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American put options are among the most frequently traded single stock options, and their calibration is computationally challenging since no closed-form expression is available. Due to the higher flexibility in comparison to European…

Numerical Analysis · Mathematics 2016-11-22 Olena Burkovska , Kathrin Glau , Mirco Mahlstedt , Barbara Wohlmuth

This paper presents a method for incorporating risk aversion into existing decision tree models used in economic evaluations. The method involves applying a probability weighting function based on rank dependent utility theory to reduced…

Theoretical Economics · Economics 2024-01-24 Jacob Smith

We advocate for a practical Maximum Likelihood Estimation (MLE) approach towards designing loss functions for regression and forecasting, as an alternative to the typical approach of direct empirical risk minimization on a specific target…

Machine Learning · Statistics 2021-10-12 Pranjal Awasthi , Abhimanyu Das , Rajat Sen , Ananda Theertha Suresh

In this paper, we propose a novel association measure for longitudinal studies based on the traditional definition of relative risk. In a Markovian fashion, such a proposal takes into account the information content regarding the previous…

Methodology · Statistics 2023-02-27 Lina Buitrago , Juan Sosa , Oscar Melo

We apply the concepts of utility based pricing and hedging of derivatives in stochastic volatility markets and introduce a new class of "reciprocal affine" models for which the indifference price and optimal hedge portfolio for pure…

Probability · Mathematics 2008-12-02 M. R. Grasselli , T. R. Hurd

We investigate model risk and distributionally robust optimization (DRO) under marginal and martingale constraints. Building on our previous work, we address the previously open case of static hedging with second-period maturity vanilla…

Probability · Mathematics 2026-01-29 Nathan Sauldubois

This paper investigates the hedging performance of pegged foreign exchange market in a regime switching (RS) model introduced in a recent paper by Drapeau, Wang and Wang (2019). We compare two prices, an exact solution and first order…

Mathematical Finance · Quantitative Finance 2020-05-29 Samuel Drapeau , Yunbo Zhang

Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local…

Pricing of Securities · Quantitative Finance 2014-04-16 Mark Higgins

In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be…

Mathematical Finance · Quantitative Finance 2021-05-11 Masaaki Fukasawa , Blanka Horvath , Peter Tankov

How to price and hedge claims on nontraded assets are becoming increasingly important matters in option pricing theory today. The most common practice to deal with these issues is to use another similar or "closely related" asset or index…

Pricing of Securities · Quantitative Finance 2014-01-28 Marcelo J. Villena , Axel A. Araneda

The need for control strategies that can address dynamic system uncertainty is becoming increasingly important. In this work, we propose a Model Predictive Control by quantifying the risk of failure in our system model. The proposed control…

Systems and Control · Electrical Eng. & Systems 2023-02-17 Mostafa Tavakkoli Anbarani , Efe C. Balta , Rômulo Meira-Góes , Ilya Kovalenko

We consider option hedging in a model where the underlying follows an exponential L\'evy process. We derive approximations to the variance-optimal and to some suboptimal strategies as well as to their mean squared hedging errors. The…

Computational Finance · Quantitative Finance 2017-07-25 Aleš Černý , Stephan Denkl , Jan Kallsen

When interest rate dynamics are described by the Libor Market Model as in BGM97, we show how some essential risk-management results can be obtained from the dual of the calibration program. In particular, if the objetive is to maximize…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Alexandre d'Aspremont

This study presents contemporaneous modeling of asset return and price range within the framework of stochastic volatility with leverage. A new representation of the probability density function for the price range is provided, and its…

Computation · Statistics 2021-10-28 Yuta Kurose

We propose a distributional framework for benchmarking socio-technical risks of foundation models with quantified statistical significance. Our approach hinges on a new statistical relative testing based on first and second order stochastic…

Harrel's concordance index is a commonly used discrimination metric for survival models, particularly for models where the relative ordering of the risk of individuals is time-independent, such as the proportional hazards model. There are…

Methodology · Statistics 2023-06-27 A. Gandy , T. J. Matcham

The estimation of risk measures recently gained a lot of attention, partly because of the backtesting issues of expected shortfall related to elicitability. In this work we shed a new and fundamental light on optimal estimation procedures…

Risk Management · Quantitative Finance 2017-08-25 Marcin Pitera , Thorsten Schmidt

This paper establishes the first analytical relationship between predictive model performance and loss ratio in insurance pricing. We derive a closed-form formula connecting the Pearson correlation between predicted and actual losses to…

Risk Management · Quantitative Finance 2025-12-04 C. Evans Hedges

In the over-the-counter market in derivatives, we sometimes see large numbers of traders taking the same position and risk. When there is this kind of concentration in the market, the position impacts the pricings of all other derivatives…

Pricing of Securities · Quantitative Finance 2016-12-05 Jun Maeda , Saul D. Jacka

We introduce a new regression method that relates the mean of an outcome variable to covariates, under the "adverse condition" that a distress variable falls in its tail. This allows to tailor classical mean regressions to adverse…

Econometrics · Economics 2025-02-04 Timo Dimitriadis , Yannick Hoga
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