Example of garch model
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GARCH(1,1) Example Using S&P 500 S&P500 Log Squared Date Index Return Log Return GARCH(1,1) [A] [B = LN(A/Lag(A)) [C = B^2] 10/01/02 847.91 10/02/02 827.91 -2.39% 0.0570% 0.000075 10/03/02 818.95 -1.09% 0.0118% 0.000104 10/04/02 800.58 -2.27% 0.0515% 0.000104 10/07/02 785.28 -1.93% 0.0372% 0.000127 10/08/02 798.55 1.68% 0.0281% 0.000141 10/09/02 776.76 -2.77% 0.0765% 0.000148 10/10/02 803.92 3.44% 0.1181% 0.000182 10/11/02 835.32 3.83% 0.1468% 0.000239 10/14/02 841.44 0.73% 0.0053% 0.000307 10/15/02 881.27 4.62% 0.2139% 0.000288 10/16/02 860.02 -2.44% 0.0596% 0.000392 10/17/02 879.20 2.21% 0.0487% 0.000399 10/18/02 884.39 0.59% 0.0035% 0.000398 10/21/02 899.72 1.72% 0.0295% 0.000371 10/22/02 890.16 -1.07% 0.0114% 0.000361 10/23/02 896.14 0.67% 0.0045% 0.000342 10/24/02 882.50 -1.53% 0.0235% 0.000320 10/25/02 897.65 1.70% 0.0290% 0.000311 10/28/02 890.23 -0.83% 0.0069% 0.000305 10/29/02 882.15 -0.91% 0.0083% 0.000287 10/30/02 890.71 0.97% 0.0093% 0.000272 10/31/02 885.76 -0.56% 0.0031% 0.000258 11/01/02 900.96 1.70% 0.0290% 0.000241 11/04/02 908.35 0.82% 0.0067% 0.000241 11/05/02 915.39 0.77% 0.0060% 0.000228 11/06/02 923.76 0.91% 0.0083% 0.000215 11/07/02 902.65 -2.31% 0.0534% 0.000205 11/08/02 894.74 -0.88% 0.0077% 0.000222 11/11/02 876.19 -2.10% 0.0439% 0.000211 11/12/02 882.95 0.77% 0.0059% 0.000222 11/13/02 882.53 -0.05% 0.0000% 0.000209 11/14/02 904.27 2.43% 0.0592% 0.000195 11/15/02 909.83 0.61% 0.0038% 0.000216 11/18/02 900.36 -1.05% 0.0109% 0.000203 11/19/02 896.74 -0.40% 0.0016% 0.000195 11/20/02 914.15 1.92% 0.0370% 0.000182 11/21/02 933.76 2.12% 0.0450% 0.000191 11/22/02 930.55 -0.34% 0.0012% 0.000204 11/25/02 932.87 0.25% 0.0006% 0.000191 11/26/02 913.31 -2.12% 0.0449% 0.000178 [D = ω + α*Lag(D) +β*Lag(C)]
description
example of the generalised autoregressive heteroscedastic model in excel
Transcript of Example of garch model
GARCHGARCH(1,1) Example Using S&P 500 Index Data on 10/1/02 to 9/28/07
S&P500LogSquaredMaximumS.D. 95%DateIndexReturnLog ReturnGARCH(1,1)LikelihoodGARCH ParametersConfidence Bands[A][B = LN(A/Lag(A))[C = B^2][D = + *Lag(D)+*Lag(C)][E = (-0.5*LN(2*)-0.5*LN(D)-0.5*(C/D))[F = 2 x SQRT(D)][G = -2 x SQRT(D)]
10/01/02847.91 =0.0000011872NOTES:10/02/02827.91-2.39%0.0570%0.0000750.038098 =0.05831118961.73%-1.73%10/03/02818.95-1.09%0.0118%0.0001043.097280 =0.92431796282.04%-2.04%1. Use Solver to set the value of $H$1210/04/02800.58-2.27%0.0515%0.0001041.194163persistence=0.98262915242.04%-2.04%2 By changing $H$7:$H$910/07/02785.28-1.93%0.0372%0.0001272.1040252.26%-2.26%3. The constraint is that $H$10
