Correlation Between Song Hong and Plastic Additives
Can any of the company-specific risk be diversified away by investing in both Song Hong and Plastic Additives 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 Song Hong and Plastic Additives into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Song Hong Garment and Plastic Additives JSC, you can compare the effects of market volatilities on Song Hong and Plastic Additives 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 Song Hong with a short position of Plastic Additives. Check out your portfolio center. Please also check ongoing floating volatility patterns of Song Hong and Plastic Additives.
Diversification Opportunities for Song Hong and Plastic Additives
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Song and Plastic is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Song Hong Garment and Plastic Additives JSC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Plastic Additives JSC and Song Hong 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 Song Hong Garment are associated (or correlated) with Plastic Additives. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Plastic Additives JSC has no effect on the direction of Song Hong i.e., Song Hong and Plastic Additives go up and down completely randomly.
Pair Corralation between Song Hong and Plastic Additives
Assuming the 90 days trading horizon Song Hong Garment is expected to generate 0.59 times more return on investment than Plastic Additives. However, Song Hong Garment is 1.7 times less risky than Plastic Additives. It trades about 0.06 of its potential returns per unit of risk. Plastic Additives JSC is currently generating about 0.03 per unit of risk. If you would invest 2,907,043 in Song Hong Garment on September 2, 2024 and sell it today you would earn a total of 2,012,957 from holding Song Hong Garment or generate 69.24% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 96.15% |
| Values | Daily Returns |
Song Hong Garment vs. Plastic Additives JSC
Performance |
| Timeline |
| Song Hong Garment |
| Plastic Additives JSC |
Song Hong and Plastic Additives Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Song Hong and Plastic Additives
The main advantage of trading using opposite Song Hong and Plastic Additives positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Song Hong position performs unexpectedly, Plastic Additives 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 Plastic Additives will offset losses from the drop in Plastic Additives' long position.| Song Hong vs. FIT INVEST JSC | Song Hong vs. Damsan JSC | Song Hong vs. An Phat Plastic | Song Hong vs. Alphanam ME |
| Plastic Additives vs. Song Hong Garment | Plastic Additives vs. Alphanam ME | Plastic Additives vs. Hochiminh City Metal | Plastic Additives vs. Atesco Industrial Cartering |
Check out your portfolio center.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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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