX Dividend Aristocrats is 1.07 times less risky than PX Prague. It trades about 0.37 of its potential returns per unit of risk. PX Prague Stock is currently generating about 0.16 per unit of risk. If you would invest  33,984  in SPTSX Dividend Aristocrats on September 1, 2024 and sell it today you would earn a total of  3,587  from holding SPTSX Dividend Aristocrats or generate 10.55% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	98.44%
Values	Daily Returns

SPTSX Dividend Aristocrats  vs.  PX Prague Stock

Pair Trading with SPTSX Dividend and PX Prague

The main advantage of trading using opposite SPTSX Dividend and PX Prague positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SPTSX Dividend position performs unexpectedly, PX Prague 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 PX Prague will offset losses from the drop in PX Prague's long position.

The idea behind SPTSX Dividend Aristocrats and PX Prague Stock 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.