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High Volatile Markets HAR-RV and Macroeconomic News. Motivation. Examine how HAR-RV model differs in the financial sector data from 1997 compared to post July 2007 and post September 15 2008 Examine how Macroeconomic News: Feds Fund Rate and the Nonfarm Payroll Announcements Affect RV. - PowerPoint PPT Presentation
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High Volatile MarketsHAR-RV
and Macroeconomic News
Motivation
• Examine how HAR-RV model differs in the financial sector data from 1997 compared to post July 2007 and post September 15 2008
• Examine how Macroeconomic News: Feds Fund Rate and the Nonfarm Payroll Announcements Affect RV
Financial Sector Data
• JPM (JP Morgan)• BK (new) (Bank of New York Mellon)• BAC (Bank of America)• AXP (American Express)• ALL (Allstate)Others Not Included Because of Data Differences
Financial Sector Data
• Equally Weighted • Modify data so that stock splits do not affect
the RV• Portfolio: 4/10/1997 through 1/7/2009
(equally weighted)
HAR-RV
Data Points
From 1997 2900
Post July 2007 356
Post Sept 15 2008 76
HAR-RV
HAR-RV for Full Data SetUsing Newey West Standard Errors
Regression with Newey-West standard errors Number of obs = 2900.000
maximum lag: 44 F( 3, 2896) = 1380.470
Prob > F = 0.000
Newey-West
RV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) 0.413 .0572137 7.21 0.000 .3003651 0.525
RV(t-5,t) 0.337 .0502072 6.71 0.000 .2382236 0.435
RV(t-22,t) 0.167 .0606095 2.75 0.006 .0481195 0.286
_cons 1.021 .2419986 4.22 0.000 .5465046 1.496
HAR-RV: Financial Crisis
. newey RV(t+1) RV(t) RV(t-5,t) RV(t-22,t), lag(44)
Regression with Newey-West standard errors Number of obs = 356.000
maximum lag: 44 F( 3, 352) = 325.170
Prob > F = 0.000
Newey-West
RV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) .3912903 .0707588 5.53 0.000 .2521271 0.530
RV(t-5,t) .348953 .0630994 5.53 0.000 .2248538 0.473
RV(t-22,t) .1119859 .0714758 1.57 0.118 -.0285874 0.253
_cons 4.713085 1.46527 3.22 0.001 1.8313 7.595
HAR-RV: Post Lehman
. newey RV(t+1) RV(t) RV(t-5,t) RV(t-22,t), lag(44)
Regression with Newey-West standard errors Number of obs = 76.000maximum lag: 44 F( 3, 72) = 8.310
Prob > F = 0.000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) .3138935 .0929552 3.38 0.001 .1285907 0.499RV(t-5,t) .3063585 .1567351 1.95 0.055 -.0060872 0.619RV(t-22,t) -.3376104 .1327388 -2.54 0.013 -.6022204 -0.073_cons 51.48582 17.5348 2.94 0.004 16.53083 86.441
HAR-RV with Fed Factor: Full Data
Regression with Newey-West standard errors Number of obs = 2900.000
maximum lag: 44 F( 4, 2895) = 1034.370
Prob > F = 0.000
Newey-West
RV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) 0.415 .0582077 7.12 0.000 .3004094 0.529
RV(t-5,t) 0.337 .0497956 6.77 0.000 .2392839 0.435
RV(t-22,t) 0.163 .0596337 2.73 0.006 .0461464 0.280
FedIndicator(t+1) 4.631 1.766731 2.62 0.009 1.167138 8.095
_cons 0.974 .2419073 4.03 0.000 .4995392 1.448
Regression with Newey-West standard errors Number of obs = 2900maximum lag: 44 F( 5, 2894) = 825.63
Prob > F =0.0000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf.
RV(t) 0.415 .0588426 7.05 0.000 .2996637RV(t-5,t) 0.337 .0495658 6.80 0.000 .2397886RV(t-22,t) 0.159 .0585163 2.72 0.007 .0446186FedIndicator(t+1) 7.910 3.073039 2.57 0.010 1.884336FedPositive(t+1) -6.953 3.175657 -2.19 0.029 -13.18013_cons 1.030 .2396987 4.30 0.000 .5601226
HAR-RV With Decision and Sign of Decision
Regression with Newey-West standard errors Number of obs =maximum lag: 44 F( 5, 2894) = 825.63
Prob > F = 0.0000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf.
RV(t) 0.415 .0588426 7.05 0.000 .2996637RV(t-5,t) 0.337 .0495658 6.80 0.000 .2397886RV(t-22,t) 0.159 .0585163 2.72 0.007 .0446186FedIndicator(t+1) 0.957 .6770606 1.41 0.158 -.3710226FedNegative(t+1) 6.953 3.175657 2.19 0.029 .7265776_cons 1.030 .2396987 4.30 0.000 .5601226
HAR-RV with Fed Direction Changes: Full Data Set
. newey RV(t+1) RV(t) RV(t-5,t) RV(t-22,t) FedNegative(t+1) FedPositive(t+1),lag(44)
Regression with Newey-West standard errors Number of obs = 2900.000maximum lag: 44 F( 5, 2894) = 825.630
Prob > F = 0.000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) .415 .0588426 7.05 0.000 .2996637 0.530RV(t-5,t) .3370 .0495658 6.80 0.000 .2397886 0.434RV(t-22,t) .1594 .0585163 2.72 0.007 .0446186 0.274FedNegative(t+1) 7.910 3.073039 2.57 0.010 1.884336 13.935FedPostivie(t+1) .9565 .6770606 1.41 0.158 -.3710226 2.284_cons 1.030 .2396987 4.30 0.000 .5601226 1.500
HAR-RV with Rate Change
newey RV(t+1) RV(t) RV(t-5,t) RV(t-22,t) FedChange(t+1), lag(44)
Regression with Newey-West standard errors Number of obs = 2900.000maximum lag: 44 F( 4, 2895) = 1018.980
Prob > F = 0.000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) .4128365 .0584136 7.07 0.000 .2983001 0.527
RV(t-5,t) .3382032 .0496406 6.81 0.000 .2408687 0.436
RV(t-22,t) .1590522 .0592867 2.68 0.007 .0428037 0.275
FedChange(t+1) -13.13035 5.702837 -2.30 0.021 -24.31239 -1.948
_cons 1.104633 .2428741 4.55 0.000 .628409 1.581
Unemployment Rate
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
1997 230 301 312 291 256 253 283 -18 508 339 303 299 1998 270 189 144 277 401 212 119 352 218 193 284 342 1999 121 410 106 376 213 266 291 192 202 408 294 294 2000 249 121 472 286 225 -46 163 3 122 -11 231 138 2001 -16 61 -30 -281 -44 -128 -125 -160 -244 -325 -292 -178 2002 -132 -147 -24 -85 -7 45 -97 -16 -55 126 8 -156 2003 83 -158 -212 -49 -6 -2 25 -42 103 203 18 124 2004 150 43 338 250 310 81 47 121 160 351 64 132 2005 182 221 121 312 212 259 322 190 87 98 380 160 2006 294 274 282 151 24 70 186 149 147 82 261 219 2007 180 36 184 35 156 54 -65 -28 100 165 215 120 2008 -72 -144 -122 -160 -137 -161 -128 -175 -321 -380 -597 -681
2009-741 -651(p) -663(p)
Insignificance of Employment Report on RV
newey RV(t+1) EmploymentChange(t+1), lag(44)
Regression with Newey-West standard errors Number of obs = 356.000maximum lag: 44 F( 1, 354) = 2.990
Prob > F = 0.084
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
EmployCh(t+1) -.0786806 .0454715 -1.73 0.084 -.1681089 0.011_cons 38.42574 6.133826 6.26 0.000 26.36241 50.489
newey RV(t+1) EmployIncr EmployDec, lag(44)
Regression with Newey-West standard errors Number of obs = 356.000maximum lag: 44 F( 2, 353) = 2.010
Prob > F = 0.135
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
EmpIncr(t+1) -12.3024 6.254994 -1.97 0.050 -24.60415 -0.001EmpDecr(t+1) 2.527 4.108933 0.62 0.539 -5.553972 10.608_cons 38.6737 6.2204 6.22 0.000 26.43991 50.908
newey RV(t+1) EmpChange(t), lag(44)
Regression with Newey-West standard errors Number of obs = 355.000maximum lag: 44 F( 1, 353) = 2.770
Prob > F = 0.097
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
EmpChange(t) -.0833593 .0501089 -1.66 0.097 -.1819089 0.015_cons 38.45999 6.147739 6.26 0.000 26.36919 50.551
Regressing Employment Error at t on RV(t+1)
newey RV(t+1) EmpChange(t+1), lag(44)
Regression with Newey-West standard errors Number of obs = 356.000maximum lag: 44 F( 1, 354) = 2.990
Prob > F = 0.084
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
EmpChange(t+1) -.0786806 .0454715 -1.73 0.084 -.1681089 0.011_cons 38.42574 6.133826 6.26 0.000 26.36241 50.489
Regressing Employment Error at t on RV(t)
HAR-RV with Indicator for Prediction Error in Unemployment
Regression with Newey-West standard errors Number of obs = 356.000
maximum lag: 44 F( 5, 350) = 215.360
Prob > F = 0.000
Newey-West
RV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) 0.392 .0708666 5.53 0.000 .2524011 0.531
RV(t-5,t) 0.352 .0631066 5.57 0.000 .2275375 0.476
RV(t-22,t) 0.109 .0704045 1.54 0.124 -.029822 0.247
EmpInc(t+1) 0.939 2.075873 0.45 0.651 -3.143268 5.022
EmpDecr(t+1) 3.478 3.13709 1.11 0.268 -2.6918 9.648
_cons 4.610 1.483457 3.11 0.002 1.692407 7.528
HAR-RV with Prediction Error of Unemployment
newey RV(t+1) RV(t) RV(t-5,t) RV(t-22,t) RV(t+1)2, lag(44)
Regression with Newey-West standard errors Number of obs = 356.000maximum lag: 44 F( 4, 351) = 250.150
Prob > F = 0.000
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) .3912955 .0708362 5.52 0.000 .2519787 0.531RV(t-5,t) .3490004 .0631436 5.53 0.000 .2248131 0.473RV(t-22,t) .1118007 .0711585 1.57 0.117 -.02815 0.252EmpChange(t+1) -.0022569 .0340129 -0.07 0.947 -.0691516 0.065_cons 4.71545 1.47223 3.20 0.001 1.819949 7.611
HAR-RV for Multiple PeriodsRegression with Newey-West standard errors Number of obs = 2900maximum lag: 44 F( 12, 2887) = 664.24
Prob > F = 0
Newey-WestRV(t+1) Coef. Std. Err. t P>t [95% Conf. Interval]
RV(t) 0.4451 .06044 7.36 0.000 .326566 0.5635857RV(t-5,t) 0.2891 .0584834 4.94 0.000 .1744394 0.4037862RV(t-22,t) 0.15508 .0385057 4.03 0.000 .0795817 0.2305846FedChangeValue(t+1) -1.8619 2.462416 -0.76 0.450 -6.690192 2.96635FC*RV(t) 0.02479 .0950022 0.26 0.794 -.1614939 0.211064FC*RV(t-5,t) 0.08579 .1382652 0.62 0.535 -.1853161 0.3569008FC*RV(t-22,t) -0.07591 .0793942 -0.96 0.339 -.2315851 0.0797648FC*FedChange(t+1) -28.5908 15.05288 -1.90 0.058 -58.10628 0.9246645PL*RV(t) -0.09931 .118297 -0.84 0.401 -.3312656 0.1326445PL*RV(t-5,t) -0.03250 .1514165 -0.21 0.830 -.3293934 0.2643973PL*RV(t-22,t) 0.10440 .1385846 0.75 0.451 -.1673375 0.3761319PL*FedChange(t+1) 7.2037 23.44532 0.31 0.759 -38.76756 53.17496_cons 1.3383 .3183748 4.20 0.000 .7140422 1.962572
Final Research
• Continue to Examine Other Macroeconomic Indicators Effect on HAR-RV Model
