Correlation Between Lyc Healthcare and Dataprep Holdings
Can any of the company-specific risk be diversified away by investing in both Lyc Healthcare and Dataprep Holdings 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 Lyc Healthcare and Dataprep Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lyc Healthcare Bhd and Dataprep Holdings Bhd, you can compare the effects of market volatilities on Lyc Healthcare and Dataprep Holdings 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 Lyc Healthcare with a short position of Dataprep Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lyc Healthcare and Dataprep Holdings.
Diversification Opportunities for Lyc Healthcare and Dataprep Holdings
0.47 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Lyc and Dataprep is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding Lyc Healthcare Bhd and Dataprep Holdings Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dataprep Holdings Bhd and Lyc Healthcare 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 Lyc Healthcare Bhd are associated (or correlated) with Dataprep Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dataprep Holdings Bhd has no effect on the direction of Lyc Healthcare i.e., Lyc Healthcare and Dataprep Holdings go up and down completely randomly.
Pair Corralation between Lyc Healthcare and Dataprep Holdings
Assuming the 90 days trading horizon Lyc Healthcare Bhd is expected to generate 1.03 times more return on investment than Dataprep Holdings. However, Lyc Healthcare is 1.03 times more volatile than Dataprep Holdings Bhd. It trades about -0.05 of its potential returns per unit of risk. Dataprep Holdings Bhd is currently generating about -0.07 per unit of risk. If you would invest 11.00 in Lyc Healthcare Bhd on September 3, 2024 and sell it today you would lose (2.00) from holding Lyc Healthcare Bhd or give up 18.18% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Lyc Healthcare Bhd vs. Dataprep Holdings Bhd
Performance |
Timeline |
Lyc Healthcare Bhd |
Dataprep Holdings Bhd |
Lyc Healthcare and Dataprep Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lyc Healthcare and Dataprep Holdings
The main advantage of trading using opposite Lyc Healthcare and Dataprep Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lyc Healthcare position performs unexpectedly, Dataprep Holdings 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 Dataprep Holdings will offset losses from the drop in Dataprep Holdings' long position.Lyc Healthcare vs. YX Precious Metals | Lyc Healthcare vs. BP Plastics Holding | Lyc Healthcare vs. Alliance Financial Group | Lyc Healthcare vs. Binasat Communications Bhd |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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