Correlation Between LAMB and Theta Network
Can any of the company-specific risk be diversified away by investing in both LAMB and Theta Network 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 LAMB and Theta Network into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LAMB and Theta Network, you can compare the effects of market volatilities on LAMB and Theta Network 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 LAMB with a short position of Theta Network. Check out your portfolio center. Please also check ongoing floating volatility patterns of LAMB and Theta Network.
Diversification Opportunities for LAMB and Theta Network
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between LAMB and Theta is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding LAMB and Theta Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Theta Network and LAMB 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 LAMB are associated (or correlated) with Theta Network. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Theta Network has no effect on the direction of LAMB i.e., LAMB and Theta Network go up and down completely randomly.
Pair Corralation between LAMB and Theta Network
Assuming the 90 days trading horizon LAMB is expected to generate 1.59 times more return on investment than Theta Network. However, LAMB is 1.59 times more volatile than Theta Network. It trades about 0.17 of its potential returns per unit of risk. Theta Network is currently generating about 0.11 per unit of risk. If you would invest 0.35 in LAMB on January 25, 2024 and sell it today you would earn a total of 0.30 from holding LAMB or generate 86.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 97.67% |
Values | Daily Returns |
LAMB vs. Theta Network
Performance |
Timeline |
LAMB |
Theta Network |
LAMB and Theta Network Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with LAMB and Theta Network
The main advantage of trading using opposite LAMB and Theta Network positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LAMB position performs unexpectedly, Theta Network 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 Theta Network will offset losses from the drop in Theta Network's long position.The idea behind LAMB and Theta Network pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Theta Network vs. Solana | Theta Network vs. XRP | Theta Network vs. Staked Ether | Theta Network vs. The Open Network |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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