We consider the problem of pricing options on a leveraged ETF (LETF) and the underlying ETF in a consistent manner. We show that if the underlying ETF has Heston dynamics then the LETF also has Heston dynamics so that options on both the ETF and the LETF can be priced analytically using standard...

We present a discrete time stochastic volatility model in which the conditional distribution of the logreturns is a Variance-Gamma, that is a normal variance-mean mixture with Gamma mixing density. We assume that the Gamma mixing density is time varying and follows an affine Garch model, trying...

We present an embarrassingly simple method for supervised learning of SABR model's European option price function based on lookup table or rote machine learning. Performance in time domain is comparable to generally used analytic approximations utilized in financial industry. However, unlike the...

In this paper, a general binomial lattice framework, which is both computationally simple and numerically accurate, is developed for pricing real estate derivatives with stochastic interest rate. To obtain a computationally simple binomial tree with constant volatility, the transformation method...

In this paper we consider the impact of bilateral initial margin on derivatives pricing. We first introduce the background of bilateral initial margin. Then, we focus on how initial margin effects counterparty credit exposures, capital requirements and funding costs. Nowadays, besides...

We investigate the importance of ambiguity, or Knightian uncertainty, in executives' decisions about when to exercise stock options. We develop an empirical estimate of ambiguity and include it in regression models alongside the more traditional measure of risk, equity volatility. We show that...

The aim of this work is to offer for the first time an application in finance of a new tool that appears to have a great potential in terms of derivative pricing. Non Uniform Discrete Fourier Transforms are innovative, precious tools in the fields of Signals Theory and Images Reconstruction...

We develop a stochastic calculus that makes it easy to capture a variety of predictable transformations of semimartingales such as changes of variables, stochastic integrals, and their compositions. The framework offers a unified treatment of real-valued and complex-valued semimartingales. The...

The aim of this paper is to provide a new straightforward \textit{measure-free} methodology based on a convex hulls to determine the no-arbitrage pricing bounds of an option (European or American). The pedagogical interest of our methodology is also briefly discussed. The central result, which...

Breakthroughs and backlashes have marked progress in the development and diffusion of Artificial Intelligence (AI). These shocks make the investment in developing an Artificial General Intelligence (AGI) subject to considerable uncertainty. This paper applies a real options model, extended to...