Correlation Between Shin Kong and Mega Financial
Can any of the company-specific risk be diversified away by investing in both Shin Kong and Mega Financial 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 Shin Kong and Mega Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shin Kong Financial and Mega Financial Holding, you can compare the effects of market volatilities on Shin Kong and Mega Financial 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 Shin Kong with a short position of Mega Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shin Kong and Mega Financial.
Diversification Opportunities for Shin Kong and Mega Financial
-0.03 | Correlation Coefficient |
Good diversification
The 3 months correlation between Shin and Mega is -0.03. Overlapping area represents the amount of risk that can be diversified away by holding Shin Kong Financial and Mega Financial Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mega Financial Holding and Shin Kong 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 Shin Kong Financial are associated (or correlated) with Mega Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mega Financial Holding has no effect on the direction of Shin Kong i.e., Shin Kong and Mega Financial go up and down completely randomly.
Pair Corralation between Shin Kong and Mega Financial
Assuming the 90 days trading horizon Shin Kong Financial is expected to generate 1.14 times more return on investment than Mega Financial. However, Shin Kong is 1.14 times more volatile than Mega Financial Holding. It trades about -0.02 of its potential returns per unit of risk. Mega Financial Holding is currently generating about -0.19 per unit of risk. If you would invest 1,195 in Shin Kong Financial on October 14, 2024 and sell it today you would lose (5.00) from holding Shin Kong Financial or give up 0.42% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Shin Kong Financial vs. Mega Financial Holding
Performance |
Timeline |
Shin Kong Financial |
Mega Financial Holding |
Shin Kong and Mega Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shin Kong and Mega Financial
The main advantage of trading using opposite Shin Kong and Mega Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shin Kong position performs unexpectedly, Mega Financial 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 Mega Financial will offset losses from the drop in Mega Financial's long position.Shin Kong vs. Cathay Financial Holding | Shin Kong vs. Taishin Financial Holding | Shin Kong vs. Fubon Financial Holding | Shin Kong vs. CTBC Financial Holding |
Mega Financial vs. CTBC Financial Holding | Mega Financial vs. Fubon Financial Holding | Mega Financial vs. First Financial Holding | Mega Financial vs. Cathay Financial Holding |
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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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