Correlation Between Conifex Timber and Ufp Industries
Can any of the company-specific risk be diversified away by investing in both Conifex Timber and Ufp Industries 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 Conifex Timber and Ufp Industries into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Conifex Timber and Ufp Industries, you can compare the effects of market volatilities on Conifex Timber and Ufp Industries 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 Conifex Timber with a short position of Ufp Industries. Check out your portfolio center. Please also check ongoing floating volatility patterns of Conifex Timber and Ufp Industries.
Diversification Opportunities for Conifex Timber and Ufp Industries
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Conifex and Ufp is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Conifex Timber and Ufp Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ufp Industries and Conifex Timber 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 Conifex Timber are associated (or correlated) with Ufp Industries. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ufp Industries has no effect on the direction of Conifex Timber i.e., Conifex Timber and Ufp Industries go up and down completely randomly.
Pair Corralation between Conifex Timber and Ufp Industries
Assuming the 90 days horizon Conifex Timber is expected to generate 8.43 times more return on investment than Ufp Industries. However, Conifex Timber is 8.43 times more volatile than Ufp Industries. It trades about 0.02 of its potential returns per unit of risk. Ufp Industries is currently generating about 0.06 per unit of risk. If you would invest 119.00 in Conifex Timber on August 24, 2024 and sell it today you would lose (86.00) from holding Conifex Timber or give up 72.27% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 99.8% |
| Values | Daily Returns |
Conifex Timber vs. Ufp Industries
Performance |
| Timeline |
| Conifex Timber |
| Ufp Industries |
Conifex Timber and Ufp Industries Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Conifex Timber and Ufp Industries
The main advantage of trading using opposite Conifex Timber and Ufp Industries positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Conifex Timber position performs unexpectedly, Ufp Industries 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 Ufp Industries will offset losses from the drop in Ufp Industries' long position.| Conifex Timber vs. Ascendant Resources | Conifex Timber vs. Cantex Mine Development | Conifex Timber vs. Amarc Resources | Conifex Timber vs. Sterling Metals Corp |
| Ufp Industries vs. West Fraser Timber | Ufp Industries vs. Canfor | Ufp Industries vs. Stella Jones | Ufp Industries vs. Simpson Manufacturing |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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