Correlation Between Niobay Metals and Kraken Energy
Can any of the company-specific risk be diversified away by investing in both Niobay Metals and Kraken Energy 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 Niobay Metals and Kraken Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Niobay Metals and Kraken Energy Corp, you can compare the effects of market volatilities on Niobay Metals and Kraken Energy 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 Niobay Metals with a short position of Kraken Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Niobay Metals and Kraken Energy.
Diversification Opportunities for Niobay Metals and Kraken Energy
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Niobay and Kraken is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding Niobay Metals and Kraken Energy Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kraken Energy Corp and Niobay Metals 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 Niobay Metals are associated (or correlated) with Kraken Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kraken Energy Corp has no effect on the direction of Niobay Metals i.e., Niobay Metals and Kraken Energy go up and down completely randomly.
Pair Corralation between Niobay Metals and Kraken Energy
Assuming the 90 days horizon Niobay Metals is expected to generate 1.74 times more return on investment than Kraken Energy. However, Niobay Metals is 1.74 times more volatile than Kraken Energy Corp. It trades about 0.03 of its potential returns per unit of risk. Kraken Energy Corp is currently generating about -0.01 per unit of risk. If you would invest 6.00 in Niobay Metals on September 4, 2024 and sell it today you would lose (2.00) from holding Niobay Metals or give up 33.33% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.44% |
Values | Daily Returns |
Niobay Metals vs. Kraken Energy Corp
Performance |
Timeline |
Niobay Metals |
Kraken Energy Corp |
Niobay Metals and Kraken Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Niobay Metals and Kraken Energy
The main advantage of trading using opposite Niobay Metals and Kraken Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Niobay Metals position performs unexpectedly, Kraken Energy 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 Kraken Energy will offset losses from the drop in Kraken Energy's long position.Niobay Metals vs. Qubec Nickel Corp | Niobay Metals vs. IGO Limited | Niobay Metals vs. Avarone Metals | Niobay Metals vs. Adriatic Metals PLC |
Kraken Energy vs. Qubec Nickel Corp | Kraken Energy vs. IGO Limited | Kraken Energy vs. Avarone Metals | Kraken Energy vs. Adriatic Metals PLC |
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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