Correlation Between HNX 30 and Song Hong

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Can any of the company-specific risk be diversified away by investing in both HNX 30 and Song Hong 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 HNX 30 and Song Hong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HNX 30 and Song Hong Garment, you can compare the effects of market volatilities on HNX 30 and Song Hong 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 HNX 30 with a short position of Song Hong. Check out your portfolio center. Please also check ongoing floating volatility patterns of HNX 30 and Song Hong.

Diversification Opportunities for HNX 30 and Song Hong

-0.2
  Correlation Coefficient

Good diversification

The 3 months correlation between HNX and Song is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding HNX 30 and Song Hong Garment in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Song Hong Garment and HNX 30 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 HNX 30 are associated (or correlated) with Song Hong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Song Hong Garment has no effect on the direction of HNX 30 i.e., HNX 30 and Song Hong go up and down completely randomly.
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Pair Corralation between HNX 30 and Song Hong

Assuming the 90 days trading horizon HNX 30 is expected to under-perform the Song Hong. But the index apears to be less risky and, when comparing its historical volatility, HNX 30 is 1.33 times less risky than Song Hong. The index trades about -0.02 of its potential returns per unit of risk. The Song Hong Garment is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest  4,000,000  in Song Hong Garment on August 27, 2024 and sell it today you would earn a total of  1,290,000  from holding Song Hong Garment or generate 32.25% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy98.93%
ValuesDaily Returns

HNX 30  vs.  Song Hong Garment

 Performance 
       Timeline  

HNX 30 and Song Hong Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with HNX 30 and Song Hong

The main advantage of trading using opposite HNX 30 and Song Hong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HNX 30 position performs unexpectedly, Song Hong 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 Song Hong will offset losses from the drop in Song Hong's long position.
The idea behind HNX 30 and Song Hong Garment 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 Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.

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