Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The...

We develop an accurate valuation setup for freight options, featuring an exponential mean-reverting model for the freight rate with distinct reversion scales for its jump and diffusion components. We calibrate to Baltic option prices and analyze the freight rate dynamics. More specifically, we...

Crude oil derivatives form an important part of the global derivatives market. In this paper, we focus on Asian options which are favoured by risk managers being effective and cost-saving hedging instruments. The paper has both empirical and theoretical contributions: we conduct an empirical...

This paper proposes an integrated pricing framework for convertible bonds, which comprises firm value evolving as an exponential jump diffusion, correlated stochastic interest rates movements and an efficient numerical pricing scheme. By construction, the proposed stochastic model fits in the...

In this paper we present a new general method for simulating integrals of stochastic processes. We focus on the nontrivial case of time integrals conditional on the state variable levels at the endpoints of a time interval, based on a moment-based probability distribution construction. We...

In this paper, we recall actuarial and financial applications of sums of dependent random variables that follow a non-Gaussian mean-reverting process and contemplate distribution approximations. Our work complements previous related studies restricted to lognormal random variables; we revisit...