Hi, I have an assignment I need help getting done. It is a statistics/finance assignment that involves regression models. The instructions are in the Week 2 Assignment 2 document, and the data is in the excel documents.

Please do not claim this lesson unless you know how to do these problems and can help by the deadline. If you are unsure on how to do this or you aren't sure you can make it before the deadline do not claim this lesson,thank you for your help!

Date Return 1/3/2012 0.015373 1/4/2012 0.005382 1/5/2012 0.011107 1/6/2012 0.01044 1/9/2012 -0.001591 1/10/2012 0.00358 1/11/2012 -0.001613 1/12/2012 -0.002741 1/13/2012 -0.003755 1/17/2012 0.011653 1/18/2012 0.010374 1/19/2012 -0.003181 1/20/2012 -0.017409 1/23/2012 0.01693 1/24/2012 -0.016382 1/25/2012 0.062435 1/26/2012 -0.004538 1/27/2012 0.005955 1/30/2012 0.01281 1/31/2012 0.007648 2/1/2012 -0.000634 2/2/2012 -0.002335 2/3/2012 0.010021 2/6/2012 0.009337 2/7/2012 0.010477 2/8/2012 0.016743 2/9/2012 0.034584 2/10/2012 0.000503 2/13/2012 0.018613 2/14/2012 0.013643 2/15/2012 -0.023143 2/16/2012 0.009123 2/17/2012 -0.000185 2/21/2012 0.025355 2/22/2012 -0.003515 2/23/2012 0.006531 2/24/2012 0.011656 2/27/2012 0.006414 2/28/2012 0.018353 2/29/2012 0.013135 3/1/2012 0.003737 3/2/2012 0.001311 3/5/2012 -0.022043 3/6/2012 -0.005451 3/7/2012 0.000819 3/8/2012 0.021281 3/9/2012 0.005877 3/12/2012 0.012521 3/13/2012 0.029172 3/14/2012 0.037812 3/15/2012 -0.006824 3/16/2012 1.77E-005 3/19/2012 0.026528 3/20/2012 0.008087 3/21/2012 -0.005718 3/22/2012 -0.005236 3/23/2012 -0.005487 3/26/2012 0.018323 3/27/2012 0.01237 3/28/2012 0.0051 3/29/2012 -0.012559 3/30/2012 -0.016907 4/2/2012 0.031826 4/3/2012 0.01727 4/4/2012 -0.007954 4/5/2012 0.015009 4/9/2012 0.004031 4/10/2012 -0.012257 4/11/2012 -0.003555 4/12/2012 -0.005483 4/13/2012 -0.028165 4/16/2012 -0.041473 4/17/2012 0.050969 4/18/2012 -0.002222 4/19/2012 -0.034358 4/20/2012 -0.024613 4/23/2012 -0.002238 4/24/2012 -0.019972 4/25/2012 0.088733 4/26/2012 -0.003764 4/27/2012 4/30/2012 5/1/2012 5/2/2012 5/3/2012 5/4/2012 5/7/2012 5/8/2012 5/9/2012 5/10/2012 5/11/2012 5/14/2012 5/15/2012 5/16/2012 5/17/2012 5/18/2012 5/21/2012 5/22/2012 5/23/2012 5/24/2012 5/25/2012 5/29/2012 5/30/2012 5/31/2012 6/1/2012 6/4/2012 6/5/2012 6/6/2012 6/7/2012 6/8/2012 6/11/2012 6/12/2012 6/13/2012 6/14/2012 6/15/2012 6/18/2012 6/19/2012 6/20/2012 6/21/2012 6/22/2012 6/25/2012 6/26/2012 6/27/2012 6/28/2012 6/29/2012 7/2/2012 7/3/2012 7/5/2012 7/6/2012 7/9/2012 7/10/2012 7/11/2012 7/12/2012 7/13/2012 7/16/2012 7/17/2012 7/18/2012 7/19/2012 7/20/2012 7/23/2012 7/24/2012 7/25/2012 7/26/2012 7/27/2012 7/30/2012 7/31/2012 8/1/2012 8/2/2012 8/3/2012 8/6/2012 8/7/2012 8/8/2012 8/9/2012 8/10/2012 8/13/2012 8/14/2012 8/15/2012 8/16/2012 8/17/2012 8/20/2012 8/21/2012 -0.007726 -0.031558 -0.003152 0.006609 -0.007095 -0.028494 0.007483 -0.00227 0.001747 0.002362 -0.006671 -0.014983 -0.00906 -0.012807 -0.029223 0.000488 0.058265 -0.007684 0.024399 -0.00919 -0.00536 0.017749 0.012054 -0.002482 -0.028965 0.005881 -0.002603 0.015344 0.000452 0.015051 -0.015772 0.008728 -0.006929 -0.001103 0.004542 0.020302 0.002772 -0.002835 -0.01379 0.007681 -0.019473 0.002211 0.004321 -0.009487 0.026262 0.014593 0.011625 0.017582 -0.006664 0.013229 -0.009266 -0.006207 -0.009154 0.010137 0.003214 5.11E-005 -0.001125 0.013289 -0.016313 -0.00077 -0.00483 -0.043182 -0.000144 0.017882 0.016861 0.026437 -0.006469 0.001619 0.013017 0.01112 -0.002641 -0.001682 0.005706 0.001559 0.013351 0.002681 -0.001369 0.008734 0.018498 0.026297 -0.013671 8/22/2012 8/23/2012 8/24/2012 8/27/2012 8/28/2012 8/29/2012 8/30/2012 8/31/2012 9/4/2012 9/5/2012 9/6/2012 9/7/2012 9/10/2012 9/11/2012 9/12/2012 9/13/2012 9/14/2012 9/17/2012 9/18/2012 9/19/2012 9/20/2012 9/21/2012 9/24/2012 9/25/2012 9/26/2012 9/27/2012 9/28/2012 10/1/2012 10/2/2012 10/3/2012 10/4/2012 10/5/2012 10/8/2012 10/9/2012 10/10/2012 10/11/2012 10/12/2012 10/15/2012 10/16/2012 10/17/2012 10/18/2012 10/19/2012 10/22/2012 10/23/2012 10/24/2012 10/25/2012 10/26/2012 10/31/2012 11/1/2012 11/2/2012 11/5/2012 11/6/2012 11/7/2012 11/8/2012 11/9/2012 11/12/2012 11/13/2012 11/14/2012 11/15/2012 11/16/2012 11/19/2012 11/20/2012 11/21/2012 11/23/2012 11/26/2012 11/27/2012 11/28/2012 11/29/2012 11/30/2012 12/3/2012 12/4/2012 12/5/2012 12/6/2012 12/7/2012 12/10/2012 12/11/2012 12/12/2012 12/13/2012 12/14/2012 12/17/2012 12/18/2012 0.019527 -0.00933 0.000901 0.018788 -0.001311 -0.001969 -0.014251 0.002063 0.014629 -0.007033 0.009019 0.006167 -0.026016 -0.003248 0.013937 0.01968 0.012153 0.012305 0.003046 0.000264 -0.00484 0.00199 -0.013283 -0.02497 -0.012415 0.02426 -0.020874 -0.011547 0.002905 0.015339 -0.006932 -0.021313 -0.022092 -0.003631 0.007952 -0.019988 0.002574 0.008013 0.02367 -0.007972 -0.018564 -0.036039 0.039666 -0.032598 0.005658 -0.01182 -0.009089 -0.014373 0.002059 -0.033093 0.013551 -0.00303 -0.038252 -0.036302 0.017309 -0.00772 0.000132 -0.011103 -0.020965 0.00392 0.072113 -0.008535 0.001426 0.017447 0.031534 -0.008051 -0.003155 0.011026 -0.006923 0.001559 -0.017645 -0.064354 0.015678 -0.02557 -0.006421 0.021825 -0.004412 -0.017269 -0.037565 0.017736 0.029044 12/19/2012 12/20/2012 12/21/2012 12/24/2012 12/26/2012 12/27/2012 12/28/2012 12/31/2012 1/2/2013 1/3/2013 1/4/2013 1/7/2013 1/8/2013 1/9/2013 1/10/2013 1/11/2013 1/14/2013 1/15/2013 1/16/2013 1/17/2013 1/18/2013 1/22/2013 1/23/2013 1/24/2013 1/25/2013 1/28/2013 1/29/2013 1/30/2013 1/31/2013 2/1/2013 2/4/2013 2/5/2013 2/6/2013 2/7/2013 2/8/2013 2/11/2013 2/12/2013 2/13/2013 2/14/2013 2/15/2013 2/19/2013 2/20/2013 2/21/2013 2/22/2013 2/25/2013 2/26/2013 2/27/2013 2/28/2013 3/1/2013 3/4/2013 3/5/2013 3/6/2013 3/7/2013 3/8/2013 3/11/2013 3/12/2013 3/13/2013 3/14/2013 3/15/2013 3/18/2013 3/19/2013 3/20/2013 3/21/2013 3/22/2013 3/25/2013 3/26/2013 3/27/2013 3/28/2013 4/1/2013 4/2/2013 4/3/2013 4/4/2013 4/5/2013 4/8/2013 4/9/2013 4/10/2013 4/11/2013 4/12/2013 4/15/2013 4/16/2013 4/17/2013 -0.014228 -0.008706 -0.004598 0.001619 -0.013776 0.004017 -0.010628 0.044317 0.031688 -0.012622 -0.027854 -0.005894 0.0027 -0.015631 0.01239 -0.006129 -0.035662 -0.031546 0.041518 -0.006745 -0.005323 0.009534 0.018298 -0.123552 -0.023574 0.022629 0.018755 -0.003132 -0.00294 -0.004119 -0.024904 0.035089 -0.001075 0.029744 0.014432 0.010428 -0.02508 -0.001895 -0.000895 -0.013783 -0.000377 -0.024217 -0.006222 0.01067 -0.01777 0.013925 -0.009807 -0.00713 -0.024752 -0.02422 0.026423 -0.012718 0.011565 0.002627 0.014259 -0.021553 -0.00019 0.009684 0.025804 0.027176 -0.002684 -0.005315 0.001443 0.020283 0.003619 -0.005276 -0.019648 -0.020831 -0.031059 0.002044 0.005122 -0.009885 -0.010556 0.007104 0.001793 0.020409 -0.003111 -0.010442 -0.023144 0.01522 -0.054995 4/18/2013 4/19/2013 4/22/2013 4/23/2013 4/24/2013 4/25/2013 4/26/2013 4/29/2013 4/30/2013 5/1/2013 5/2/2013 5/3/2013 5/6/2013 5/7/2013 5/8/2013 5/9/2013 5/10/2013 5/13/2013 5/14/2013 5/15/2013 5/16/2013 5/17/2013 5/20/2013 5/21/2013 5/22/2013 5/23/2013 5/24/2013 5/28/2013 5/29/2013 5/30/2013 5/31/2013 6/3/2013 6/4/2013 6/5/2013 6/6/2013 6/7/2013 6/10/2013 6/11/2013 6/12/2013 6/13/2013 6/14/2013 6/17/2013 6/18/2013 6/19/2013 6/20/2013 6/21/2013 6/24/2013 6/25/2013 6/26/2013 6/27/2013 6/28/2013 7/1/2013 7/2/2013 7/3/2013 7/5/2013 7/8/2013 7/9/2013 7/10/2013 7/11/2013 7/12/2013 7/15/2013 7/16/2013 7/17/2013 7/18/2013 7/19/2013 7/22/2013 7/23/2013 7/24/2013 7/25/2013 7/26/2013 7/29/2013 7/30/2013 7/31/2013 8/1/2013 8/2/2013 8/5/2013 8/6/2013 8/7/2013 8/8/2013 8/9/2013 8/12/2013 -0.026694 -0.003873 0.020852 0.018713 -0.001656 0.007189 0.021613 0.030952 0.029454 -0.007895 0.014199 0.009997 0.02385 -0.004447 0.011288 -0.008723 -0.008312 0.003889 -0.023913 -0.033828 0.013363 -0.003029 0.022317 -0.007383 0.003846 0.001789 0.006801 -0.008325 0.007959 0.014882 -0.004081 0.002184 -0.003122 -0.009352 -0.014922 0.00762 -0.0066 -0.00293 -0.012378 0.008738 -0.013563 0.004544 -0.000539 -0.020307 -0.014577 -0.008016 -0.026494 0.000226 -0.011341 -0.010759 0.006968 0.032019 0.022638 0.005516 -0.008036 -0.005676 0.017588 -0.003836 0.015594 -0.001825 0.002184 0.006467 0.000259 0.003365 -0.015782 0.003217 -0.017171 0.05135 -0.004551 0.005657 0.015429 0.012345 -0.001742 0.009173 0.012837 0.014929 -0.008929 -0.000588 -0.002003 -0.014226 0.028419 8/13/2013 8/14/2013 8/15/2013 8/16/2013 8/19/2013 8/20/2013 8/21/2013 8/22/2013 8/23/2013 8/26/2013 8/27/2013 8/28/2013 8/29/2013 8/30/2013 9/3/2013 9/4/2013 9/5/2013 9/6/2013 9/9/2013 9/10/2013 9/11/2013 9/12/2013 9/13/2013 9/16/2013 9/17/2013 9/18/2013 9/19/2013 9/20/2013 9/23/2013 9/24/2013 9/25/2013 9/26/2013 9/27/2013 9/30/2013 10/1/2013 10/2/2013 10/3/2013 10/4/2013 10/7/2013 10/8/2013 10/9/2013 10/10/2013 10/11/2013 10/14/2013 10/15/2013 10/16/2013 10/17/2013 10/18/2013 10/21/2013 10/22/2013 10/23/2013 10/24/2013 10/25/2013 10/28/2013 10/29/2013 10/30/2013 10/31/2013 11/1/2013 11/4/2013 11/5/2013 11/6/2013 11/7/2013 11/8/2013 11/11/2013 11/12/2013 11/13/2013 11/14/2013 11/15/2013 11/18/2013 11/19/2013 11/20/2013 11/21/2013 11/22/2013 11/25/2013 11/26/2013 11/27/2013 11/29/2013 12/2/2013 12/3/2013 12/4/2013 12/5/2013 0.04752 0.018244 -0.00119 0.008868 0.010773 -0.013134 0.002569 0.001201 -0.00386 0.003895 -0.028597 0.004735 0.001639 -0.009123 0.002787 0.020711 -0.006858 0.00595 0.015949 -0.022773 -0.054436 0.010645 -0.016491 -0.031783 0.011553 0.020544 0.016408 -0.01035 0.049688 -0.003137 -0.015486 0.009755 -0.007137 -0.012439 0.023524 0.003277 -0.012574 -0.00077 0.009766 -0.013961 0.011754 0.006263 0.006471 0.006552 0.005333 0.004861 0.006764 0.008713 0.024489 -0.002855 0.00979 0.01324 -0.011176 0.007439 -0.024905 0.015905 -0.004177 -0.005119 0.01292 -0.002463 -0.002833 -0.016183 0.015747 -0.002901 0.00185 0.001192 0.014463 -0.006002 -0.012115 0.001774 -0.008758 0.011922 -0.002571 0.00758 0.018444 0.023547 0.018518 -0.008704 0.027375 -0.002331 0.005133 12/6/2013 12/9/2013 12/10/2013 12/11/2013 12/12/2013 12/13/2013 12/16/2013 12/17/2013 12/18/2013 12/19/2013 12/20/2013 12/23/2013 12/24/2013 12/26/2013 12/27/2013 12/30/2013 12/31/2013 -0.013876 0.011446 -0.001554 -0.007409 -0.001461 -0.0109 0.005537 -0.004502 -0.007604 -0.011457 0.008375 0.038377 -0.004245 -0.006641 -0.006757 -0.009945 0.011722 crsp_fund 23325 28387 5745 21176 3940 18737 30579 16630 19249 31877 3091 8359 45613 7354 10596 19408 23816 25249 26385 27649 12802 15477 17584 9469 8798 12238 8995 19631 28328 14803 17389 11041 11163 13036 31144 4055 14726 22907 4051 24124 30112 7619 7907 8971 19974 11995 25467 14251 20025 32186 19988 32171 26630 4273 18304 caldt 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 20091231 Average Median Max Min 3-yr ret tna_latest logtna size_sq exp_ratio turn_ratio age_mo sigma -0.01637 723.8 2.859619 1.468169 0.0135 1.7 279 0.065071 -0.18559 25.1 1.399674 0.061635 0.0197 1.56 300 0.069881 -0.33216 5 0.69897 0.900541 0.0141 1.37 79 0.064068 -0.10159 36 1.556303 0.008397 0.0202 0.25 149 0.068163 -0.09524 303.6 2.482302 0.696162 0.0138 0.62 167 0.071096 0.04849 526.7 2.721563 1.15267 0.0128 1.99 434 0.076686 -0.21856 35.7 1.552668 0.009076 0.0128 0.73 132 0.072092 -0.04437 111.3 2.046495 0.158847 0.0171 0.85 113 0.066373 -0.00534 301.2 2.478855 0.690422 0.016 1.5 155 0.080889 -0.04096 482 2.683047 1.07145 0.0179 0.87 122 0.066315 -0.08256 781.8 2.893096 1.550417 0.0128 0.29 170 0.067572 -0.26664 30.2 1.480007 0.028201 0.0125 0.95 90 0.08039 -0.20906 2.3 0.361728 1.654338 0.0161 3.13 55 0.062957 -0.11757 182.3 2.260787 0.375583 0.0129 0.23 110 0.069277 -0.09232 46.7 1.669317 0.000457 0.0133 1.18 174 0.070156 -0.1659 37.3 1.571709 0.005811 0.0126 8.65 163 0.073974 -0.07805 81.7 1.912222 0.069846 0.0127 1.19 151 0.066941 -0.21509 13.4 1.127105 0.271268 0.0195 0.78 54 0.071235 -0.08497 414.9 2.617943 0.94091 0.0149 1.59 275 0.072125 -0.13468 10.9 1.037426 0.372725 0.0151 1.57 120 0.067605 -0.01849 3.8 0.579784 1.140955 0.0185 0.9 44 0.073269 -0.06558 71 1.851258 0.041339 0.015 1.78 174 0.067997 -0.11591 137.1 2.137037 0.239218 0.0125 0.83 221 0.074404 -0.19076 5.6 0.748188 0.809551 0.0177 2.34 120 0.065168 -0.09831 307.1 2.48728 0.704494 0.0104 1.1 494 0.077506 -0.16368 7 0.845098 0.644553 0.0126 0.81 204 0.07634 -0.21074 6.6 0.819544 0.686237 0.019 1.19 76 0.071692 -0.19577 187.3 2.272538 0.390124 0.0149 0.67 90 0.078377 -0.2759 11.4 1.056905 0.349321 0.026 2 146 0.072342 -0.15091 305.6 2.485153 0.700929 0.0132 1.8 161 0.067912 -0.18824 77.2 1.887617 0.057446 0.015 0.83 151 0.067886 -0.15281 781.7 2.89304 1.550278 0.0195 0.9 84 0.074252 -0.25345 20.9 1.320146 0.107448 0.0175 2.44 51 0.064663 -0.11571 167.1 2.222976 0.330669 0.0134 0.43 115 0.07399 -0.08475 684.2 2.835183 1.40955 0.014 2.19 109 0.058908 -0.27313 0.3 -0.52288 4.712447 0.012 1.86 51 0.061316 -0.19241 49.4 1.693727 0.002097 0.0107 0.84 94 0.070081 -0.15944 0.9 -0.04576 2.868606 0.0136 2.9 77 0.065529 -0.19423 17.4 1.240549 0.165966 0.012 1.28 51 0.064478 -0.12752 1.2 0.079181 2.460999 0.0144 0.64 42 0.072702 -0.15102 10.7 1.029384 0.38261 0.014 1.13 39 0.067195 -0.16799 132.4 2.121888 0.224628 0.0127 1.3 168 0.071043 -0.0501 61.6 1.789581 0.020063 0.0137 1.49 49 0.068976 -0.14725 7.2 0.857332 0.625058 0.0097 1.24 101 0.076989 -0.2299 5.6 0.748188 0.809551 0.0147 2.63 115 0.070184 -0.08827 44.7 1.650308 5.6E-006 0.0133 1.5 61 0.072957 -0.06926 23.8 1.376577 0.073637 0.015 0.43 48 0.068459 -0.16435 314.9 2.498173 0.722898 0.0149 0.58 191 0.078386 -0.22728 13.4 1.127105 0.271268 0.0156 1.29 96 0.071919 0.028424 179.9 2.255031 0.368562 0.014 0.76 233 0.080269 -0.0888 75.4 1.877371 0.052639 0.0152 0.92 127 0.072446 -0.16576 2.9 0.462398 1.405506 0.0144 1.69 71 0.074651 -0.19753 49.3 1.692847 0.002017 0.0159 1.33 107 0.069662 -0.11197 158 2.198657 0.303291 0.0162 1.08 490 0.076154 -0.07756 451.2 2.654369 1.012903 0.0131 0.41 137 0.069425 -0.13773 155.0127 1.647938 0.67516 0.014811 1.391091 143.2727 0.070734 -0.14725 49.3 1.692847 0.375583 0.0141 1.19 120 0.070184 0.04849 781.8 2.893096 4.712447 0.026 8.65 494 0.080889 -0.33216 0.3 -0.52288 5.6E-006 0.0097 0.23 39 0.058908 fund_namenasdaq Oppenheime OPOCX Seligman FrSLFRX BB&T Funds BTVAX Morgan StanMPAX S Alger FundsALSAX Lord AbbetLAGWX UBS Funds:BNSCX Ivy Funds, WSGAX MFS Series MNDAX Waddell & R UNSAX AIM Growth GTSAX DWS Adviso SSDAX Forward FunFHAX F Columbia ALAUAX Evergreen EEGWAX MTB GroupARPAX RS Investme GPSCX Principal F PPSMX RS Investme RSEGX RidgeWorth SCGIX Forum Fund BASAX ING Equity NSPAX JPMorgan Tr GSGX P Dreyfus FouFDIDX Delaware Gr ELTX D Fifth Third KNEMX Optimum Fu ASGX O Managers A MBRSX Security Eq SSCAX Hartford Mu IHSAX JPMorgan TVSCOX Federated FKASX Federated QASGX Franklin St FSGRX Van Kampen ASCX V Allegiant F ALOAX Hartford Mu HSLAX Old MutualOSSAX Allegiant F ALWAX Virtus Equi PSGAX TouchstoneTDSAX Columbia Fu SCGX N Columbia Fu GOAX C Delaware Gr SCAX D MassMutual MMEGX Fidelity Se FCAGX ProfessionaSTSGX John HancocPVAX S MassMutual MRWAX Wells FargoMNSCX MassMutual MMGEX Wells Farg WFSAX RiverSource AXSCX AllianceBerQUASX Legg Mason SASMX retail_fundend_dt Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 Y 20091231 lipper_claslipper_cla SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap SCGE Small-Cap lipper_obj SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG SG lipper_obj_name SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SMALL-CAP FUNDS SUMMARY OUTPUT Regression using logtna Regression Statistics Multiple R 0.571514 R Square 0.326628 Adjusted R 0.257916 Standard E 0.068798 Observatio 55 Average Median Max Min ANOVA df Regression Residual Total SS MS 5 0.112499 0.0225 49 0.231927 0.004733 54 0.344427 Coefficients Standard Error t Stat Intercept -0.21642 0.155375 -1.39287 logtna 0.044232 0.013394 3.302439 exp_ratio -2.27984 3.336067 -0.68339 F Significance F 4.753615 0.00128 P-value Lower 95%Upper 95% Lower 95.0%pper 95.0% U 0.169947 -0.52866 0.095821 -0.52866 0.095821 0.001795 0.017316 0.071148 0.017316 0.071148 0.497579 -8.98392 4.424239 -8.98392 4.424239 3-yr ret tna_latest logtna exp_ratio turn_ratio age_mo -0.13773 155.0127 1.647938 0.014811 1.391091 143.2727 -0.14725 49.3 1.692847 0.0141 1.19 120 0.04849 781.8 2.893096 0.026 8.65 494 -0.33216 0.3 -0.52288 0.0097 0.23 39 sigma 0.070734 0.070184 0.080889 0.058908 turn_ratio -0.00452 0.008174 -0.55304 0.582752 -0.02095 0.011906 -0.02095 0.011906 age_mo 9.8E-005 0.000113 0.871236 0.387874 -0.00013 0.000325 -0.00013 0.000325 sigma 0.449358 2.063128 0.217804 0.828486 -3.69665 4.595368 -3.69665 4.595368 SUMMARY OUTPUT Regression using logtna and size_sq Regression Statistics Multiple R 0.585437 R Square 0.342736 Adjusted R 0.260578 Standard E 0.068675 Observatio 55 ANOVA df Regression Residual Total Intercept logtna size_sq exp_ratio turn_ratio age_mo sigma SS MS F Significance F 6 0.118047 0.019675 4.171673 0.001878 48 0.226379 0.004716 54 0.344427 Coefficients Standard Error t Stat -0.28476 0.167407 -1.70099 0.049543 0.014238 3.479589 0.013532 0.012476 1.084618 -1.7188 3.370013 -0.51003 -0.00411 0.008168 -0.50357 8.1E-005 0.000114 0.708726 1.07285 2.138149 0.501766 P-value Lower 95%Upper 95% Lower 95.0%pper 95.0% U 0.095415 -0.62135 0.051836 -0.62135 0.051836 0.001079 0.020915 0.078171 0.020915 0.078171 0.283509 -0.01155 0.038618 -0.01155 0.038618 0.612369 -8.49467 5.057064 -8.49467 5.057064 0.616868 -0.02054 0.012309 -0.02054 0.012309 0.481922 -0.00015 0.000309 -0.00015 0.000309 0.618126 -3.22619 5.371886 -3.22619 5.371886 Part 1: Recall the weak form of the efficient markets hypothesis. It states that there is no useful information in past prices or returns that would allow us to forecast future returns. You will test this hypothesis with a time series of daily returns for Apple. Suppose you could forecast future stock prices by examining patterns in past prices or returns. This would be a great way to make money, and there is a field of study, technical analysis, where practitioners try to identify recurring patterns in stock prices and returns. However, there is a considerable body of evidence suggesting there is no useful memory in past prices. Let's do a quick experiment. The spreadsheet attached to this assignment contains two years of daily stock returns for Apple. The experiment is simple. Is today's return explained by the returns generated over each of the previous five trading days? The regression approach can be modeled like this: Rt = a + b1(Rt-1) + b2(Rt-2) + b3(Rt-3) + b4(Rt-4) + b5(Rt-5) + e The spreadsheet contains 502 daily returns. These are your Rt, or dependent variables. You will need to create five additional columns with the lagged returns. The lagged returns are just those occurring 1, 2, 3, 4, and 5 days prior to a particular value of Rt. Note that this means you must discard the first 5 observations. It's not until the 5th day of your sample that you can compute a complete set of independent variables. 1. 2. What are the null and alternative hypotheses associated with this test? Run the regression described above. Discuss your results. Do they support the weak form of the efficient markets hypothesis? Why or why not? 3. Attach a copy of the Excel output for your regression analysis. Click the hyperlink below to download the file to your computer. Problem Set 3 Part 2: Recall the analysis of our sample of small cap growth oriented mutual funds in Lesson 2. The data behind this analysis is linked to a slide within the lesson. In the analysis presented in Lesson 2, we ran two regressions. The first employed logtna (the log of total net assets under management, column E) and a number of control variables to explain returns on our sample of funds. The second regression added [logtna - avg.logtna]2, denoted on the spreadsheet as size_sq (column F). 1. Rerun the first regression using the raw (unlogged) values of total net assets (column D on the spreadsheet instead of column E). Use the control variables in columns G through J as well. (Note: You may want to rearrange the columns before running the new regression.) 2. Before rerunning the second regression, recreate the values for the quadratic term, size_sq (column F) using raw (unlogged) values of total net assets. In other words, create a variable: [tna - avg.tna]2.Now rerun the second regression. 3. Calculate VIFs for each independent variable. Is multicollinearity a problem with this regression? 4. Discuss your results for both of the new regressions focusing on the expected signs and significance of the independent variables. Also discuss any differences between these results and the original regressions that used the logged values of total net assets