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Providing a measure of market risk is an important issue for investors and financial institutions. However, the existing models for this purpose are per definition symmetric. The current paper introduces an asymmetric capital asset pricing…

Pricing of Securities · Quantitative Finance 2024-05-07 Abdulnasser Hatemi-J

We introduce an equilibrium asset pricing model, which we build on the relationship between a novel risk measure, the Expected Downside Risk (EDR) and the expected return. On the one hand, our proposed risk measure uses a nonparametric…

Pricing of Securities · Quantitative Finance 2015-12-08 Mihaly Ormos , Dusan Timotity

The paper introduces benchmark-neutral pricing and hedging for long-term contingent claims. It employs the growth optimal portfolio of the stocks as numeraire and the new benchmark-neutral pricing measure for pricing. For a realistic…

Mathematical Finance · Quantitative Finance 2024-07-03 Eckhard Platen

This article considers the pricing and hedging of a call option when liquidity matters, that is, either for a large nominal or for an illiquid underlying asset. In practice, as opposed to the classical assumptions of a price-taking agent in…

Trading and Market Microstructure · Quantitative Finance 2015-04-06 Olivier Guéant , Jiang Pu

In statistical exercises where there are several candidate models, the traditional approach is to select one model using some data driven criterion and use that model for estimation, testing and other purposes, ignoring the variability of…

Statistics Theory · Mathematics 2008-12-18 Snigdhansu Chatterjee , Nitai D. Mukhopadhyay

In this paper we study the pricing and hedging problem of a portfolio of life insurance products under the benchmark approach, where the reference market is modelled as driven by a state variable following a polynomial diffusion on a…

Mathematical Finance · Quantitative Finance 2016-09-26 Francesca Biagini , Yinglin Zhang

We propose a hedging approach for general contingent claims when liquidity is a concern and trading is subject to transaction cost. Multiple assets with different liquidity levels are available for hedging. Our risk criterion targets a…

Mathematical Finance · Quantitative Finance 2018-07-02 Panagiotis Christodoulou , Nils Detering , Thilo Meyer-Brandis

Options are contingent claims regarding the value of underlying assets. The Black-Scholes formula provides a road map for pricing these options in a risk-neutral setting, justified by a delta hedging argument in which countervailing…

Mathematical Finance · Quantitative Finance 2026-05-26 Erina Nanyonga , Matt Davison

We propose a pricing technique based on coherent risk measures, which enables one to get finer price intervals than in the No Good Deals pricing. The main idea consists in splitting a liability into several parts and selling these parts to…

Probability · Mathematics 2008-12-02 Alexander S. Cherny , Dilip B. Madan

Proof that under simple assumptions, such as constraints of Put-Call Parity, the probability measure for the valuation of a European option has the mean derived from the forward price which can, but does not have to be the risk-neutral one,…

Mathematical Finance · Quantitative Finance 2016-09-05 Nassim N. Taleb

We introduce a new model for pricing corporate bonds, which is a modification of the classical model of Merton. In this new model, we drop the liquidity assumption of the firm's asset value process, and assume that there is a liquidly…

Pricing of Securities · Quantitative Finance 2019-10-22 Juan Dong , Lyudmila Korobenko , Deniz Sezer

Model uncertainty is a type of inevitable financial risk. Mistakes on the choice of pricing model may cause great financial losses. In this paper we investigate financial markets with mean-volatility uncertainty. Models for stock markets…

Pricing of Securities · Quantitative Finance 2014-07-31 Yuhong Xu

The Black-Scholes option pricing model remains a cornerstone in financial mathematics, yet its application is often challenged by the need for accurate hedging strategies, especially in dynamic market environments. This paper presents a…

Mathematical Finance · Quantitative Finance 2024-05-07 Agni Rakshit , Gautam Bandyopadhyay , Tanujit Chakraborty

In this paper we study mean-variance hedging under the G-expectation framework. Our analysis is carried out by exploiting the G-martingale representation theorem and the related probabilistic tools, in a contin- uous financial market with…

Mathematical Finance · Quantitative Finance 2016-08-26 Francesca Biagini , Jacopo Mancin , Thilo Meyer Brandis

Relative error approaches are more of concern compared to absolute error ones such as the least square and least absolute deviation, when it needs scale invariant of output variable, for example with analyzing stock and survival data. An…

Methodology · Statistics 2017-04-21 Zhanfeng Wang , Zhuojian Chen , Zimu Chen

In this work, we present a numerical method based on a sparse grid approximation to compute the loss distribution of the balance sheet of a financial or an insurance company. We first describe, in a stylised way, the assets and liabilities…

This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under uncertainty. A relationship between risk envelopes and regret envelopes is established by…

Mathematical Finance · Quantitative Finance 2020-06-16 Jie Sun , Xinmin Yang , Qiang Yao , Min Zhang

We present an alternative approach to the forecasting of motor vehicle collision rates. We adopt an oft-used tool in mathematical finance, the Heston Stochastic Volatility model, to forecast the short-term and long-term evolution of motor…

Applications · Statistics 2022-03-04 Darren Shannon , Grigorios Fountas

We study option pricing and hedging with uncertainty about a Black-Scholes reference model which is dynamically recalibrated to the market price of a liquidly traded vanilla option. For dynamic trading in the underlying asset and this…

Mathematical Finance · Quantitative Finance 2017-04-18 Sebastian Herrmann , Johannes Muhle-Karbe

We observe a $n$-sample, the distribution of which is assumed to belong, or at least to be close enough, to a given mixture model. We propose an estimator of this distribution that belongs to our model and possesses some robustness…

Statistics Theory · Mathematics 2025-02-06 Alexandre Lecestre