Correlation Between Kings Town and JSL Construction
Can any of the company-specific risk be diversified away by investing in both Kings Town and JSL Construction 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 Kings Town and JSL Construction into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kings Town Construction and JSL Construction Development, you can compare the effects of market volatilities on Kings Town and JSL Construction 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 Kings Town with a short position of JSL Construction. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kings Town and JSL Construction.
Diversification Opportunities for Kings Town and JSL Construction
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Kings and JSL is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Kings Town Construction and JSL Construction Development in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on JSL Construction Dev and Kings Town 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 Kings Town Construction are associated (or correlated) with JSL Construction. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of JSL Construction Dev has no effect on the direction of Kings Town i.e., Kings Town and JSL Construction go up and down completely randomly.
Pair Corralation between Kings Town and JSL Construction
Assuming the 90 days trading horizon Kings Town Construction is expected to generate 0.98 times more return on investment than JSL Construction. However, Kings Town Construction is 1.02 times less risky than JSL Construction. It trades about 0.06 of its potential returns per unit of risk. JSL Construction Development is currently generating about -0.1 per unit of risk. If you would invest 5,360 in Kings Town Construction on September 19, 2024 and sell it today you would earn a total of 1,450 from holding Kings Town Construction or generate 27.05% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Kings Town Construction vs. JSL Construction Development
Performance |
Timeline |
Kings Town Construction |
JSL Construction Dev |
Kings Town and JSL Construction Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kings Town and JSL Construction
The main advantage of trading using opposite Kings Town and JSL Construction positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kings Town position performs unexpectedly, JSL Construction 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 JSL Construction will offset losses from the drop in JSL Construction's long position.Kings Town vs. Kindom Construction Corp | Kings Town vs. Highwealth Construction Corp | Kings Town vs. Hung Sheng Construction | Kings Town vs. Huaku Development Co |
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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 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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