Correlation Between Bank of Kaohsiung and Ibase Gaming
Can any of the company-specific risk be diversified away by investing in both Bank of Kaohsiung and Ibase Gaming 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 Bank of Kaohsiung and Ibase Gaming into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of Kaohsiung and Ibase Gaming, you can compare the effects of market volatilities on Bank of Kaohsiung and Ibase Gaming 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 Bank of Kaohsiung with a short position of Ibase Gaming. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Kaohsiung and Ibase Gaming.
Diversification Opportunities for Bank of Kaohsiung and Ibase Gaming
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bank and Ibase is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Kaohsiung and Ibase Gaming in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ibase Gaming and Bank of Kaohsiung 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 Bank of Kaohsiung are associated (or correlated) with Ibase Gaming. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ibase Gaming has no effect on the direction of Bank of Kaohsiung i.e., Bank of Kaohsiung and Ibase Gaming go up and down completely randomly.
Pair Corralation between Bank of Kaohsiung and Ibase Gaming
Assuming the 90 days trading horizon Bank of Kaohsiung is expected to under-perform the Ibase Gaming. But the stock apears to be less risky and, when comparing its historical volatility, Bank of Kaohsiung is 3.35 times less risky than Ibase Gaming. The stock trades about -0.02 of its potential returns per unit of risk. The Ibase Gaming is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 4,840 in Ibase Gaming on August 24, 2024 and sell it today you would lose (795.00) from holding Ibase Gaming or give up 16.43% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of Kaohsiung vs. Ibase Gaming
Performance |
| Timeline |
| Bank of Kaohsiung |
| Ibase Gaming |
Bank of Kaohsiung and Ibase Gaming Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of Kaohsiung and Ibase Gaming
The main advantage of trading using opposite Bank of Kaohsiung and Ibase Gaming positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Kaohsiung position performs unexpectedly, Ibase Gaming 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 Ibase Gaming will offset losses from the drop in Ibase Gaming's long position.| Bank of Kaohsiung vs. Fubon Financial Holding | Bank of Kaohsiung vs. Cathay Financial Holding | Bank of Kaohsiung vs. ESUN Financial Holding |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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