Correlation Between BITM and Kamino

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

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

Diversification Opportunities for BITM and Kamino

0.52

Correlation Coefficient

BITM  Kamino

Very weak diversification

The 3 months correlation between BITM and Kamino is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding BITM and Kamino in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kamino and BITM 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 BITM are associated (or correlated) with Kamino. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kamino has no effect on the direction of BITM i.e., BITM and Kamino go up and down completely randomly.

Pair Corralation between BITM and Kamino

If you would invest  4.72  in Kamino on August 30, 2024 and sell it today you would earn a total of  9.28  from holding Kamino or generate 196.61% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Weak
Accuracy	1.56%
Values	Daily Returns

BITM  vs.  Kamino

BITM

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days BITM has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental indicators, BITM is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

Kamino

Risk-Adjusted Performance

9 of 100

OK

Compared to the overall equity markets, risk-adjusted returns on investments in Kamino are ranked lower than 9 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, Kamino exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with BITM and Kamino

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

The idea behind BITM and Kamino 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.

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.