Correlation Between AOYAMA TRADING and INSURANCE AUST
Can any of the company-specific risk be diversified away by investing in both AOYAMA TRADING and INSURANCE AUST 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 AOYAMA TRADING and INSURANCE AUST into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AOYAMA TRADING and INSURANCE AUST GRP, you can compare the effects of market volatilities on AOYAMA TRADING and INSURANCE AUST 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 AOYAMA TRADING with a short position of INSURANCE AUST. Check out your portfolio center. Please also check ongoing floating volatility patterns of AOYAMA TRADING and INSURANCE AUST.
Diversification Opportunities for AOYAMA TRADING and INSURANCE AUST
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between AOYAMA and INSURANCE is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding AOYAMA TRADING and INSURANCE AUST GRP in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on INSURANCE AUST GRP and AOYAMA TRADING 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 AOYAMA TRADING are associated (or correlated) with INSURANCE AUST. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of INSURANCE AUST GRP has no effect on the direction of AOYAMA TRADING i.e., AOYAMA TRADING and INSURANCE AUST go up and down completely randomly.
Pair Corralation between AOYAMA TRADING and INSURANCE AUST
Assuming the 90 days horizon AOYAMA TRADING is expected to generate 2.94 times more return on investment than INSURANCE AUST. However, AOYAMA TRADING is 2.94 times more volatile than INSURANCE AUST GRP. It trades about 0.08 of its potential returns per unit of risk. INSURANCE AUST GRP is currently generating about 0.09 per unit of risk. If you would invest 330.00 in AOYAMA TRADING on September 20, 2024 and sell it today you would earn a total of 1,100 from holding AOYAMA TRADING or generate 333.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
AOYAMA TRADING vs. INSURANCE AUST GRP
Performance |
Timeline |
AOYAMA TRADING |
INSURANCE AUST GRP |
AOYAMA TRADING and INSURANCE AUST Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AOYAMA TRADING and INSURANCE AUST
The main advantage of trading using opposite AOYAMA TRADING and INSURANCE AUST positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AOYAMA TRADING position performs unexpectedly, INSURANCE AUST 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 INSURANCE AUST will offset losses from the drop in INSURANCE AUST's long position.AOYAMA TRADING vs. FAST RETAIL ADR | AOYAMA TRADING vs. CCC SA | AOYAMA TRADING vs. Superior Plus Corp | AOYAMA TRADING vs. SIVERS SEMICONDUCTORS AB |
INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Microsoft |
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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