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This paper focuses on the valuation and hedging of gas storage facilities, using a spot-based valuation framework coupled with a financial hedging strategy implemented with futures contracts. The first novelty consist in proposing a model…

Pricing of Securities · Quantitative Finance 2014-06-30 Patrick Henaff , Ismail Laachir , Francesco Russo

The classical discrete time model of proportional transaction costs relies on the assumption that a feasible portfolio process has solvent increments at each step. We extend this setting in two directions, allowing for convex transaction…

Mathematical Finance · Quantitative Finance 2021-01-15 Emmanuel Lepinette , Ilya Molchanov

This paper investigates the dynamic reinsurance design problem under the mean-variance criterion, incorporating heterogeneous beliefs between the insurer and the reinsurer, and introducing an incentive compatibility constraint to address…

Optimization and Control · Mathematics 2025-08-19 Junyi Guo , Xia Han , Hao Wang

In this work we present a general representation formula for the price of a vulnerable European option, and the related CVA in stochastic (either rough or not) volatility models for the underlying's price, when admitting correlation with…

Computational Finance · Quantitative Finance 2022-04-26 Elisa Alòs , Fabio Antonelli , Alessandro Ramponi , Sergio Scarlatti

Derivatives, as a critical class of financial instruments, isolate and trade the price attributes of risk assets such as stocks, commodities, and indices, aiding risk management and enhancing market efficiency. However, traditional hedging…

Computational Finance · Quantitative Finance 2025-03-07 Yiheng Ding , Gangnan Yuan , Dewei Zuo , Ting Gao

This paper explores the optimal investment problem of a renewal risk model with generalized Erlang distributed interarrival times. The phases of the Erlang interarrival time is assumed to be observable. The price of the risky asset is…

Optimization and Control · Mathematics 2025-06-04 Linlin Tian , Yixuan Tian , Bohan Li , Guoqing Li

We consider an investor who seeks to maximize her expected utility derived from her terminal wealth relative to the maximum performance achieved over a fixed time horizon, and under a portfolio drawdown constraint, in a market with local…

Portfolio Management · Quantitative Finance 2016-10-28 Ankush Agarwal , Ronnie Sircar

The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the…

Pricing of Securities · Quantitative Finance 2014-09-19 José Da Fonseca , Claude Martini

Value function estimation is an indispensable subroutine in reinforcement learning, which becomes more challenging in the offline setting. In this paper, we propose Hybrid Value Estimation (HVE) to reduce value estimation error, which…

Machine Learning · Computer Science 2022-06-07 Xue-Kun Jin , Xu-Hui Liu , Shengyi Jiang , Yang Yu

This paper presents hedging strategies for European and exotic options in a Levy market. By applying Taylor's Theorem, dynamic hedging portfolios are con- structed under different market assumptions, such as the existence of power jump…

Portfolio Management · Quantitative Finance 2008-12-10 Wing Yan Yip , Sofia Olhede , David Stephens

We extend the Annually Recalculated Virtual Annuity (ARVA) spending rule for retirement savings decumulation to include a cap and a floor on withdrawals. With a minimum withdrawal constraint, the ARVA strategy runs the risk of depleting the…

Computational Finance · Quantitative Finance 2021-01-11 Peter A. Forsyth , Kenneth R. Vetzal , Graham Westmacott

We propose a new model for the joint evolution of the European inflation rate, the European Central Bank official interest rate and the short-term interest rate, in a stochastic, continuous time setting. We derive the valuation equation for…

Mathematical Finance · Quantitative Finance 2022-12-22 F. Antonacci , C. Costantini , F. D'Ippoliti , M. Papi

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We…

Computational Finance · Quantitative Finance 2018-02-12 Hans Bühler , Lukas Gonon , Josef Teichmann , Ben Wood

We consider an optimal investment and risk control problem for an insurer under the mean-variance (MV) criterion. By introducing a deterministic auxiliary process defined forward in time, we formulate an alternative time-consistent problem…

Portfolio Management · Quantitative Finance 2021-01-12 Yang Shen , Bin Zou

We develop a reinforcement learning (RL) framework for insurance loss reserving that formulates reserve setting as a finite-horizon sequential decision problem under claim development uncertainty, macroeconomic stress, and solvency…

Machine Learning · Computer Science 2026-03-24 Stella C. Dong

In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such markets in the case of European options. A…

Pricing of Securities · Quantitative Finance 2020-03-19 Josselin Garnier , Knut Solna

Value at Risk (VaR) and stress testing are two of the most widely used approaches in portfolio risk management to estimate potential market value losses under adverse market moves. VaR quantifies potential loss in value over a specified…

Computational Finance · Quantitative Finance 2024-10-01 Krishan Mohan Nagpal

This paper is devoted to study the effects arising from imposing a value-at-risk (VaR) constraint in mean-variance portfolio selection problem for an investor who receives a stochastic cash flow which he/she must then invest in a…

Portfolio Management · Quantitative Finance 2010-11-24 Jun Ye , Tiantian Li

Since risky positions in multivariate portfolios can be offset by various choices of capital requirements that depend on the exchange rules and related transaction costs, it is natural to assume that the risk measures of random vectors are…

Risk Management · Quantitative Finance 2016-07-12 Ignacio Cascos , Ilya Molchanov

We consider an online stochastic game with risk-averse agents whose goal is to learn optimal decisions that minimize the risk of incurring significantly high costs. Specifically, we use the Conditional Value at Risk (CVaR) as a risk measure…

Machine Learning · Computer Science 2022-06-17 Zifan Wang , Yi Shen , Michael M. Zavlanos