Correlation Between HK Electric and Food Life
Can any of the company-specific risk be diversified away by investing in both HK Electric and Food Life 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 HK Electric and Food Life into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HK Electric Investments and Food Life Companies, you can compare the effects of market volatilities on HK Electric and Food Life 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 HK Electric with a short position of Food Life. Check out your portfolio center. Please also check ongoing floating volatility patterns of HK Electric and Food Life.
Diversification Opportunities for HK Electric and Food Life
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between HKT and Food is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding HK Electric Investments and Food Life Companies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Food Life Companies and HK 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 HK Electric Investments are associated (or correlated) with Food Life. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Food Life Companies has no effect on the direction of HK Electric i.e., HK Electric and Food Life go up and down completely randomly.
Pair Corralation between HK Electric and Food Life
Assuming the 90 days trading horizon HK Electric is expected to generate 2.54 times less return on investment than Food Life. But when comparing it to its historical volatility, HK Electric Investments is 1.57 times less risky than Food Life. It trades about 0.14 of its potential returns per unit of risk. Food Life Companies is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 1,940 in Food Life Companies on September 23, 2024 and sell it today you would earn a total of 160.00 from holding Food Life Companies or generate 8.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
HK Electric Investments vs. Food Life Companies
Performance |
Timeline |
HK Electric Investments |
Food Life Companies |
HK Electric and Food Life Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with HK Electric and Food Life
The main advantage of trading using opposite HK Electric and Food Life positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HK Electric position performs unexpectedly, Food Life 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 Food Life will offset losses from the drop in Food Life's long position.HK Electric vs. Ping An Insurance | HK Electric vs. Chongqing Machinery Electric | HK Electric vs. Direct Line Insurance | HK Electric vs. Penta Ocean Construction Co |
Food Life vs. HK Electric Investments | Food Life vs. Apollo Investment Corp | Food Life vs. Khiron Life Sciences | Food Life vs. BLUESCOPE STEEL |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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