Correlation Between Thoresen Thai and Tata Steel
Can any of the company-specific risk be diversified away by investing in both Thoresen Thai and Tata Steel 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 Thoresen Thai and Tata Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Thoresen Thai Agencies and Tata Steel Public, you can compare the effects of market volatilities on Thoresen Thai and Tata Steel 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 Thoresen Thai with a short position of Tata Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Thoresen Thai and Tata Steel.
Diversification Opportunities for Thoresen Thai and Tata Steel
0.21 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Thoresen and Tata is 0.21. Overlapping area represents the amount of risk that can be diversified away by holding Thoresen Thai Agencies and Tata Steel Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tata Steel Public and Thoresen Thai 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 Thoresen Thai Agencies are associated (or correlated) with Tata Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tata Steel Public has no effect on the direction of Thoresen Thai i.e., Thoresen Thai and Tata Steel go up and down completely randomly.
Pair Corralation between Thoresen Thai and Tata Steel
Assuming the 90 days trading horizon Thoresen Thai Agencies is expected to generate 1.13 times more return on investment than Tata Steel. However, Thoresen Thai is 1.13 times more volatile than Tata Steel Public. It trades about -0.07 of its potential returns per unit of risk. Tata Steel Public is currently generating about -0.1 per unit of risk. If you would invest 635.00 in Thoresen Thai Agencies on August 29, 2024 and sell it today you would lose (50.00) from holding Thoresen Thai Agencies or give up 7.87% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 97.56% |
| Values | Daily Returns |
Thoresen Thai Agencies vs. Tata Steel Public
Performance |
| Timeline |
| Thoresen Thai Agencies |
| Tata Steel Public |
Thoresen Thai and Tata Steel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Thoresen Thai and Tata Steel
The main advantage of trading using opposite Thoresen Thai and Tata Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Thoresen Thai position performs unexpectedly, Tata Steel 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 Tata Steel will offset losses from the drop in Tata Steel's long position.| Thoresen Thai vs. MCS Steel Public | Thoresen Thai vs. Asia Plus Group | Thoresen Thai vs. Lalin Property Public | Thoresen Thai vs. Lam Soon Public |
| Tata Steel vs. TMT Steel Public | Tata Steel vs. TPI Polene Public | Tata Steel vs. Thoresen Thai Agencies | Tata Steel vs. TRC Construction Public |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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