Correlation Between NFI and Stella Jones
Can any of the company-specific risk be diversified away by investing in both NFI and Stella Jones 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 NFI and Stella Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NFI Group and Stella Jones, you can compare the effects of market volatilities on NFI and Stella Jones 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 NFI with a short position of Stella Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of NFI and Stella Jones.
Diversification Opportunities for NFI and Stella Jones
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between NFI and Stella is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding NFI Group and Stella Jones in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Stella Jones and NFI 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 NFI Group are associated (or correlated) with Stella Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Stella Jones has no effect on the direction of NFI i.e., NFI and Stella Jones go up and down completely randomly.
Pair Corralation between NFI and Stella Jones
Assuming the 90 days trading horizon NFI Group is expected to generate 0.56 times more return on investment than Stella Jones. However, NFI Group is 1.79 times less risky than Stella Jones. It trades about -0.33 of its potential returns per unit of risk. Stella Jones is currently generating about -0.25 per unit of risk. If you would invest 1,665 in NFI Group on August 28, 2024 and sell it today you would lose (217.00) from holding NFI Group or give up 13.03% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
NFI Group vs. Stella Jones
Performance |
| Timeline |
| NFI Group |
| Stella Jones |
NFI and Stella Jones Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with NFI and Stella Jones
The main advantage of trading using opposite NFI and Stella Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NFI position performs unexpectedly, Stella Jones 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 Stella Jones will offset losses from the drop in Stella Jones' long position.The idea behind NFI Group and Stella Jones 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.| Stella Jones vs. First Majestic Silver | Stella Jones vs. Ivanhoe Energy | Stella Jones vs. Orezone Gold Corp | Stella Jones vs. Faraday Copper Corp |
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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