Correlation Analysis Between OSE All and NQEGT

This module allows you to analyze existing cross correlation between OSE All and NQEGT. You can compare the effects of market volatilities on OSE All and NQEGT 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 OSE All with a short position of NQEGT. See also your portfolio center. Please also check ongoing floating volatility patterns of OSE All and NQEGT.
Horizon     30 Days    Login   to change

OSE All  vs.  NQEGT

 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, OSE All is expected to generate 0.5 times more return on investment than NQEGT. However, OSE All is 1.99 times less risky than NQEGT. It trades about -0.08 of its potential returns per unit of risk. NQEGT is currently generating about -0.07 per unit of risk. If you would invest  103,750  in OSE All on September 18, 2018 and sell it today you would lose (2,285)  from holding OSE All or give up 2.2% of portfolio value over 30 days.

Pair Corralation between OSE All and NQEGT

Time Period1 Month [change]
ValuesDaily Returns


Pay attention

Overlapping area represents the amount of risk that can be diversified away by holding OSE All and NQEGT in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NQEGT and OSE All 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 OSE All are associated (or correlated) with NQEGT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NQEGT has no effect on the direction of OSE All i.e. OSE All and NQEGT go up and down completely randomly.

Comparative Volatility

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See also your portfolio center. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.