Correlation Between X Financial and Lufax Holding
Can any of the company-specific risk be diversified away by investing in both X Financial and Lufax Holding 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 X Financial and Lufax Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between X Financial Class and Lufax Holding, you can compare the effects of market volatilities on X Financial and Lufax Holding 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 X Financial with a short position of Lufax Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of X Financial and Lufax Holding.
Diversification Opportunities for X Financial and Lufax Holding
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between XYF and Lufax is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding X Financial Class and Lufax Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lufax Holding and X Financial 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 X Financial Class are associated (or correlated) with Lufax Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lufax Holding has no effect on the direction of X Financial i.e., X Financial and Lufax Holding go up and down completely randomly.
Pair Corralation between X Financial and Lufax Holding
Considering the 90-day investment horizon X Financial Class is expected to generate 0.63 times more return on investment than Lufax Holding. However, X Financial Class is 1.58 times less risky than Lufax Holding. It trades about -0.03 of its potential returns per unit of risk. Lufax Holding is currently generating about -0.23 per unit of risk. If you would invest 662.00 in X Financial Class on August 27, 2024 and sell it today you would lose (12.00) from holding X Financial Class or give up 1.81% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
X Financial Class vs. Lufax Holding
Performance |
| Timeline |
| X Financial Class |
| Lufax Holding |
X Financial and Lufax Holding Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with X Financial and Lufax Holding
The main advantage of trading using opposite X Financial and Lufax Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if X Financial position performs unexpectedly, Lufax Holding 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 Lufax Holding will offset losses from the drop in Lufax Holding's long position.| X Financial vs. LM Funding America | X Financial vs. Nisun International Enterprise | X Financial vs. Qudian Inc | X Financial vs. FinVolution Group |
| Lufax Holding vs. SLM Corp | Lufax Holding vs. Orix Corp Ads | Lufax Holding vs. FirstCash | Lufax Holding vs. Medallion Financial Corp |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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