International Journal of Theoretical and Applied Finance

For the Barndorf-Nielsen and Shephard model, we present approximate expressions of call option prices based on the decomposition formula developed by [T. Arai (2021) Alos type decomposition formula for Barndor-Nielsen and Shephard model, Journal of Stochastic Analysis 2 (2), 3]. Besides, some numerical experiments are also implemented to make sure how effective our approximations are.

In this paper, we measure the market and the longevity risks borne by an insurer by computing their solvency capital for a given annuity and within an investment strategy. For this purpose, we propose the investment strategy in such a way as to mitigate the solvency capital of the insurer and improve the internal rate of return of a shareholder investing on a given annuity. Numerically, we study the sensitivity of both the solvency capital and the internal rate of return with respect to some significant parameters.

To investigate the effect of short-selling constraints on investor behavior, we formulate an optimal stopping model in which the decision to cover a short position is affected by two short sale-specific frictions — margin risk and recall risk. Margin risk is introduced by assuming that a short seller is forced to close out their position involuntarily if they cannot fund margin calls (since short sales are collateralized transactions). Recall risk is introduced by permitting the lender to recall borrowed stock at any time, once again triggering an involuntary close-out. Examining the effect of these frictions on the optimal close-out strategy and associated value function, we finding that the optimal behavior can be qualitatively different in their presence. Moreover, these frictions lead to a substantial loss in value, relative to the first-best situation without them (a reduction of approximately 17% for our conservative base-case parameters). This significant effect has important implications for many familiar no-arbitrage identities, which are predicated on the assumption of unfettered short selling.

We propose Monte Carlo calibration algorithms for three models: local volatility with stochastic interest rates, stochastic local volatility with deterministic interest rates and finally stochastic local volatility with stochastic interest rates. For each model, we include detailed derivations of the corresponding SDE systems and list the required input data and steps for calibration. We give conditions under which a local volatility can exist given European option prices, stochastic interest rate model parameters, and correlations. The models are posed in a foreign exchange setting. The drift term for the exchange rate is given as a difference of two stochastic short rates, domestic and foreign; each modeled by a Gaussian one-factor model with deterministic shift (G1$++$) process. For stochastic volatility, we model the variance for the exchange rate by a Cox–Ingersoll–Ross (CIR) process. We include tests to show the convergence and the accuracy of the proposed algorithms.

In this paper, we develop a stochastic model for future monthly spot prices of the most important crude oils and refined products. The model is easy to calibrate to both historical data and views of a user even in the presence of negative prices which have been observed recently. This makes it particularly useful for risk management and design of optimal hedging strategies in incomplete market situations where perfect hedging may be impossible or prohibitively expensive to implement. We illustrate the model with optimization of hedging strategies for refinery margins in illiquid markets using a portfolio of 12 most liquid derivative contracts with 12 maturities traded on New York Mercantile Exchange (NYMEX) and Intercontinental Exchange (ICE).