'Plot h-step ahead forecasts against actual realizations of time
series. Note that forecasts are lined up with their respective
realizations.
Parameters
steps :'

def plot_forecast(self, steps=1, figsize=(10, 10)):

    import matplotlib.pyplot as plt
    (fig, axes) = plt.subplots(figsize=figsize, nrows=self.neqs, sharex=True)
    forc = self.forecast(steps=steps)
    dates = forc.index
    y_overlay = self.y.reindex(dates)
    for (i, col) in enumerate(forc.columns):
        ax = axes[i]
        y_ts = y_overlay[col]
        forc_ts = forc[col]
        y_handle = ax.plot(dates, y_ts.values, 'k.', ms=2)
        forc_handle = ax.plot(dates, forc_ts.values, 'k-')
    lines = (y_handle[0], forc_handle[0])
    labels = ('Y', 'Forecast')
    fig.legend(lines, labels)
    fig.autofmt_xdate()
    fig.suptitle(('Dynamic    %d-step    forecast' % steps))
    plotting.adjust_subplots(bottom=0.15, left=0.1)
    plt.draw_if_interactive()
