Correlation Between SPASX Dividend and ALS

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

Diversification Opportunities for SPASX Dividend and ALS

-0.02
  Correlation Coefficient

Good diversification

The 3 months correlation between SPASX and ALS is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding SPASX Dividend Opportunities and ALS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ALS and SPASX 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 SPASX Dividend Opportunities are associated (or correlated) with ALS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ALS has no effect on the direction of SPASX Dividend i.e., SPASX Dividend and ALS go up and down completely randomly.
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Pair Corralation between SPASX Dividend and ALS

Assuming the 90 days trading horizon SPASX Dividend is expected to generate 4.8 times less return on investment than ALS. But when comparing it to its historical volatility, SPASX Dividend Opportunities is 2.32 times less risky than ALS. It trades about 0.05 of its potential returns per unit of risk. ALS is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest  1,047  in ALS on September 1, 2024 and sell it today you would earn a total of  548.00  from holding ALS or generate 52.34% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy99.63%
ValuesDaily Returns

SPASX Dividend Opportunities  vs.  ALS

 Performance 
       Timeline  

SPASX Dividend and ALS Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with SPASX Dividend and ALS

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

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