Search Results for author: Emanuele Nastasi

Found 5 papers, 0 papers with code

Pricing commodity index options

no code implementations2 Aug 2022 Alberto Manzano, Emanuele Nastasi, Andrea Pallavicini, Carlos Vázquez

We present a stochastic local volatility model for derivative contracts on commodity futures.

Reinforcement learning for options on target volatility funds

no code implementations3 Dec 2021 Roberto Daluiso, Emanuele Nastasi, Andrea Pallavicini, Stefano Polo

In this work we deal with the funding costs rising from hedging the risky securities underlying a target volatility strategy (TVS), a portfolio of risky assets and a risk-free one dynamically rebalanced in order to keep the realized volatility of the portfolio on a certain level.

reinforcement-learning Reinforcement Learning (RL)

Pricing commodity swing options

no code implementations24 Jan 2020 Roberto Daluiso, Emanuele Nastasi, Andrea Pallavicini, Giulio Sartorelli

In commodity and energy markets swing options allow the buyer to hedge against futures price fluctuations and to select its preferred delivery strategy within daily or periodic constraints, possibly fixed by observing quoted futures contracts.

reinforcement-learning Reinforcement Learning (RL)

A closed formula for illiquid corporate bonds and an application to the European market

no code implementations21 Jan 2019 Roberto Baviera, Aldo Nassigh, Emanuele Nastasi

We propose an option approach for pricing bond illiquidity that is reminiscent of the celebrated work of Longstaff (1995) on the non-marketability of some non-dividend-paying shares in IPOs.

Position

Smile Modelling in Commodity Markets

no code implementations29 Aug 2018 Emanuele Nastasi, Andrea Pallavicini, Giulio Sartorelli

We present a stochastic-local volatility model for derivative contracts on commodity futures able to describe forward-curve and smile dynamics with a fast calibration to liquid market quotes.

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