Correlation Between SanDi Properties and Kwong Fong
Can any of the company-specific risk be diversified away by investing in both SanDi Properties and Kwong Fong 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 SanDi Properties and Kwong Fong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SanDi Properties Co and Kwong Fong Industries, you can compare the effects of market volatilities on SanDi Properties and Kwong Fong 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 SanDi Properties with a short position of Kwong Fong. Check out your portfolio center. Please also check ongoing floating volatility patterns of SanDi Properties and Kwong Fong.
Diversification Opportunities for SanDi Properties and Kwong Fong
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between SanDi and Kwong is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding SanDi Properties Co and Kwong Fong Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kwong Fong Industries and SanDi Properties 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 SanDi Properties Co are associated (or correlated) with Kwong Fong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kwong Fong Industries has no effect on the direction of SanDi Properties i.e., SanDi Properties and Kwong Fong go up and down completely randomly.
Pair Corralation between SanDi Properties and Kwong Fong
Assuming the 90 days trading horizon SanDi Properties Co is expected to generate 1.87 times more return on investment than Kwong Fong. However, SanDi Properties is 1.87 times more volatile than Kwong Fong Industries. It trades about -0.08 of its potential returns per unit of risk. Kwong Fong Industries is currently generating about -0.19 per unit of risk. If you would invest 6,040 in SanDi Properties Co on August 31, 2024 and sell it today you would lose (350.00) from holding SanDi Properties Co or give up 5.79% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.65% |
| Values | Daily Returns |
SanDi Properties Co vs. Kwong Fong Industries
Performance |
| Timeline |
| SanDi Properties |
| Kwong Fong Industries |
SanDi Properties and Kwong Fong Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SanDi Properties and Kwong Fong
The main advantage of trading using opposite SanDi Properties and Kwong Fong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SanDi Properties position performs unexpectedly, Kwong Fong 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 Kwong Fong will offset losses from the drop in Kwong Fong's long position.| SanDi Properties vs. Advancetek Enterprise Co | SanDi Properties vs. I Hwa Industrial Co | SanDi Properties vs. Carnival Industrial Corp | SanDi Properties vs. Tung Ho Textile |
| Kwong Fong vs. Chaintech Technology Corp | Kwong Fong vs. AVerMedia Technologies | Kwong Fong vs. Avision | Kwong Fong vs. Clevo Co |
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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