FIN-321
Homework 5 – Fall 2019
1. In class, we learned that we can assess the impact of a macro indicator by running a regression of the appropriate measure of stock market returns on the appropriate measure of the surprise contained in the announcement of the macro indicator.
a. Using the posted spreadsheet, how exactly would you measure a surprise in nonfarm payrolls? Please state your answer by copying and pasting the corresponding Excel formula with cell references below.
b. Using the posted spreadsheet, how exactly would you measure the stock return associated with the nonfarm payroll announcement? Please state your answer by copying and pasting the corresponding Excel formula with cell references below.
2. Using your answer to question 1, estimate a regression of announcement returns on nonfarm payroll surprises. Copy and paste the regression statistics below. Based on your results, are nonfarm payroll surprises a statistically significant determinant of stock market returns? How does the economic magnitude of their effect compare to that of ISM surprises (put differently, which macro indicator has been a more powerful driver of stock returns during the past 3 years
ISM_regression_chart
ISM surprise Line Fit Plot
SPY open-to-close return on ISM announcement date 0.0178571428571428 0.0330097087378641 -0.00754716981132073 -0.05 0.0258964143426294 0.00386847195357825 0.0191570881226054 0.012962962962963 0.0181818181818182 0.0303571428571429 0.00175131348511386 -0.0300884955752213 0.00365630712979882 0.0490018148820326 -0.0017730496453901 0.0407079646017699 0.0482758620689655 -0.0134453781512605 -0.00171526586620916 0.0257731958762887 0.0051020408163266 0.0357751277683134 -0.0116666666666667 -0.0205128205128206 0.0103270223752152 0.0343642611683849 -0.0218855218855218 0.064236111111111 -0.00664451827242534 -0.0220338983050847 0.0313043478260869 -0.0640138408304497 0.044280442804428 -0.0286738351254479 0.0146788990825688 -0.04 0.00549923488905901 0.00267481849445916 -0.00115106588701142 9.20090168836651E-5 -0.000185339634880877 -0.00901704785610302 -0.00525528926743079 0.000888730892285805 -0.00278197629843813 0.00583078149251226 -0.00199321458863444 0.0 0.00574451378270035 -0.00275856389986817 -0.000565747999676791 -0.000322684737011913 0.00330033003300323 -0.00213145248798641 -0.00113310167699054 0.00561421772754333 0.0018144946098837 -0.0136693563243803 -0.0193486954865739 0.00420661689468305 0.00436841525641496 0.00871952803235509 -0.00248614860065344 -0.000103505382279767 -0.00130087980555271 0.00703240058910159 -0.00349650349650332 -0.0161946581799137 -0.000333148250971638 -7.13165026386964E-5 0.00396909027046011 -0.00987377850162874 Predicted SPY open-to-close return on ISM announcement date 0.0178571428571428 0.0330097087378641 -0.00754716981132073 -0.05 0.0258964143426294 0.00386847195357825 0.0191570881226054 0.012962962962963 0.0181818181818182 0.0303571428571429 0.00175131348511386 -0.0300884955752213 0.003656307129 ...
Graduate Outcomes Presentation Slides - English (v3).pptx
FIN-321Homework 5 – Fall 20191. In class, we learned that we.docx
1. FIN-321
Homework 5 – Fall 2019
1. In class, we learned that we can assess the impact of a macro
indicator by running a regression of the appropriate measure of
stock market returns on the appropriate measure of the surprise
contained in the announcement of the macro indicator.
a. Using the posted spreadsheet, how exactly would you
measure a surprise in nonfarm payrolls? Please state your
answer by copying and pasting the corresponding Excel formula
with cell references below.
b. Using the posted spreadsheet, how exactly would you
measure the stock return associated with the nonfarm payroll
announcement? Please state your answer by copying and pasting
the corresponding Excel formula with cell references below.
2. Using your answer to question 1, estimate a regression of
announcement returns on nonfarm payroll surprises. Copy and
paste the regression statistics below. Based on your results, are
nonfarm payroll surprises a statistically significant determinant
of stock market returns? How does the economic magnitude of
their effect compare to that of ISM surprises (put differently,
which macro indicator has been a more powerful driver of stock
returns during the past 3 years
4. 0.000549731439697245 -0.00534584373209582
0.00135232268129959 -0.00316001054388672 -
0.000478577891540578 -0.00386055109514136
ISM surprise
SPY open-to-close return on ISM announcement date
ISM_regressionSUMMARY OUTPUTStep 1:Locate the slope
coefficient which tells us whether the relation is positive or
negativeHere: positive, as expectedRegression
StatisticsMultiple R0.293Step 2:Is the relation statistically
significant? At conventional levelsR Square0.086(i)Is |t-
stat|>2?YesAdjusted R Square0.059or(ii)Is p-value<5%?The p-
value is the probability of observing the estimated slope
coefficient if there was no relation at all - YesStandard
Error0.006or(iii)Does the (lower 95%, upper 95%) confidence
interval contain 0? Significant if not.Observations36Stop if not
statistically significant.ANOVAStep 3:Is the relation
economically significant?dfSSMSFSignificance FTo answer, we
compute the standard deviation of X-variable (ISM
surprises)Regression10.0000.0003.1940.083Std3.0%Residual34
0.0010.000What effect does a 1-standard-deviation ISM surprise
have on SPY returns?Total350.001Std*Coeff0.18%We can
compare this effect with the average absolute daily SPY
returnCoefficientsStandard Errort StatP-valueLower 95%Upper
95%Average |Daily SPY return|0.43%Intercept-0.0010.001-
1.3320.192-0.0040.001This allows to estimate how big the
effect of an ISM surprise is relative to the average SPY
returnISM surprise0.0620.0351.7870.083-0.0080.13243%This is
substantial - Alan Greenspan is still correct about
ISMRESIDUAL OUTPUTObservationPredicted SPY open-to-
close return on ISM announcement dateResiduals1-
0.00028199870.005781233620.00065521060.00201960793-
0.00185329410.00070222824-
0.00447906630.004571075350.0002152425-0.00040058226-
0.0011472193-0.00786982867-0.0002015951-0.00505369428-
0.00058471120.0014734429-0.000261917-
0.0025200593100.00049114540.005339636111-0.0012781688-