Correlation Between Indian Oil and Punjab Sind
Can any of the company-specific risk be diversified away by investing in both Indian Oil and Punjab Sind 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 Indian Oil and Punjab Sind into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Indian Oil and Punjab Sind Bank, you can compare the effects of market volatilities on Indian Oil and Punjab Sind 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 Indian Oil with a short position of Punjab Sind. Check out your portfolio center. Please also check ongoing floating volatility patterns of Indian Oil and Punjab Sind.
Diversification Opportunities for Indian Oil and Punjab Sind
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Indian and Punjab is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Indian Oil and Punjab Sind Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Punjab Sind Bank and Indian Oil 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 Indian Oil are associated (or correlated) with Punjab Sind. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Punjab Sind Bank has no effect on the direction of Indian Oil i.e., Indian Oil and Punjab Sind go up and down completely randomly.
Pair Corralation between Indian Oil and Punjab Sind
Assuming the 90 days trading horizon Indian Oil is expected to under-perform the Punjab Sind. But the stock apears to be less risky and, when comparing its historical volatility, Indian Oil is 1.39 times less risky than Punjab Sind. The stock trades about -0.19 of its potential returns per unit of risk. The Punjab Sind Bank is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 4,862 in Punjab Sind Bank on August 28, 2024 and sell it today you would earn a total of 20.00 from holding Punjab Sind Bank or generate 0.41% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.0% |
| Values | Daily Returns |
Indian Oil vs. Punjab Sind Bank
Performance |
| Timeline |
| Indian Oil |
| Punjab Sind Bank |
Indian Oil and Punjab Sind Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Indian Oil and Punjab Sind
The main advantage of trading using opposite Indian Oil and Punjab Sind positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Indian Oil position performs unexpectedly, Punjab Sind 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 Punjab Sind will offset losses from the drop in Punjab Sind's long position.| Indian Oil vs. JGCHEMICALS LIMITED | Indian Oil vs. Omkar Speciality Chemicals | Indian Oil vs. NRB Industrial Bearings | Indian Oil vs. Dharani SugarsChemicals Limited |
| Punjab Sind vs. Cartrade Tech Limited | Punjab Sind vs. LT Foods Limited | Punjab Sind vs. Newgen Software Technologies | Punjab Sind vs. Fine Organic Industries |
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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