In finance, we could remove firm-specific risk by combining different stocks in our portfolio. First, let us look at a hypothetical case by assuming that we have 5 years' annual returns of two stocks as follows:

Year |
Stock A |
Stock B |
---|---|---|

2009 |
0.102 |
0.1062 |

2010 |
-0.02 |
0.23 |

2011 |
0.213 |
0.045 |

2012 |
0.12 |
0.234 |

2013 |
0.13 |
0.113 |

We form an equal-weighted portfolio using those two stocks. Using the `mean()`

and `std()`

functions contained in `NumPy`

, we can estimate their means, standard deviations, and correlation coefficients as follows:

>>>import numpy as np>>>A=[0.102,-0.02, 0.213,0.12,0.13]>>>B=[0.1062,0.23, 0.045,0.234,0.113]>>>port_EW=(np.array(ret_A)+np.array(ret_B))/2.>>>round(np.mean(A),3),round(np.mean(B),3),round(np.mean(port_EW),3) ...

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