Correlation Between AMS Small and IShares China

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

Diversification Opportunities for AMS Small and IShares China

0.05
  Correlation Coefficient

Significant diversification

The 3 months correlation between AMS and IShares is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding AMS Small Cap and iShares China CNY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on iShares China CNY and AMS Small 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 AMS Small Cap are associated (or correlated) with IShares China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of iShares China CNY has no effect on the direction of AMS Small i.e., AMS Small and IShares China go up and down completely randomly.
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Pair Corralation between AMS Small and IShares China

Assuming the 90 days trading horizon AMS Small Cap is expected to under-perform the IShares China. In addition to that, AMS Small is 5.13 times more volatile than iShares China CNY. It trades about -0.22 of its total potential returns per unit of risk. iShares China CNY is currently generating about 0.1 per unit of volatility. If you would invest  516.00  in iShares China CNY on February 3, 2024 and sell it today you would earn a total of  2.00  from holding iShares China CNY or generate 0.39% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

AMS Small Cap  vs.  iShares China CNY

 Performance 
       Timeline  

AMS Small and IShares China Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with AMS Small and IShares China

The main advantage of trading using opposite AMS Small and IShares China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AMS Small position performs unexpectedly, IShares China 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 IShares China will offset losses from the drop in IShares China's long position.
The idea behind AMS Small Cap and iShares China CNY 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.

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