This is a convenience function for calibrating variance cumulation (the
at-the-money volatility of the continuous process) and equity linked default
intensity of the form $h(s + (1-s)(S0/S_t)^p)$, using a `data.frame`

of
option market data.

1 2 3 4 | ```
fit_to_option_market_df(S0 = ragtop::TSLAMarket$S0,
discount_factor_fcn = spot_to_df_fcn(ragtop::TSLAMarket$risk_free_rates),
options_df = ragtop::TSLAMarket$options, min_maturity = 1/12,
min_moneyness = 0.8, max_moneyness = 1.2, base_default_intensity = 0.05)
``` |

`S0` |
Current underlying price |

`discount_factor_fcn` |
A function for computing present values to
time |

`options_df` |
A data frame of American option details. It should
have columns |

`min_maturity` |
Minimum option maturity to allow in calibration |

`min_moneyness` |
Maximum option strike as a proportion of S0 to allow in calibration |

`max_moneyness` |
Maximum option strike as a proportion of S0 to allow in calibration |

`base_default_intensity` |
Overall default intensity (in natural units) |

`fit_to_option_market`

the underlying fit algorithm

Other Equity Dependent Default Intensity: `find_present_value`

,
`fit_variance_cumulation`

,
`form_present_value_grid`

,
`implied_jump_process_volatility`

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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