Correlation Between Keyang Electric and KG Eco
Can any of the company-specific risk be diversified away by investing in both Keyang Electric and KG Eco 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 Keyang Electric and KG Eco into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Keyang Electric Machinery and KG Eco Technology, you can compare the effects of market volatilities on Keyang Electric and KG Eco 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 Keyang Electric with a short position of KG Eco. Check out your portfolio center. Please also check ongoing floating volatility patterns of Keyang Electric and KG Eco.
Diversification Opportunities for Keyang Electric and KG Eco
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Keyang and 151860 is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Keyang Electric Machinery and KG Eco Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KG Eco Technology and Keyang Electric 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 Keyang Electric Machinery are associated (or correlated) with KG Eco. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KG Eco Technology has no effect on the direction of Keyang Electric i.e., Keyang Electric and KG Eco go up and down completely randomly.
Pair Corralation between Keyang Electric and KG Eco
Assuming the 90 days trading horizon Keyang Electric Machinery is expected to generate 0.63 times more return on investment than KG Eco. However, Keyang Electric Machinery is 1.59 times less risky than KG Eco. It trades about -0.02 of its potential returns per unit of risk. KG Eco Technology is currently generating about -0.02 per unit of risk. If you would invest 564,154 in Keyang Electric Machinery on October 13, 2024 and sell it today you would lose (155,154) from holding Keyang Electric Machinery or give up 27.5% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 99.79% |
| Values | Daily Returns |
Keyang Electric Machinery vs. KG Eco Technology
Performance |
| Timeline |
| Keyang Electric Machinery |
| KG Eco Technology |
Keyang Electric and KG Eco Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Keyang Electric and KG Eco
The main advantage of trading using opposite Keyang Electric and KG Eco positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Keyang Electric position performs unexpectedly, KG Eco 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 KG Eco will offset losses from the drop in KG Eco's long position.| Keyang Electric vs. Busan Industrial Co | Keyang Electric vs. Busan Ind | Keyang Electric vs. UNISEM Co | Keyang Electric vs. RPBio Inc |
| KG Eco vs. ENERGYMACHINERY KOREA CoLtd | KG Eco vs. KEPCO Engineering Construction | KG Eco vs. Keyang Electric Machinery | KG Eco vs. Bosung Power Technology |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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