References of "Galluccio, Stefano"
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See detailEarly exercise decision in american options with dividends, stochastic volatility, and jumps
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

in Journal of Financial and Quantitative Analysis (2020), 55(1), 331-356

Using a fast numerical technique, we investigate a large database of investors' suboptimal nonexercise of short-maturity American call options on dividend-paying stocks listed on the Dow Jones. The ... [more ▼]

Using a fast numerical technique, we investigate a large database of investors' suboptimal nonexercise of short-maturity American call options on dividend-paying stocks listed on the Dow Jones. The correct modeling of the discrete dividend is essential for a correct calculation of the early exercise boundary, as confirmed by theoretical insights. Pricing with stochastic volatility and jumps instead of the Black--Scholes--Merton benchmark cuts the amount lost by investors through suboptimal exercise by one-quarter. The remaining three-quarters are largely unexplained by transaction fees and may be interpreted as an opportunity cost for the investors to monitor optimal exercise. [less ▲]

Detailed reference viewed: 64 (2 UL)
See detailValuing American options using fast recursive projections
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

Scientific Conference (2016, December)

Detailed reference viewed: 121 (2 UL)
See detailValuing American options using fast recursive projections
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

Scientific Conference (2016, July)

Detailed reference viewed: 80 (3 UL)
See detailValuing American options using fast recursive projections
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

Scientific Conference (2016, May)

Detailed reference viewed: 68 (2 UL)
Full Text
See detailValuing American options using fast recursive projections
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

E-print/Working paper (2015)

We introduce a fast and widely applicable numerical pricing method that uses recursive projections. We characterize its convergence speed. We find that the early exercise boundary of an American call ... [more ▼]

We introduce a fast and widely applicable numerical pricing method that uses recursive projections. We characterize its convergence speed. We find that the early exercise boundary of an American call option on a discrete dividend paying stock is higher under the Merton and Heston models than under the Black-Scholes model, as opposed to the continuous dividend case. A large database of call options on stocks with quarterly dividends shows that adding stochastic volatility and jumps to the Black-Scholes benchmark reduces the amount foregone by call holders failing to optimally exercise by 25%. Transaction fees cannot fully explain the suboptimal behavior. [less ▲]

Detailed reference viewed: 131 (9 UL)
See detailValuing American options using fast recursive projections
Cosma, Antonio UL; Galluccio, Stefano; Pederzoli, Paola et al

Scientific Conference (2014, April)

Detailed reference viewed: 116 (9 UL)