Correlation Between Algorand and Crosswood

Can any of the company-specific risk be diversified away by investing in both Algorand and Crosswood 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 Algorand and Crosswood into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Algorand and Crosswood, you can compare the effects of market volatilities on Algorand and Crosswood 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 Algorand with a short position of Crosswood. Check out your portfolio center. Please also check ongoing floating volatility patterns of Algorand and Crosswood.

Diversification Opportunities for Algorand and Crosswood

0.16

Correlation Coefficient

Algorand  Crosswood

Average diversification

The 3 months correlation between Algorand and Crosswood is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Algorand and Crosswood in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Crosswood and Algorand 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 Algorand are associated (or correlated) with Crosswood. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Crosswood has no effect on the direction of Algorand i.e., Algorand and Crosswood go up and down completely randomly.

Pair Corralation between Algorand and Crosswood

Assuming the 90 days trading horizon Algorand is expected to generate 1.29 times more return on investment than Crosswood. However, Algorand is 1.29 times more volatile than Crosswood. It trades about 0.05 of its potential returns per unit of risk. Crosswood is currently generating about 0.05 per unit of risk. If you would invest  24.00  in Algorand on October 11, 2024 and sell it today you would earn a total of  12.00  from holding Algorand or generate 50.0% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	63.46%
Values	Daily Returns

Algorand  vs.  Crosswood

Algorand

Risk-Adjusted Performance

17 of 100

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in Algorand are ranked lower than 17 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, Algorand exhibited solid returns over the last few months and may actually be approaching a breakup point.

Crosswood

Risk-Adjusted Performance

3 of 100

Insignificant

Compared to the overall equity markets, risk-adjusted returns on investments in Crosswood are ranked lower than 3 (%) of all global equities and portfolios over the last 90 days. Despite somewhat weak basic indicators, Crosswood sustained solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with Algorand and Crosswood

The main advantage of trading using opposite Algorand and Crosswood positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Algorand position performs unexpectedly, Crosswood 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 Crosswood will offset losses from the drop in Crosswood's long position.

The idea behind Algorand and Crosswood 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.

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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.