Correlation Between NYSE Composite and Locafy

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

Diversification Opportunities for NYSE Composite and Locafy

0.56
  Correlation Coefficient

Very weak diversification

The 3 months correlation between NYSE and Locafy is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Locafy Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Locafy Limited and NYSE Composite 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 NYSE Composite are associated (or correlated) with Locafy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Locafy Limited has no effect on the direction of NYSE Composite i.e., NYSE Composite and Locafy go up and down completely randomly.
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Pair Corralation between NYSE Composite and Locafy

Assuming the 90 days trading horizon NYSE Composite is expected to generate 121.4 times less return on investment than Locafy. But when comparing it to its historical volatility, NYSE Composite is 36.08 times less risky than Locafy. It trades about 0.02 of its potential returns per unit of risk. Locafy Limited is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest  1,670  in Locafy Limited on December 30, 2024 and sell it today you would lose (1,180) from holding Locafy Limited or give up 70.66% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy85.48%
ValuesDaily Returns

NYSE Composite  vs.  Locafy Limited

 Performance 
       Timeline  

NYSE Composite and Locafy Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and Locafy

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