The log-normal approximation in financial and other computations
By Daniel Dufresne. Advances in Applied Probability, 2004
111 citations recorded by the source corpus.
Subfields: Finance, Mathematical Physics
View Paper: https://www.semanticscholar.org/paper/fed334de242c1d136b2fa43223446433b584853f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Masaaki Kijima
- Tony Siu Tung Wong
- Antoine Jacquier
- Claude Martini
- Aitor Muguruza
- Peter Tankov
- Archil Gulisashvili
- Daniel Dufresne
In Mathematical Physics
- Masaaki Kijima
- Tony Siu Tung Wong
- Antoine Jacquier
- Claude Martini
- Aitor Muguruza
- Archil Gulisashvili
- Peter Tankov
- Daniel Dufresne
Citations in the corpus
- Fitting combinations of exponentials to probability distributions (2007, background): “The distribution of a stochastic annuity with an exponential lifetime is known in closed form; the mathematical result was first derived by Yor (1992), but see Dufresne (2004a) for the financial interpretation.”
- Tail behavior of sums and differences of log-normal random variables (2013, background): “The history and the applications of log-normal distributions are reviewed in [1,15,16,22,26].”
- On VIX futures in the rough Bergomi model (2017, methodology): “In a different context (geometric Brownian motion and Asian options), Dufresne (2004) proved that, under certain conditions, an integral of log-normal variables asymptotically converges to a log-normal.”
- Pricing of Ratchet Equity-Indexed Annuities under Stochastic Interest Rates ? (2007, methodology): “Consequently, they assume that the short rate follows the Vasicek model and obtain prices for various EIAs using the riskminimizing scheme of Föllmer and Sondermann (1986).”