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We propose a portfolio approach for operational risk quantification based on a class of analytical models from which we derive new results on the correlation problem. In particular, we show that uniform correlation is a robust assumption…

Risk Management · Quantitative Finance 2014-05-08 Vivien Brunel

Customer scoring models are the core of scalable direct marketing. Uplift models provide an estimate of the incremental benefit from a treatment that is used for operational decision-making. Training and monitoring of uplift models require…

Machine Learning · Computer Science 2019-10-02 Johannes Haupt , Daniel Jacob , Robin M. Gubela , Stefan Lessmann

This research critically analyses blockchain scaling solutions based on their ability to realistically balance the properties of the blockchain trilemma. We have concluded this research by outlining a gap in the current body of literature…

Cryptography and Security · Computer Science 2022-02-02 Frazer Chard , Cayo Fletcher-Smith

We propose a versatile Monte-Carlo method for pricing and hedging options when the market is incomplete, for an arbitrary risk criterion (chosen here to be the expected shortfall), for a large class of stochastic processes, and in the…

Condensed Matter · Physics 2007-05-23 Benoît Pochart , Jean-Philippe Bouchaud

We introduce a novel logic for the specification of context-free hyperproperties, which capture, e.g., the flow of information in security-critical recursive systems. Intuitively, the logic extends visibly pushdown automata by…

Logic in Computer Science · Computer Science 2026-05-07 Sarah Winter , Martin Zimmermann

Uplift modeling is aimed at estimating the incremental impact of an action on an individual's behavior, which is useful in various application domains such as targeted marketing (advertisement campaigns) and personalized medicine (medical…

Machine Learning · Statistics 2018-11-21 Ikko Yamane , Florian Yger , Jamal Atif , Masashi Sugiyama

The standard approach for compensating liquidity providers on many decentralized exchanges (DEX) for serving as counter-party to swaps is through charging a small percentage of fees. The expected payoff from the cash flow of this mode of…

Mathematical Finance · Quantitative Finance 2022-09-07 Jin Hong Kuan

We introduce a novel approach to options trading strategies using a highly scalable and data-driven machine learning algorithm. In contrast to traditional approaches that often require specifications of underlying market dynamics or…

Portfolio Management · Quantitative Finance 2024-11-22 Wee Ling Tan , Stephen Roberts , Stefan Zohren

Pricing financial or real options with arbitrary payoffs in regime-switching models is an important problem in finance. Mathematically, it is to solve, under certain standard assumptions, a general form of optimal stopping problems in…

Mathematical Finance · Quantitative Finance 2018-09-11 Masahiko Egami , Rusudan Kevkhishvili

Concentrated liquidity (CL) provisioning is a way how to improve the capital efficiency of Automated Market Makers (AMM). Allowing liquidity providers to use leverage is a step towards even higher capital efficiency. A number of…

Trading and Market Microstructure · Quantitative Finance 2024-09-20 Atis Elsts , Krešimir Klas

Stylized facts can be regarded as constraints for any modeling attempt of price dynamics on a financial market, in that an empirically reasonable model has to reproduce these stylized facts at least qualitatively. The dynamics of market…

Computational Finance · Quantitative Finance 2010-04-12 Stefan Reimann , Andreas Tupak

This paper presents a simple, effective, and cost-efficient strategy to improve LLM performance by scaling test-time compute. Our strategy builds upon the repeated-sampling-then-voting framework, with a novel twist: incorporating multiple…

Artificial Intelligence · Computer Science 2025-11-11 Jianhao Chen , Zishuo Xun , Bocheng Zhou , Han Qi , Hangfan Zhang , Qiaosheng Zhang , Yang Chen , Wei Hu , Yuzhong Qu , Wanli Ouyang , Shuyue Hu

This paper investigates whether a financial system can be made more stable if financial institutions share risk by exchanging contingent convertible (CoCo) debt obligations. The question is framed in a financial network model of debt and…

Risk Management · Quantitative Finance 2022-10-27 Zachary Feinstein , T. R. Hurd

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 this paper, we present a method for constructing a (static) portfolio of co-maturing European options whose price sign is determined by the skewness level of the associated implied volatility. This property holds regardless of the…

Pricing of Securities · Quantitative Finance 2016-11-18 Sergey Nadtochiy , Jan Obloj

The recent "correlation breakdown" in the modeling of credit default swaps, in which model correlations had to exceed 100% in order to reproduce market prices of supersenior tranches, is analyzed and argued to be a fundamental market…

Pricing of Securities · Quantitative Finance 2009-09-01 Rodanthy Tzani , Alexios P. Polychronakos

We consider a seller who offers services to a buyer with multi-unit demand. Prior to the realization of demand, the buyer receives a noisy signal of their future demand, and the seller can design contracts based on the reported value of…

Theoretical Economics · Economics 2025-02-13 Dirk Bergemann , Michael C. Wang

We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with pair-copula constructions, and nest…

Mathematical Finance · Quantitative Finance 2018-01-19 Damien Ackerer , Thibault Vatter

We propose a possible solution to a public challenge posed by the Fair Isaac Corporation (FICO), which is to provide an explainable model for credit risk assessment. Rather than present a black box model and explain it afterwards, we…

Machine Learning · Computer Science 2018-12-03 Chaofan Chen , Kangcheng Lin , Cynthia Rudin , Yaron Shaposhnik , Sijia Wang , Tong Wang

We introduce a local volatility model for the valuation of options on commodity futures by using European vanilla option prices. The corresponding calibration problem is addressed within an online framework, allowing the use of multiple…

Computational Finance · Quantitative Finance 2016-02-16 Vinicius Albani , Uri M. Ascher , Jorge P. Zubelli