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Multiscale stochastic volatility models have been developed as an efficient way to capture the principle effects on derivative pricing and portfolio optimization ofrandomly varying volatility. The rec...
Trading large volumes of a nancial asset in order driven markets requires the use of algorithmic execution dividing the volume in many transactions in order to minimize costs due to market impact. A ...
In this paper we calibrate chaotic models for interest rates to market data using a polynomial{exponential parametrization for the chaos coecients. We identify a subclass of one{ variable models th...
In recent years research on credit risk modelling has mainly focused on default probabilities. Recovery rates are usually modelled independently, quite often they are even assumed constant.
In this paper we develop structural first passage models (AT1P and SBTV)with time-varying volatility and characterized by high tractability, moving from the original work of Brigo and Tarenghi (2004, ...
Regime switching volatility models provide a tractable method of modelling stochastic volatility. Currently the most popular method of regime switching calibration is the Hamilton filter. We propose u...
In this work we develop a tractable structural model with analytical default probabilities depending on a random default barrier and possibly random volatil-ity ideally associated with a scenario base...
In this paper we develop a tractable structural model with analytical default probabilities depending on some dynamics parameters, and we show how to cal-ibrate the model using a chosen number of Cred...

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