References of "Scaillet, Olivier"
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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: 108 (6 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: 138 (4 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: 98 (5 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: 90 (4 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: 145 (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: 133 (9 UL)
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See detailMultivariate Wavelet-Based Shape Preserving Estimation for Dependent Observations
Cosma, Antonio UL; Scaillet, Olivier; Von Sachs, Rainer

in Bernoulli (2007), 13(2), 301-329

We present a new approach on shape preserving estimation of probability distribution and density functions using wavelet methodology for multivariate dependent data. Our estimators preserve shape ... [more ▼]

We present a new approach on shape preserving estimation of probability distribution and density functions using wavelet methodology for multivariate dependent data. Our estimators preserve shape constraints such as monotonicity, positivity and integration to one, and allow for low spatial regularity of the underlying functions. As important application, we discuss conditional quantile estimation for financial time series data. We show that our methodology can be easily implemented with B-splines, and performs well in a finite sample situation, through Monte Carlo simulations. [less ▲]

Detailed reference viewed: 115 (8 UL)