Data is as under;

Sheet 1;

Sheet 2;

Sheet 3;

Just done Part (a,b,c,d) Also explain how you had arrived to the solution plz do not use excel. work will be appreciated. Thanks

Problem 8: Portfolio Choice Using Numerical Methods (6 points) For this problem, you will need data in Excel file homework3.data.2.xlsx available on Black- board, which contains monthly returns on Microsoft and Alcoa stocks. Assume that those are only 2 stocks on the market. You will need to use a statistical software. Microsoft Excel should satisfy your needs, but you can use anything else you prefer. Do all tasks below at monthly frequency. Use population statistics to compute return properties. a) (0.5 point) Compute the expected return and standard deviation of Microsoft. b) (0.5 point) Compute the expected retum and standard deviation of Alcoa. c) (0.5 point) Compute the covariance and correlation between Microsoft and Alcoa returns. d) (1 point) Construct the grid of possible portfolio allocations. Assume that a is the portfolio allocation to Microsoft. Assume that a is between 0 and 1 and use the grid precision of 0.005 (0.5%). Thus, your grid is going to be 0,0.005, 0.01, 0.015...0.985, 0.99, 0.995, 1. For each portfolio allocation on the grid, compute the expected return and the standard deviation using 3 properties of individual assets from a)-c). Do not report the whole grid in the answer: report only the rows corresponding to the following values of a: 0.1, 0.3, 0.7, and 0.95. e) (0.5 point) Plot the opportunity set in the standard deviation-expected return domain. Use the grid constructed in part d) to answer the questions below: 1) (1 point) What is the minimum standard deviation you can achieve using those 2 assets? What is (approximately) the portfolio allocation to Microsoft to achieve that standard deviation? g) (1 point) Suppose the maximum monthly standard deviation you can tolerate is 9%. What is your optimal portfolio allocation among Alcoa and Microsoft stocks? h) (1 point) Suppose that the monthly risk-free rate is 0.1% and you can both invest and borrow at this rate. What is the weight of Microsoft in the aggregate market portfolio? E F G H 1 J K L M 1991 1992 A B D 1 Return of 0.01 corresponds to 1% return 2 Year Month Microsoft Alcoa 3 1990 1 0.063218 -0.157667 4 1990 2 0.067568 0.046843 5 1990 3 0.121519 0.007782 6 1990 4 0.047404 -0.036293 7 1990 5 0.258621 0.064516 8 1990 6 0.041096 -0.034091 9 1990 7 -0.125 0.097255 10 1990 8 -0.075188 -0.073741 11 1990 9 0.02439 0.027184 12 1990 10 0.011905 -0.145309 13 1990 11 0.133333 0.032941 14 1990 12 0.041522 0.050114 15 1991 1 0.303987 0.127202 16 1991 2 0.057325 -0.003883 17 1991 3 0.022892 0.021442 18 1991 4 -0.067138 0.036641 19 1991 5 0.108586 0.053704 20 1991 6 -0.068907 -0.050967 21 1991 0.078899 0.052222 22 1991 8 0.159864 -0.019469 23 9 0.043988 -0.077617 24 1991 10 0.054775 -0.001566 25 1991 11 0.035952 -0.076923 26 1991 12 0.143959 0.100427 27 1992 1 0.080899 0.001942 28 1992 2 0.027027 0.081783 29 1992 3 -0.040486 0.016216 30 1992 4 -0.06962 0.103191 31 1992 5 0.097506 0.003231 32 1992 6 -0.132231 -0.022544 33 1992 7 0.039286 -0.028007 34 1992 8 0.024055 0.118305 35 9 0.080537 0.025145 36 1992 10 0.102484 0.05283 37 1992 11 0.049296 0.011111 38 1992 12 -0.083221 0.02139 39 1993 1 0.013177 0.038394 40 1993 2 -0.036127 -0.051765 41 1993 3 0.109445 -0.080214 42 1993 4 -0.075676 0.025194 43 1993 5 0.083333 0.026843 44 1993 6 0.049933 0.037037 45 1993 7 -0.159091 0.017857 46 1993 8 0.015203 0.06 47 1993 9 0.09817 -0.106489 48 1993 10 -0.028788 0.013035 49 1993 11 -0.00156 0.024265 50 1993 12 0.007813 0.001805 51 1994 1 0.055814 0.146306 52 1994 2 0.030837 -0.048973 53 1994 3 0.027273 -0.048173 54 1994 4 0.091445 -0.050611 55 1994 5 0.162162 0.044485 56 1994 6 -0.039535 0.035398 57 1994 7 -0.002421 0.070085 58 1994 8 0.128641 0.078594 59 1994 9 -0.034409 0.008929 60 1994 10 0.122494 0.010619 61 1994 11 -0.001984 -0.042522 62 1994 12 -0.027833 0.061256 63 1995 1 -0.02863 -0.087157 64 1995 2 0.061053 -0.007949 65 1995 3 0.128968 0.064103 66 1995 4 0.149385 0.081325 67 1995 5 0.035933 0.041226 68 6 0.067159 0.077957 69 1995 7 0.001383 0.137157 70 1995 8 0.022099 0.00614 71 1995 9 -0.021622 -0.074398 72 1995 10 0.104972 -0.035461 73 1995 11 -0.12875 0.151471 74 1995 12 0.007174 0.096154 75 1996 1 0.054131 0.055934 76 1996 2 0.066892 0.024775 77 1996 3 0.044965 0.101099 78 1996 4 0.098182 -0.003992 79 1996 5 0.048565 -0.006693 80 1996 6 0.011579 -0.068966 81 1996 7 -0.01873 0.016688 82 1996 8 0.039236 0.071121 83 1996 9 0.076531 -0.050302 84 1996 10 0.040758 -0.00072 85 1996 11 0.142987 0.085288 86 1996 12 0.053386 0.001965 87 1997 1 0.234493 0.082353 88 1997 2 -0.044118 0.03587 89 1997 3 -0.059615 -0.045614 90 1997 4 0.325153 0.03125 91 1997 5 0.020576 0.053667 92 1997 6 0.019153 0.023769 93 1997 7 0.119683 0.174129 94 1997 8 -0.065813 -0.067797 95 1997 9 0.000946 -0.00304 96 1997 10 -0.017478 -0.109756 97 1997 11 0.0884620.075342 98 1997 12 -0.086572 0.046468 99 1998 1 0.154255 0.085258 100 1998 2 0.136154 -0.036007 101 1998 3 0.056047 -0.062181 102 1998 4 0.006983 0.126249 1995 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2001 2001 2001 2001 2001 2001 2001 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 2001 2001 2001 2001 2001 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2006 2006 2006 1 0.154255 0.085258 2 0.136154 -0.036007 3 0.056047 0.062181 4 0.006983 0.126249 5 -0.058946 -0.101613 6 0.277819 -0.04955 7 0.014418 0.051185 8 -0.127345 -0.130748 9 0.147231 0.185804 10 -0.038047 0.116197 11 0.152302 -0.05836 12 0.136783 0.004209 1 0.26183 0.120704 2 -0.142143 -0.025849 3 0.194005 0.016975 4 -0.092748 0.511381 5 -0.007686 0.113225 6 0.117738 0.125 7 -0.04851 -0.032323 8 0.07866 0.081649 9 -0.021607 -0.038722 10 0.022084 -0.021148 11 -0.016374 0.081502 12 0.282306 0.267176 1 -0.16167 -0.160392 2 -0.086845 -0.013453 3 0.188811 0.025547 4 -0.343529 -0.076512 5 -0.103047 -0.095376 6 0.278721 -0.007487 7 -0.127344 0.043103 8 0 0.103306 9 -0.136079 0.238722 10 0.141969 0.133333 11 -0.166969 -0.013072 12 -0.244009 0.18847 1 0.407781 0.101194 2 -0.033777 -0.026674 3 -0.073093 0.005313 4 0.238857 0.151599 5 0.021107 0.045894 6 0.055218 -0.086906 7 -0.093288 -0.004315 8 -0.138087 -0.024471 9 -0.103068 -0.186516 10 0.136408 0.045469 11 0.104213 0.196157 12 0.031771 -0.079016 1 -0.03834 0.008439 2 -0.084288 0.052162 3 0.033768 0.004525 4 -0.133477 -0.098304 5 -0.025832 0.032324 6 0.074445 -0.052316 7 -0.122852 -0.179487 8 0.022926 -0.072458 9 -0.108802 -0.230769 10 0.222451 0.143005 11 0.078736 0.165005 12 -0.103675 -0.108415 1 -0.082012 -0.132133 2 0.002107 0.044512 3 0.021519 -0.054634 4 0.055762 0.190919 5 -0.037167 0.073266 6 0.041853 0.036164 7 0.030031 0.08902 8 0.004165 0.033849 9 0.048265 -0.084034 10 0.053957 0.206804 11 -0.01645 0.044029 12 0.064566 0.158183 1 0.01023 -0.100526 2 -0.040506 0.100644 3 -0.060309 -0.074193 4 0.048135 -0.113577 5 0.003827 0.022764 6 0.08883 0.055272 7 -0.002451 -0.030276 8 -0.038961 0.01561 9 0.012821 0.037369 10 0.011573 -0.03245 11 0.068645 0.050154 12 -0.003357 -0.075338 1 -0.016467 -0.060789 2 -0.039574 0.093528 3 -0.039348 -0.053861 4 0.046752 -0.045081 5 0.022925 -0.060992 6 -0.037209 -0.035793 7 0.030998 0.073479 8 0.072237 0.039572 9 -0.060263 -0.088466 10 -0.001166 -0.005323 11 0.080156 0.134623 12 -0.055275 0.078803 1 0.076482 0.065269 2 -0.042273 -0.064444 3 0.012653 0.042292 4 -0.112459 0.105366 5 -0.058385 -0.056542 6 0.028698 0.020177 7 0.032618 -0.074475 8 0.071904 -0.040401 2006 2006 2006 2006 2006 1 199 2006 200 2006 201 2006 202 2006 203 2006 204 2006 205 2006 206 2006 207 2007 208 2007 209 2007 210 2007 211 2007 212 2007 213 2007 214 2007 215 2007 216 2007 217 2007 218 2007 219 2008 220 2008 221 2008 222 2008 223 2008 224 2008 225 2008 226 2008 227 2008 228 2008 229 2008 230 008 231 2009 232 2009 233 2009 234 2009 235 2009 236 2009 237 2009 238 2009 239 2009 240 2009 241 2009 242 2009 243 2010 244 2010 245 2010 246 2010 247 2010 248 2010 249 2010 250 2010 251 2010 252 2010 253 2010 254 2010 255 2011 256 2011 257 2011 258 2011 259 2011 260 2011 261 2011 262 2011 263 2011 264 2011 265 2011 266 2011 267 2012 268 2012 269 2012 270 2012 271 2012 272 2012 273 2012 274 2012 275 2012 276 277 2012 278 2012 279 2013 280 2013 281 2013 282 2013 283 2013 284 2013 285 2013 286 2013 287 2013 288 2013 289 2013 290 2013 291 2014 292 2014 293 2014 294 2014 295 2014 296 2014 297 2014 298 2014 299 2014 300 2014 301 302 2014 303 5 -0.058385 -0.056542 6 0.028698 0.020177 7 0.032618 -0.074475 8 0.071904 -0.040401 9 0.064202 -0.019237 10 0.049726 0.031027 11 0.026123 0.083362 12 0.01703 -0.037215 1 0.03349 0.081973 2 -0,083927 0.034365 3 -0.01065 0.014666 4 0.074273 0.046903 5 0.028393 0.167935 6 -0.039756 -0.018169 7 -0.016288 -0.057488 8 -0.005519 -0.039267 9 0.025409 0.070901 10 0.249491 0.01636 11 -0.084216 -0.081334 12 0.059524 0.004949 1 -0.08427 -0.094665 2 -0.162273 0.127531 30.043386 -0.029079 4 0.004933 -0.030782 5 -0.003156 0.16705 6 -0.028602 -0.122444 7 -0.065067 -0.052499 8 0.065319 -0.042963 9 -0.021986 -0.29723 100.163357 -0.4907 11 -0.08867 -0.049565 12 -0.038576 0.046468 1 -0.12037 -0.308171 2 -0.047953 -0.178434 3 0.137461 0.17817 4 0.102885 0.235695 5 0.037512 0.019846 6 0.137865 0.12039 7 -0.010517 0.138432 8 0.053571 0.027211 9 0.043408 0.088797 10 0.078149 -0.053354 11 0.065272 0.010467 12 0.036382 0.28754 1 -0.075459 -0.210298 2 0.022001 0.047133 3 0.021538 0.070677 4 0.042595 -0.056882 50.150811 -0.13105 6 -0.108140.135739 70.121686 0.110338 8 -0.085819 0.062587 9 0.043682 0.185221 10 0.088812 0.085054 11 -0.046784 0.001142 12 0.105018 0.172571 1 -0.006628 0.076673 2 -0.035528 0.018709 3 -0.044771 0.048071 4 0.020874 -0.037373 5 -0.028935 -0.009412 6 0.039584 -0.056514 7 0.053846 -0.071248 8 -0.023358 0.128988 9 -0.064286 -0.252344 10 0.069908 0.124347 11 -0.031919 -0.065985 12 0.014855 -0.136727 1 0.137519 0.174567 2 0.081612 0.003937 30.016226 -0.014749 4 -0.007441 -0.028942 50.081993 0.118191 6 0.047962 0.023392 7 0.036613 -0.032 8 0.052596 0.014168 9 -0.034393 0.034463 100.040995 -0.028797 11 -0.05939 -0.01867 12 0.003558 0.032105 1 0.027217 0.018433 2 0.021129 -0.032805 3 0.028957 0 4 0.15714 -0.002347 5 0.061329 0.003529 6 -0.010172 -0.08 7 -0.078304 8 0.056219 +0.027673 9 -0.003593 0.054545 10 0.063852 0.141626 11 0.084875 0.039914 12 0.018883 0.106139 10.011494 0.082785 2 0.01982 0.022589 3 0.069956 0.096252 4 -0.014394 0.04662 5 0.020297 0.012621 6 0.018564 0.094049 7 0.035012 0.100739 8 0.059082 0.015253 90.020471 0.031306 10 0.012726 0.041641 11 0.02492 0.033413 12 -0.028446 -0.086755 2012 2014 Problem 8: Portfolio Choice Using Numerical Methods (6 points) For this problem, you will need data in Excel file homework3.data.2.xlsx available on Black- board, which contains monthly returns on Microsoft and Alcoa stocks. Assume that those are only 2 stocks on the market. You will need to use a statistical software. Microsoft Excel should satisfy your needs, but you can use anything else you prefer. Do all tasks below at monthly frequency. Use population statistics to compute return properties. a) (0.5 point) Compute the expected return and standard deviation of Microsoft. b) (0.5 point) Compute the expected retum and standard deviation of Alcoa. c) (0.5 point) Compute the covariance and correlation between Microsoft and Alcoa returns. d) (1 point) Construct the grid of possible portfolio allocations. Assume that a is the portfolio allocation to Microsoft. Assume that a is between 0 and 1 and use the grid precision of 0.005 (0.5%). Thus, your grid is going to be 0,0.005, 0.01, 0.015...0.985, 0.99, 0.995, 1. For each portfolio allocation on the grid, compute the expected return and the standard deviation using 3 properties of individual assets from a)-c). Do not report the whole grid in the answer: report only the rows corresponding to the following values of a: 0.1, 0.3, 0.7, and 0.95. e) (0.5 point) Plot the opportunity set in the standard deviation-expected return domain. Use the grid constructed in part d) to answer the questions below: 1) (1 point) What is the minimum standard deviation you can achieve using those 2 assets? What is (approximately) the portfolio allocation to Microsoft to achieve that standard deviation? g) (1 point) Suppose the maximum monthly standard deviation you can tolerate is 9%. What is your optimal portfolio allocation among Alcoa and Microsoft stocks? h) (1 point) Suppose that the monthly risk-free rate is 0.1% and you can both invest and borrow at this rate. What is the weight of Microsoft in the aggregate market portfolio? E F G H 1 J K L M 1991 1992 A B D 1 Return of 0.01 corresponds to 1% return 2 Year Month Microsoft Alcoa 3 1990 1 0.063218 -0.157667 4 1990 2 0.067568 0.046843 5 1990 3 0.121519 0.007782 6 1990 4 0.047404 -0.036293 7 1990 5 0.258621 0.064516 8 1990 6 0.041096 -0.034091 9 1990 7 -0.125 0.097255 10 1990 8 -0.075188 -0.073741 11 1990 9 0.02439 0.027184 12 1990 10 0.011905 -0.145309 13 1990 11 0.133333 0.032941 14 1990 12 0.041522 0.050114 15 1991 1 0.303987 0.127202 16 1991 2 0.057325 -0.003883 17 1991 3 0.022892 0.021442 18 1991 4 -0.067138 0.036641 19 1991 5 0.108586 0.053704 20 1991 6 -0.068907 -0.050967 21 1991 0.078899 0.052222 22 1991 8 0.159864 -0.019469 23 9 0.043988 -0.077617 24 1991 10 0.054775 -0.001566 25 1991 11 0.035952 -0.076923 26 1991 12 0.143959 0.100427 27 1992 1 0.080899 0.001942 28 1992 2 0.027027 0.081783 29 1992 3 -0.040486 0.016216 30 1992 4 -0.06962 0.103191 31 1992 5 0.097506 0.003231 32 1992 6 -0.132231 -0.022544 33 1992 7 0.039286 -0.028007 34 1992 8 0.024055 0.118305 35 9 0.080537 0.025145 36 1992 10 0.102484 0.05283 37 1992 11 0.049296 0.011111 38 1992 12 -0.083221 0.02139 39 1993 1 0.013177 0.038394 40 1993 2 -0.036127 -0.051765 41 1993 3 0.109445 -0.080214 42 1993 4 -0.075676 0.025194 43 1993 5 0.083333 0.026843 44 1993 6 0.049933 0.037037 45 1993 7 -0.159091 0.017857 46 1993 8 0.015203 0.06 47 1993 9 0.09817 -0.106489 48 1993 10 -0.028788 0.013035 49 1993 11 -0.00156 0.024265 50 1993 12 0.007813 0.001805 51 1994 1 0.055814 0.146306 52 1994 2 0.030837 -0.048973 53 1994 3 0.027273 -0.048173 54 1994 4 0.091445 -0.050611 55 1994 5 0.162162 0.044485 56 1994 6 -0.039535 0.035398 57 1994 7 -0.002421 0.070085 58 1994 8 0.128641 0.078594 59 1994 9 -0.034409 0.008929 60 1994 10 0.122494 0.010619 61 1994 11 -0.001984 -0.042522 62 1994 12 -0.027833 0.061256 63 1995 1 -0.02863 -0.087157 64 1995 2 0.061053 -0.007949 65 1995 3 0.128968 0.064103 66 1995 4 0.149385 0.081325 67 1995 5 0.035933 0.041226 68 6 0.067159 0.077957 69 1995 7 0.001383 0.137157 70 1995 8 0.022099 0.00614 71 1995 9 -0.021622 -0.074398 72 1995 10 0.104972 -0.035461 73 1995 11 -0.12875 0.151471 74 1995 12 0.007174 0.096154 75 1996 1 0.054131 0.055934 76 1996 2 0.066892 0.024775 77 1996 3 0.044965 0.101099 78 1996 4 0.098182 -0.003992 79 1996 5 0.048565 -0.006693 80 1996 6 0.011579 -0.068966 81 1996 7 -0.01873 0.016688 82 1996 8 0.039236 0.071121 83 1996 9 0.076531 -0.050302 84 1996 10 0.040758 -0.00072 85 1996 11 0.142987 0.085288 86 1996 12 0.053386 0.001965 87 1997 1 0.234493 0.082353 88 1997 2 -0.044118 0.03587 89 1997 3 -0.059615 -0.045614 90 1997 4 0.325153 0.03125 91 1997 5 0.020576 0.053667 92 1997 6 0.019153 0.023769 93 1997 7 0.119683 0.174129 94 1997 8 -0.065813 -0.067797 95 1997 9 0.000946 -0.00304 96 1997 10 -0.017478 -0.109756 97 1997 11 0.0884620.075342 98 1997 12 -0.086572 0.046468 99 1998 1 0.154255 0.085258 100 1998 2 0.136154 -0.036007 101 1998 3 0.056047 -0.062181 102 1998 4 0.006983 0.126249 1995 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2001 2001 2001 2001 2001 2001 2001 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 2001 2001 2001 2001 2001 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2006 2006 2006 1 0.154255 0.085258 2 0.136154 -0.036007 3 0.056047 0.062181 4 0.006983 0.126249 5 -0.058946 -0.101613 6 0.277819 -0.04955 7 0.014418 0.051185 8 -0.127345 -0.130748 9 0.147231 0.185804 10 -0.038047 0.116197 11 0.152302 -0.05836 12 0.136783 0.004209 1 0.26183 0.120704 2 -0.142143 -0.025849 3 0.194005 0.016975 4 -0.092748 0.511381 5 -0.007686 0.113225 6 0.117738 0.125 7 -0.04851 -0.032323 8 0.07866 0.081649 9 -0.021607 -0.038722 10 0.022084 -0.021148 11 -0.016374 0.081502 12 0.282306 0.267176 1 -0.16167 -0.160392 2 -0.086845 -0.013453 3 0.188811 0.025547 4 -0.343529 -0.076512 5 -0.103047 -0.095376 6 0.278721 -0.007487 7 -0.127344 0.043103 8 0 0.103306 9 -0.136079 0.238722 10 0.141969 0.133333 11 -0.166969 -0.013072 12 -0.244009 0.18847 1 0.407781 0.101194 2 -0.033777 -0.026674 3 -0.073093 0.005313 4 0.238857 0.151599 5 0.021107 0.045894 6 0.055218 -0.086906 7 -0.093288 -0.004315 8 -0.138087 -0.024471 9 -0.103068 -0.186516 10 0.136408 0.045469 11 0.104213 0.196157 12 0.031771 -0.079016 1 -0.03834 0.008439 2 -0.084288 0.052162 3 0.033768 0.004525 4 -0.133477 -0.098304 5 -0.025832 0.032324 6 0.074445 -0.052316 7 -0.122852 -0.179487 8 0.022926 -0.072458 9 -0.108802 -0.230769 10 0.222451 0.143005 11 0.078736 0.165005 12 -0.103675 -0.108415 1 -0.082012 -0.132133 2 0.002107 0.044512 3 0.021519 -0.054634 4 0.055762 0.190919 5 -0.037167 0.073266 6 0.041853 0.036164 7 0.030031 0.08902 8 0.004165 0.033849 9 0.048265 -0.084034 10 0.053957 0.206804 11 -0.01645 0.044029 12 0.064566 0.158183 1 0.01023 -0.100526 2 -0.040506 0.100644 3 -0.060309 -0.074193 4 0.048135 -0.113577 5 0.003827 0.022764 6 0.08883 0.055272 7 -0.002451 -0.030276 8 -0.038961 0.01561 9 0.012821 0.037369 10 0.011573 -0.03245 11 0.068645 0.050154 12 -0.003357 -0.075338 1 -0.016467 -0.060789 2 -0.039574 0.093528 3 -0.039348 -0.053861 4 0.046752 -0.045081 5 0.022925 -0.060992 6 -0.037209 -0.035793 7 0.030998 0.073479 8 0.072237 0.039572 9 -0.060263 -0.088466 10 -0.001166 -0.005323 11 0.080156 0.134623 12 -0.055275 0.078803 1 0.076482 0.065269 2 -0.042273 -0.064444 3 0.012653 0.042292 4 -0.112459 0.105366 5 -0.058385 -0.056542 6 0.028698 0.020177 7 0.032618 -0.074475 8 0.071904 -0.040401 2006 2006 2006 2006 2006 1 199 2006 200 2006 201 2006 202 2006 203 2006 204 2006 205 2006 206 2006 207 2007 208 2007 209 2007 210 2007 211 2007 212 2007 213 2007 214 2007 215 2007 216 2007 217 2007 218 2007 219 2008 220 2008 221 2008 222 2008 223 2008 224 2008 225 2008 226 2008 227 2008 228 2008 229 2008 230 008 231 2009 232 2009 233 2009 234 2009 235 2009 236 2009 237 2009 238 2009 239 2009 240 2009 241 2009 242 2009 243 2010 244 2010 245 2010 246 2010 247 2010 248 2010 249 2010 250 2010 251 2010 252 2010 253 2010 254 2010 255 2011 256 2011 257 2011 258 2011 259 2011 260 2011 261 2011 262 2011 263 2011 264 2011 265 2011 266 2011 267 2012 268 2012 269 2012 270 2012 271 2012 272 2012 273 2012 274 2012 275 2012 276 277 2012 278 2012 279 2013 280 2013 281 2013 282 2013 283 2013 284 2013 285 2013 286 2013 287 2013 288 2013 289 2013 290 2013 291 2014 292 2014 293 2014 294 2014 295 2014 296 2014 297 2014 298 2014 299 2014 300 2014 301 302 2014 303 5 -0.058385 -0.056542 6 0.028698 0.020177 7 0.032618 -0.074475 8 0.071904 -0.040401 9 0.064202 -0.019237 10 0.049726 0.031027 11 0.026123 0.083362 12 0.01703 -0.037215 1 0.03349 0.081973 2 -0,083927 0.034365 3 -0.01065 0.014666 4 0.074273 0.046903 5 0.028393 0.167935 6 -0.039756 -0.018169 7 -0.016288 -0.057488 8 -0.005519 -0.039267 9 0.025409 0.070901 10 0.249491 0.01636 11 -0.084216 -0.081334 12 0.059524 0.004949 1 -0.08427 -0.094665 2 -0.162273 0.127531 30.043386 -0.029079 4 0.004933 -0.030782 5 -0.003156 0.16705 6 -0.028602 -0.122444 7 -0.065067 -0.052499 8 0.065319 -0.042963 9 -0.021986 -0.29723 100.163357 -0.4907 11 -0.08867 -0.049565 12 -0.038576 0.046468 1 -0.12037 -0.308171 2 -0.047953 -0.178434 3 0.137461 0.17817 4 0.102885 0.235695 5 0.037512 0.019846 6 0.137865 0.12039 7 -0.010517 0.138432 8 0.053571 0.027211 9 0.043408 0.088797 10 0.078149 -0.053354 11 0.065272 0.010467 12 0.036382 0.28754 1 -0.075459 -0.210298 2 0.022001 0.047133 3 0.021538 0.070677 4 0.042595 -0.056882 50.150811 -0.13105 6 -0.108140.135739 70.121686 0.110338 8 -0.085819 0.062587 9 0.043682 0.185221 10 0.088812 0.085054 11 -0.046784 0.001142 12 0.105018 0.172571 1 -0.006628 0.076673 2 -0.035528 0.018709 3 -0.044771 0.048071 4 0.020874 -0.037373 5 -0.028935 -0.009412 6 0.039584 -0.056514 7 0.053846 -0.071248 8 -0.023358 0.128988 9 -0.064286 -0.252344 10 0.069908 0.124347 11 -0.031919 -0.065985 12 0.014855 -0.136727 1 0.137519 0.174567 2 0.081612 0.003937 30.016226 -0.014749 4 -0.007441 -0.028942 50.081993 0.118191 6 0.047962 0.023392 7 0.036613 -0.032 8 0.052596 0.014168 9 -0.034393 0.034463 100.040995 -0.028797 11 -0.05939 -0.01867 12 0.003558 0.032105 1 0.027217 0.018433 2 0.021129 -0.032805 3 0.028957 0 4 0.15714 -0.002347 5 0.061329 0.003529 6 -0.010172 -0.08 7 -0.078304 8 0.056219 +0.027673 9 -0.003593 0.054545 10 0.063852 0.141626 11 0.084875 0.039914 12 0.018883 0.106139 10.011494 0.082785 2 0.01982 0.022589 3 0.069956 0.096252 4 -0.014394 0.04662 5 0.020297 0.012621 6 0.018564 0.094049 7 0.035012 0.100739 8 0.059082 0.015253 90.020471 0.031306 10 0.012726 0.041641 11 0.02492 0.033413 12 -0.028446 -0.086755 2012 2014