Correlation Between Sahamit Machinery and Tata Steel
Can any of the company-specific risk be diversified away by investing in both Sahamit Machinery 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 Sahamit Machinery and Tata Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sahamit Machinery Public and Tata Steel Public, you can compare the effects of market volatilities on Sahamit Machinery 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 Sahamit Machinery with a short position of Tata Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sahamit Machinery and Tata Steel.
Diversification Opportunities for Sahamit Machinery and Tata Steel
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Sahamit and Tata is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Sahamit Machinery Public 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 Sahamit Machinery 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 Sahamit Machinery Public 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 Sahamit Machinery i.e., Sahamit Machinery and Tata Steel go up and down completely randomly.
Pair Corralation between Sahamit Machinery and Tata Steel
Assuming the 90 days trading horizon Sahamit Machinery is expected to generate 1.0 times less return on investment than Tata Steel. But when comparing it to its historical volatility, Sahamit Machinery Public is 1.0 times less risky than Tata Steel. It trades about 0.05 of its potential returns per unit of risk. Tata Steel Public is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 83.00 in Tata Steel Public on August 26, 2024 and sell it today you would lose (16.00) from holding Tata Steel Public or give up 19.28% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sahamit Machinery Public vs. Tata Steel Public
Performance |
| Timeline |
| Sahamit Machinery Public |
| Tata Steel Public |
Sahamit Machinery and Tata Steel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sahamit Machinery and Tata Steel
The main advantage of trading using opposite Sahamit Machinery and Tata Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sahamit Machinery 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.| Sahamit Machinery vs. Tata Steel Public | Sahamit Machinery vs. Thaifoods Group Public | Sahamit Machinery vs. TMT Steel Public | Sahamit Machinery vs. The Erawan Group |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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