A comparison of biased simulation schemes for stochastic volatility models
By R. Lord, R. Koekkoek, Dick Van Dijk. 2010
409 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/614746de528b110918a8e0ec1ba063d07b51b85c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Damiano Brigo
- Andrea Pallavicini
- H. V. D. Weide
- Nicola Bruti-Liberati
- Cornelis W. Oosterlee
- Lukasz Szpruch
- Xuerong Mao
- Bin Chen
In Finance
- Andrea Pallavicini
- Xuerong Mao
- Damiano Brigo
- Lukasz Szpruch
- Vasileios Papatheodorou
- H. V. D. Weide
- Nicola Bruti-Liberati
- Cornelis W. Oosterlee
Citations in the corpus
- The Heston Stochastic-Local Volatility Model: Efficient Monte Carlo Simulation (2014, neutral): “Although several fixes like “absorption at zero” for handling negative variance realizations are known in the literature (see [16] for an overview), these improved methods are typically not free of bias.”
- A LOW-BIAS SIMULATION SCHEME FOR THE SABR STOCHASTIC VOLATILITY MODEL (2012, methodology): “Despite the fact that the CEV model has been introduced more than 30 years ago and that various researchers have shown evidence of significant bias in the basic Euler scheme for the CEV model, only a few references devising efficient unbiased Monte Carlo schemes were found in the literature.”
- Numerical Solution of Stochastic Differential Equations with Jumps in Finance (2010, methodology): “Cyganowski, Grune & Kloeden (2002) described MAPLE implementations of the Euler scheme and of the strong schemes presented in Maghsoodi (1996). Gardon (2004) proved a convergence theorem for regular strong Taylor schemes of any given order "( E {0.”
- ARBITRAGE-FREE VALUATION OF BILATERAL COUNTERPARTY RISK FOR INTEREST-RATE PRODUCTS: IMPACT OF VOLATILITIES AND CORRELATIONS (2011, result): “We find similar convergence results both with the full truncation scheme introduced by [23] and with the implied scheme by [8].”
- Strong convergence rates for backward Euler–Maruyama method for non-linear dissipative-type stochastic differential equations with super-linear diffusion coefficients (2013, background): “4) by Xtkþ1 1⁄4 Xtk þ m2 aXrtkþ1 Dt þ bXrtk1{Xtk$0}Dwtk : This ‘fix’ has been found to be the most efficient among several alternatives [23].”