Correlation Between HB Technology and Cots Technology
Can any of the company-specific risk be diversified away by investing in both HB Technology and Cots Technology 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 HB Technology and Cots Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HB Technology TD and Cots Technology Co, you can compare the effects of market volatilities on HB Technology and Cots Technology 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 HB Technology with a short position of Cots Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of HB Technology and Cots Technology.
Diversification Opportunities for HB Technology and Cots Technology
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 078150 and Cots is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding HB Technology TD and Cots Technology Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cots Technology and HB Technology 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 HB Technology TD are associated (or correlated) with Cots Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cots Technology has no effect on the direction of HB Technology i.e., HB Technology and Cots Technology go up and down completely randomly.
Pair Corralation between HB Technology and Cots Technology
Assuming the 90 days trading horizon HB Technology TD is expected to under-perform the Cots Technology. But the stock apears to be less risky and, when comparing its historical volatility, HB Technology TD is 1.07 times less risky than Cots Technology. The stock trades about -0.11 of its potential returns per unit of risk. The Cots Technology Co is currently generating about -0.06 of returns per unit of risk over similar time horizon. If you would invest 1,822,000 in Cots Technology Co on September 28, 2024 and sell it today you would lose (301,000) from holding Cots Technology Co or give up 16.52% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
HB Technology TD vs. Cots Technology Co
Performance |
Timeline |
HB Technology TD |
Cots Technology |
HB Technology and Cots Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with HB Technology and Cots Technology
The main advantage of trading using opposite HB Technology and Cots Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HB Technology position performs unexpectedly, Cots Technology 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 Cots Technology will offset losses from the drop in Cots Technology's long position.HB Technology vs. Nice Information Telecommunication | HB Technology vs. Inzi Display CoLtd | HB Technology vs. Sejong Telecom | HB Technology vs. Korea Information Communications |
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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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