Correlation Between SPTSX Dividend and Magna Mining

Can any of the company-specific risk be diversified away by investing in both SPTSX Dividend and Magna Mining 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 Magna Mining 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 Magna Mining, you can compare the effects of market volatilities on SPTSX Dividend and Magna Mining 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 Magna Mining. Check out your portfolio center. Please also check ongoing floating volatility patterns of SPTSX Dividend and Magna Mining.

Diversification Opportunities for SPTSX Dividend and Magna Mining

0.63

Correlation Coefficient

SPTSX Dividend  Magna Mining

Poor diversification

The 3 months correlation between SPTSX and Magna is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding SPTSX Dividend Aristocrats and Magna Mining in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Magna Mining 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 Magna Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Magna Mining has no effect on the direction of SPTSX Dividend i.e., SPTSX Dividend and Magna Mining go up and down completely randomly.

Pair Corralation between SPTSX Dividend and Magna Mining

Assuming the 90 days trading horizon SPTSX Dividend is expected to generate 5.79 times less return on investment than Magna Mining. But when comparing it to its historical volatility, SPTSX Dividend Aristocrats is 8.19 times less risky than Magna Mining. It trades about 0.2 of its potential returns per unit of risk. Magna Mining is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest  73.00  in Magna Mining on September 22, 2024 and sell it today you would earn a total of  69.00  from holding Magna Mining or generate 94.52% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	99.22%
Values	Daily Returns

SPTSX Dividend Aristocrats  vs.  Magna Mining

Pair Trading with SPTSX Dividend and Magna Mining

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

The idea behind SPTSX Dividend Aristocrats and Magna Mining 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.