Abstract The extraction of information from IoT data plays a fundamental role in many fields. In this paper we focus our attention on financial data and we use them to describe derivatives in the Black-Scholes model. This model lets us obtain an expression of the price of a derivative in a complete market with no possibility of arbitrage portfolios. Traders can sell amounts of assets even if they do not own them (i.e., short sellings are allowed) and must pay no frictional costs.
A Stochastic Method for Financial IoT Data / Cuomo, Salvatore; DE MICHELE, Pasquale. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - 98:(2016), pp. 491-496. [http://dx.doi.org/10.1016/j.procs.2016.09.082]
A Stochastic Method for Financial IoT Data
CUOMO, SALVATORE;DE MICHELE, PASQUALE
2016
Abstract
Abstract The extraction of information from IoT data plays a fundamental role in many fields. In this paper we focus our attention on financial data and we use them to describe derivatives in the Black-Scholes model. This model lets us obtain an expression of the price of a derivative in a complete market with no possibility of arbitrage portfolios. Traders can sell amounts of assets even if they do not own them (i.e., short sellings are allowed) and must pay no frictional costs.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
