Correlation Between Financial Street and Jinlong Machinery
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By analyzing existing cross correlation between Financial Street Holdings and Jinlong Machinery Electronic, you can compare the effects of market volatilities on Financial Street and Jinlong Machinery 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 Financial Street with a short position of Jinlong Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of Financial Street and Jinlong Machinery.
Diversification Opportunities for Financial Street and Jinlong Machinery
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Financial and Jinlong is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Financial Street Holdings and Jinlong Machinery Electronic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jinlong Machinery and Financial Street 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 Financial Street Holdings are associated (or correlated) with Jinlong Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jinlong Machinery has no effect on the direction of Financial Street i.e., Financial Street and Jinlong Machinery go up and down completely randomly.
Pair Corralation between Financial Street and Jinlong Machinery
Assuming the 90 days trading horizon Financial Street Holdings is expected to under-perform the Jinlong Machinery. But the stock apears to be less risky and, when comparing its historical volatility, Financial Street Holdings is 1.44 times less risky than Jinlong Machinery. The stock trades about -0.03 of its potential returns per unit of risk. The Jinlong Machinery Electronic is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 520.00 in Jinlong Machinery Electronic on October 11, 2024 and sell it today you would lose (82.00) from holding Jinlong Machinery Electronic or give up 15.77% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Financial Street Holdings vs. Jinlong Machinery Electronic
Performance |
| Timeline |
| Financial Street Holdings |
| Jinlong Machinery |
Financial Street and Jinlong Machinery Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Financial Street and Jinlong Machinery
The main advantage of trading using opposite Financial Street and Jinlong Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Financial Street position performs unexpectedly, Jinlong Machinery 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 Jinlong Machinery will offset losses from the drop in Jinlong Machinery's long position.| Financial Street vs. Henan Shuanghui Investment | Financial Street vs. Jiujiang Shanshui Technology | Financial Street vs. INKON Life Technology | Financial Street vs. Shanghai Material Trading |
| Jinlong Machinery vs. Financial Street Holdings | Jinlong Machinery vs. Ping An Insurance | Jinlong Machinery vs. Panda Financial Holding | Jinlong Machinery vs. GRG Banking Equipment |
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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