Correlation Between General Engineering and TPI Polene
Can any of the company-specific risk be diversified away by investing in both General Engineering and TPI Polene 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 General Engineering and TPI Polene into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Engineering Public and TPI Polene Public, you can compare the effects of market volatilities on General Engineering and TPI Polene 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 General Engineering with a short position of TPI Polene. Check out your portfolio center. Please also check ongoing floating volatility patterns of General Engineering and TPI Polene.
Diversification Opportunities for General Engineering and TPI Polene
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between General and TPI is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding General Engineering Public and TPI Polene Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TPI Polene Public and General Engineering 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 General Engineering Public are associated (or correlated) with TPI Polene. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TPI Polene Public has no effect on the direction of General Engineering i.e., General Engineering and TPI Polene go up and down completely randomly.
Pair Corralation between General Engineering and TPI Polene
Assuming the 90 days trading horizon General Engineering Public is expected to generate 50.55 times more return on investment than TPI Polene. However, General Engineering is 50.55 times more volatile than TPI Polene Public. It trades about 0.05 of its potential returns per unit of risk. TPI Polene Public is currently generating about -0.07 per unit of risk. If you would invest 20.00 in General Engineering Public on September 24, 2024 and sell it today you would lose (12.00) from holding General Engineering Public or give up 60.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
General Engineering Public vs. TPI Polene Public
Performance |
Timeline |
General Engineering |
TPI Polene Public |
General Engineering and TPI Polene Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with General Engineering and TPI Polene
The main advantage of trading using opposite General Engineering and TPI Polene positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if General Engineering position performs unexpectedly, TPI Polene 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 TPI Polene will offset losses from the drop in TPI Polene's long position.General Engineering vs. Dynasty Ceramic Public | General Engineering vs. Chonburi Concrete Product | General Engineering vs. Eastern Star Real | General Engineering vs. Better World Green |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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