A. For GameStop, list out the key regression statistics (alpha, beta and R squared) in the regression. Do you notice any patterns? Can you interpret beta and R2 of the regression?

B. During the period of the regression, GameStop had incredible volatility but its beta does not seem to reflect it. Explain why.

 

GME US $S 1140.585 -0.505 GME US Equity Data Last Price At 14:07 d Vol 5,497,683 0 141.88N Relative Index SPX Index Data Last Price Wkly Linear Beta +/- 04/14/2019-04/13/202104/14/2018 - 04/13/2020 Lag 0 6M YTD 1Y 2Y 5Y Max Weekly Legend + Track Annotate Q Zoom Select Copy 400 Activate/deactivate the tracking crosshair. E G 350 300 250 200 150 100 50 0 -50 350 300-4000- 250- 200- 150- 100- 3500- 3000- 50-2500 04 2002 -16 Weekly: 04/19/19-04/09/21 GME US Equity 158.36 SPX Index 4128.7998 2003 2004 2005 -14 2006 -12 2007 3140.61/140.75T 1x1 H 145.3771D L 132.00K Val 765.2371 90 Actions 97) Edit. Non-Param Reg On Percent Winsorize 2 Std Dev Local -10 2008 -8 2009 -6 2010 Select 2011 -2 SPX Index-Percent 2012 2013 2014 2015 2016 2017 8 10 12 2019 Statistics Transformations Y= GAMESTOP CORP-CLASS A X-S&P 500 INDEX Linear Beta Raw BETA Adjusted BETA ALPHA (Intercept) R2 (Correlation 2) Historical Beta R (Correlation) Std Dev of Error Std Error of ALPHA Std Error of BETA t-Test Significance Last T-Value Last P-Value Number of Points Last Spread Last Ratio Range 1 -0.825 -0.216 8.694 0.003 -0.058 47.705 4.734 1.418 -0.582 0.562 -0.494 0.311 103 3970.44 0.038