Correlation Between NTG Nordic and TITAN MACHINERY
Can any of the company-specific risk be diversified away by investing in both NTG Nordic and TITAN MACHINERY 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 NTG Nordic and TITAN MACHINERY into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NTG Nordic Transport and TITAN MACHINERY, you can compare the effects of market volatilities on NTG Nordic and TITAN MACHINERY 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 NTG Nordic with a short position of TITAN MACHINERY. Check out your portfolio center. Please also check ongoing floating volatility patterns of NTG Nordic and TITAN MACHINERY.
Diversification Opportunities for NTG Nordic and TITAN MACHINERY
-0.26 | Correlation Coefficient |
Very good diversification
The 3 months correlation between NTG and TITAN is -0.26. Overlapping area represents the amount of risk that can be diversified away by holding NTG Nordic Transport and TITAN MACHINERY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TITAN MACHINERY and NTG Nordic 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 NTG Nordic Transport are associated (or correlated) with TITAN MACHINERY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TITAN MACHINERY has no effect on the direction of NTG Nordic i.e., NTG Nordic and TITAN MACHINERY go up and down completely randomly.
Pair Corralation between NTG Nordic and TITAN MACHINERY
Assuming the 90 days trading horizon NTG Nordic Transport is expected to under-perform the TITAN MACHINERY. But the stock apears to be less risky and, when comparing its historical volatility, NTG Nordic Transport is 1.44 times less risky than TITAN MACHINERY. The stock trades about -0.05 of its potential returns per unit of risk. The TITAN MACHINERY is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 1,190 in TITAN MACHINERY on September 15, 2024 and sell it today you would earn a total of 250.00 from holding TITAN MACHINERY or generate 21.01% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
NTG Nordic Transport vs. TITAN MACHINERY
Performance |
Timeline |
NTG Nordic Transport |
TITAN MACHINERY |
NTG Nordic and TITAN MACHINERY Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NTG Nordic and TITAN MACHINERY
The main advantage of trading using opposite NTG Nordic and TITAN MACHINERY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NTG Nordic position performs unexpectedly, TITAN MACHINERY 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 TITAN MACHINERY will offset losses from the drop in TITAN MACHINERY's long position.NTG Nordic vs. Superior Plus Corp | NTG Nordic vs. SIVERS SEMICONDUCTORS AB | NTG Nordic vs. NorAm Drilling AS | NTG Nordic vs. Norsk Hydro ASA |
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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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