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20192026
most citedA neural network-based framework for financial model calibration

66 citations · 77 across the 21 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

q-fin.MF2024

Volatility Parametrizations with Random Coefficients: Analytic Flexibility for Implied Volatility Surfaces

Nicola F. Zaugg, Leonardo Perotti, Lech A. Grzelak

It is a market practice to express market-implied volatilities in some parametric form. The most popular parametrizations are based on or inspired by an underlying stochastic model…

q-fin.CP2024

Modeling and Replication of the Prepayment Option of Mortgages including Behavioral Uncertainty

Leonardo Perotti, Lech A. Grzelak, Cornelis W. Oosterlee

Prepayment risk embedded in fixed-rate mortgages forms a significant fraction of a financial institution's exposure, and it receives particular attention because of the magnitude o…

q-fin.CP2024★ 1 cited

Basket Options with Volatility Skew: Calibrating a Local Volatility Model by Sample Rearrangement

Nicola F. Zaugg, Lech A. Grzelak

The pricing of derivatives tied to baskets of assets demands a sophisticated framework that aligns with the available market information to capture the intricate non-linear depende…

q-fin.CP2024

On the Hull-White model with volatility smile for Valuation Adjustments

T. van der Zwaard, L. A. Grzelak, C. W. Oosterlee

Affine Diffusion dynamics are frequently used for Valuation Adjustments (xVA) calculations due to their analytic tractability. However, these models cannot capture the market-impli…

q-fin.PR2024

Consistent asset modelling with random coefficients and switches between regimes

Felix L. Wolf, Griselda Deelstra, Lech A. Grzelak

We explore a stochastic model that enables capturing external influences in two specific ways. The model allows for the expression of uncertainty in the parametrisation of the stoc…