def get(eqprice, callprice, strike, shares=<NUM_LIT:1>, buycomm=<NUM_LIT:0.>, excomm=<NUM_LIT:0.>, dividend=<NUM_LIT:0.>):
_index = ['<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', <EOL>'<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>',<EOL>'<STR_LIT>', '<STR_LIT>']<EOL>_metrics = pd.DataFrame(index=_index, columns=['<STR_LIT>'])<EOL>_shares = float(shares)<EOL>_dividends = _shares * dividend<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _eqcost = _shares * eqprice<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _optprem = _shares * callprice<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = float(buycomm)<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _invested = _eqcost - _optprem + buycomm<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _dividends<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _eqsale = strike * _shares<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = float(excomm)<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _profitex = _eqsale + _dividends - _invested - excomm<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = round(_profitex / _invested, _constants.NDIGITS_SIG)<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _profitunch = _eqcost + _dividends - _invested<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = round(_profitunch / _invested, _constants.NDIGITS_SIG)<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _breakeven = round((_invested - _dividends) / _shares, <EOL>_constants.NDIGITS_SIG)<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = _protpts = eqprice - _breakeven<EOL>_metrics.loc['<STR_LIT>', '<STR_LIT>'] = round(_protpts / eqprice, _constants.NDIGITS_SIG)<EOL>return _metrics<EOL>
Metrics for covered calls.

Parameters
----------
eqprice : float
    Price at which stock is purchased.
callprice : float
    Price for which call is sold.
strike : float
    Strike price of call sold.
shares : int, optional
    Number of shares of stock. Defaults to 1.
buycomm : float, optional
    Commission paid on total initial purchase.
excomm : float optional
    Commission to be paid if option is exercised.
dividend : float, optional
    Total dividends per share expected between purchase and expiration.

Returns
----------
metrics : :class:`pandas.DataFrame`
    Investment metrics

Notes
-----
Cf. Lawrence McMillan, Options as a Strategic Investment, 5th ed., p. 43