Correlation Between Tata Steel and Spirent Communications
Can any of the company-specific risk be diversified away by investing in both Tata Steel and Spirent Communications 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 Tata Steel and Spirent Communications into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tata Steel Limited and Spirent Communications plc, you can compare the effects of market volatilities on Tata Steel and Spirent Communications 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 Tata Steel with a short position of Spirent Communications. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tata Steel and Spirent Communications.
Diversification Opportunities for Tata Steel and Spirent Communications
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Tata and Spirent is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Tata Steel Limited and Spirent Communications plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Spirent Communications and Tata Steel 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 Tata Steel Limited are associated (or correlated) with Spirent Communications. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Spirent Communications has no effect on the direction of Tata Steel i.e., Tata Steel and Spirent Communications go up and down completely randomly.
Pair Corralation between Tata Steel and Spirent Communications
Assuming the 90 days trading horizon Tata Steel Limited is expected to generate 4.59 times more return on investment than Spirent Communications. However, Tata Steel is 4.59 times more volatile than Spirent Communications plc. It trades about 0.12 of its potential returns per unit of risk. Spirent Communications plc is currently generating about 0.32 per unit of risk. If you would invest 1,563 in Tata Steel Limited on April 22, 2025 and sell it today you would earn a total of 332.00 from holding Tata Steel Limited or generate 21.24% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Tata Steel Limited vs. Spirent Communications plc
Performance |
Timeline |
Tata Steel Limited |
Spirent Communications |
Tata Steel and Spirent Communications Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tata Steel and Spirent Communications
The main advantage of trading using opposite Tata Steel and Spirent Communications positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tata Steel position performs unexpectedly, Spirent Communications 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 Spirent Communications will offset losses from the drop in Spirent Communications' long position.Tata Steel vs. Givaudan SA | Tata Steel vs. Antofagasta PLC | Tata Steel vs. EVRAZ plc | Tata Steel vs. Atalaya Mining |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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