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Primer on Arbitrage and Asset Pricing
In this paper, the authors go back to basics with arbitrage and asset pricing.
Thu 19 Oct 2023
Barrier Options and Lumpy Dividends
In this article, the authors study the pricing of barrier options on stocks with lumpy dividends.
Fri 26 May 2023
Approximation of Continuous Monitoring with Discrete Monitoring Applied to Down—And—Out Options
In this paper, Stefan Ebenfeld and Damaris Hilzinger consider down—and—out options in the Black—Scholes framework.
Thu 23 Mar 2023
Pricing Credit Derivatives with Uncertain Default Probabilities
In this article, the author presents a model for pricing credit spread options in an environment where the rating transition probabilities are uncertain parameters.
Tue 11 Oct 2022
Swaptions: 1 Price, 10 Deltas, and … 61/2 Gammas*
This article compares simple risk measures (first and second order sensitivity to the underlying yield curve) for simple instruments (swaptions).
Thu 1 Sep 2022
Can anyone solve the smile problem?
In this paper, the authors explore whether the smile problem can be solved and provide a general reflection of the problem.
Tue 31 May 2022
Knock-in/out Margrabe
In this paper, Espen G. Haug and Jorgen Haug push the Black-Scholes-Merton (BSM) formula to the limit by using it to value exchange-one-asset-for-another options with knock-in or knock-out provisions that depend on the ratio of the two asset prices.
Tue 31 May 2022
Calibration problems – An inverse problems view
In this article, Heniz W. Engl discusses the model parameters from market prices of liquid instruments.
Thu 21 Apr 2022
Numerical Methods for the Markov Functional Model
Some numerical methods for efficient implementation of the 1- and 2-factor Markov Functional models of interest rate derivatives are proposed.
Thu 4 Nov 2021
Order Statistics for Value at Risk Estimation and Option Pricing
We apply order statistics to the setting of VaR estimation. Here techniques like historical and Monte Carlo simulation rely on using the k-th heaviest loss to estimate the quantile of the profit and loss distribution of a portfolio of assets. We show that when the k-th heaviest loss is used the expected quantile and its error will be independent of the portfolio composition and the return functions of the assets in the portfolio.
Tue 12 Oct 2021
