HAR-RV Model(Andersen, Bollerslev, Diebold 2006)

HAR-RV (Heterogeneous AR model in the RV)a simple AR-type model in the RV that considers volatilities realized

over different interval sizesused Standard HAR with lags of 1, 5, and 22 days

Stocks Used

• 13 stocks:– AEP, BHI, BRKH, ETR, GOOG, GS, HNZ, KFT, MA,

MET, NYX, PM

• AIC– Akaike Information Criteria– Measure of the relative goodness of fit– Estimates relative support for a model

• SBIC– Schwartz/Bayesian Information Criteria– Measures efficiency of parameterized model in

terms of predicting data– Similar to the AIC

Parameters AIC SBIC

AEP 9.388018877 0.73457274 5.209431245 5.236745578

BHI 11.50978375 0.798306882 5.486833993 5.514148325

BRKH 19.24976406 0.462519354 5.937276534 5.964590866

ETR 8.412608506 0.769853458 5.157838165 5.185152498

GOOG 11.46459014 0.723224038 5.259170259 5.286484592

GS 17.68949645 0.720398439 6.613640609 6.640954942

HNZ 5.712941823 0.777521641 4.284006114 4.311320447

KFT 6.395478171 0.760584009 4.21710759 4.244421923

MA 14.12625235 0.727809945 5.587182841 5.614497173

MET 11.80923099 0.847437497 6.416902161 6.444216494

NYX 15.4038086 0.75926854 5.90681508 5.934129412

PM 12.22827329 0.652062411 5.724042276 5.751356608

• VCV– Non-heteroskedasticity robust covariance matrix

• VCCV Robust– Heteroskedasticity-robust covariance matrix

VCVAEP 3.18120755 -0.067160907

-0.067160907 0.001915862

BHI 5.855145244 -0.084363966

-0.084363966 0.001493994

BRKH 5.921627256 -0.117747581

-0.117747581 0.00329362

ETR 3.008103994 -0.061344988

-0.061344988 0.001692993

GOOG 4.280496659 -0.082522739

-0.082522739 0.001996214

GS 11.31765252 -0.126317175

-0.126317175 0.00200695

HNZ 1.403756633 -0.042120536

-0.042120536 0.001648804

KFT 1.54991693 -0.046766631

-0.046766631 0.001759004

MA 6.585749927 -0.103171084

-0.103171084 0.00197873

MET 9.505721933 -0.088388593

-0.088388593 0.00115916

NYX 8.766176313 -0.111762569

-0.111762569 0.001757937

PM 4.369732751 -0.084943502

-0.084943502 0.002416094

VCV RobustHNZ 1.403756633 -0.042120536

-0.042120536 0.001648804

KFT 1.54991693 -0.046766631

-0.046766631 0.001759004

MA 6.585749927 -0.103171084

-0.103171084 0.00197873

MET 9.505721933 -0.088388593

-0.088388593 0.00115916

NYX 8.766176313 -0.111762569

-0.111762569 0.001757937

PM 4.369732751 -0.084943502

-0.084943502 0.002416094

AEP 8.042936267 -0.193470125

-0.193470125 0.005205272

BHI 6.130023799 -0.081468096

-0.081468096 0.00126948

BRKH 33.9753212 -0.843463721

-0.843463721 0.022514742

ETR 7.91036198 -0.189287715

-0.189287715 0.004995754

GOOG 9.015934833 -0.190324752

-0.190324752 0.004486223

GS 27.7585666 -0.406571731

-0.406571731 0.006751666