package com.imsl.test.example.stat;

import com.imsl.stat.EGARCH;
import com.imsl.stat.TimeSeries;
import java.util.logging.Level;
import java.util.logging.Logger;

/**
 * <p>
 * Fits an EGARCH(1, 1) with an ARMA(1,1) on the mean.
 * </p>
 * 
 * <p>
 * This example fits the exponential GARCH (EGARCH) with an ARMA(1,1) 
 * for the mean process. The data is a segment of S&amp;P 500 returns 
 * for a period in 1988. Forecasts 4 steps ahead from the end of the 
 * series are generated. 
 * </p>
 *
 * @see <a href="EGARCHEx3.java">Code</a>
 * @see <a href="doc-files/EGARCHEx3.out">Output</a>
 */
public class EGARCHEx3 {

    public static void main(String args[]) {

        double data1[] = {
            0.940543272, 2.664279727, 0.252045652, 1.221098464, 0.270575973,
            0.446882726, 0.073672969, -4.450030305, 0.007699415, -0.215808015,
            -0.498908466, -0.696433123, 0.113159704, 1.440322251, 0.887874183,
            0.5585227, -0.049267619, -0.452119841, -0.488606538, 0.087972619,
            0.549032948, -1.024238871, -0.589472147, -0.507487482, -0.365744931,
            0.42010331, -1.687159586, 0.212950629, 1.147614577, 0.748805609,
            -1.311175287, -1.574960025, 0.484204788, 0.178009897, -0.869311816,
            1.062785115, 0.098566846, 0.342257263, -0.47633197
        };

        TimeSeries ts;
        ts = new TimeSeries();
        ts.setSeriesValues(data1);
        int[] meanModel = {1, 0, 1};

        EGARCH egarch = new EGARCH(ts, 1, 1, meanModel);

        String[] names = {"mu", "meanAlpha1", "meanBeta1",
            "omega", "alpha", "beta", "gamma"};

        try {
            egarch.estimate();
            double[] parameters = egarch.getParameters();
            int nParameters = egarch.getNumberOfParameters();
            int T = egarch.getT();
            double[][][] forecasts = egarch.forecast(1, 4);

            System.out.println("Parameter estimates:");
            for (int j = 0; j < nParameters; j++) {
                System.out.printf("%s:  %3.4f \n", names[j], parameters[j]);
            }
            System.out.println("\n Forecasts 1-4 steps ahead from 1 snapshot origin:");
            System.out.println("t \t Epsilon \t Conditional variance ");
            for (int j = 0; j < 4; j++) {
                System.out.printf("%d \t   %3.4f         \t%3.4f\n", T + j + 1, 
                        forecasts[0][j][0], forecasts[0][j][1]);
            }
        } catch (Exception ex) {
            Logger.getLogger(EGARCHEx3.class.getName()).log(Level.SEVERE, null, ex);
        }
    }
}