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The existence of asymmetric information has always been a major concern for financial institutions. Financial intermediaries such as commercial banks need to study the quality of potential borrowers in order to make their decision on…

Statistical Finance · Quantitative Finance 2017-07-05 Jinglun Yao , Maxime Levy-Chapira , Mamikon Margaryan

We study the impact of learning on the optimal policy and the time-to-decision in an infinite-horizon Bayesian sequential decision model with two irreversible alternatives, exit and expansion. In our model, a firm undertakes a small-scale…

Optimization and Control · Mathematics 2019-01-15 H. Dharma Kwon , Steven A. Lippman

Statistical arbitrage exploits temporal price differences between similar assets. We develop a framework to jointly identify similar assets through factors, identify mispricing and form a trading policy that maximizes risk-adjusted…

Machine Learning · Computer Science 2025-10-14 Elliot L. Epstein , Rose Wang , Jaewon Choi , Markus Pelger

Net profit is sometimes found from data for net operating surplus. We propose a way to find it from data for consumption, pay and market-value capital, and concomitantly to reveal the factor shares in consumption.

General Economics · Economics 2024-10-21 Gordon Getty , Nikita Tkachenko

As financial instruments grow in complexity more and more information is neglected by risk optimization practices. This brings down a curtain of opacity on the origination of risk, that has been one of the main culprits in the 2007-2008…

General Finance · Quantitative Finance 2019-10-23 Marco Bardoscia , Daniele d'Arienzo , Matteo Marsili , Valerio Volpati

In financial asset management, choosing a portfolio requires balancing returns, risk, exposure, liquidity, volatility and other factors. These concerns are difficult to compare explicitly, with many asset managers using an intuitive or…

Computational Engineering, Finance, and Science · Computer Science 2017-08-28 Kevin Tee , Michael McCourt , Ruben Martinez-Cantin , Ian Dewancker , Frank Liu

The sparse factorization of a large matrix is fundamental in modern statistical learning. In particular, the sparse singular value decomposition and its variants have been utilized in multivariate regression, factor analysis, biclustering,…

Machine Learning · Statistics 2020-03-19 Kun Chen , Ruipeng Dong , Wanwan Xu , Zemin Zheng

Given a new candidate asset represented as a time series of returns, how should a quantitative investment manager be thinking about assessing its usefulness? This is a key qualitative question inherent to the investment process which we aim…

Statistical Finance · Quantitative Finance 2018-06-25 Yves-Laurent Kom Samo , Dieter Hendricks

American football is unique in that offensive and defensive units typically consist of separate players who don't share the field simultaneously, which tempts one to evaluate them independently. However, a team's offensive and defensive…

Applications · Statistics 2025-06-04 Andrey Skripnikov , Sujit Sivadanam

Hedging a portfolio containing autocallable notes presents unique challenges due to the complex risk profile of these financial instruments. In addition to hedging, pricing these notes, particularly when multiple underlying assets are…

Computational Engineering, Finance, and Science · Computer Science 2024-11-05 Anil Sharma , Freeman Chen , Jaesun Noh , Julio DeJesus , Mario Schlener

The aim of this paper is to introduce a synthetic ALM model that catches the main specificity of life insurance contracts. First, it keeps track of both market and book values to apply the regulatory profit sharing rule. Second, it…

Risk Management · Quantitative Finance 2019-08-05 Aurélien Alfonsi , Adel Cherchali , Jose Arturo Infante Acevedo

We consider risk averse investors with different levels of anxiety about asset price drawdowns. The latter is defined as the distance of the current price away from its best performance since inception. These drawdowns can increase either…

Mathematical Finance · Quantitative Finance 2020-06-02 Neofytos Rodosthenous , Hongzhong Zhang

Many real-world analytics problems involve two significant challenges: prediction and optimization. Due to the typically complex nature of each challenge, the standard paradigm is predict-then-optimize. By and large, machine learning tools…

Optimization and Control · Mathematics 2020-11-23 Adam N. Elmachtoub , Paul Grigas

We consider the problem of automatically proving resource bounds. That is, we study how to prove that an integer-valued resource variable is bounded by a given program expression. Automatic resource-bound analysis has recently received…

Programming Languages · Computer Science 2021-10-15 Tianhan Lu , Bor-Yuh Evan Chang , Ashutosh Trivedi

We revisit the index leverage effect, that can be decomposed into a volatility effect and a correlation effect. We investigate the latter using a matrix regression analysis, that we call `Principal Regression Analysis' (PRA) and for which…

Statistical Finance · Quantitative Finance 2013-01-29 Pierre-Alain Reigneron , Romain Allez , Jean-Philippe Bouchaud

Machine learning algorithms with empirical risk minimization are vulnerable under distributional shifts due to the greedy adoption of all the correlations found in training data. Recently, there are robust learning methods aiming at this…

Machine Learning · Computer Science 2021-05-12 Jiashuo Liu , Zheyan Shen , Peng Cui , Linjun Zhou , Kun Kuang , Bo Li , Yishi Lin

We present a decomposition method for stochastic programs with 0-1 variables in the second-stage with absolute semi-deviation (ASD) risk measure. Traditional stochastic programming models are risk-neutral where expected costs are considered…

Optimization and Control · Mathematics 2016-05-27 Saravanan Venkatachalam , Lewis Ntaimo

Online Resource Allocation problem is a central problem in many areas of Computer Science, Operations Research, and Economics. In this problem, we sequentially receive $n$ stochastic requests for $m$ kinds of shared resources, where each…

Data Structures and Algorithms · Computer Science 2025-05-07 Rohan Ghuge , Sahil Singla , Yifan Wang

Put-call parity is risk-neutral at terminal payoff, but its enforcement is path-dependent and capital-using. I test whether the SPX and RUT carry gap is explained by OIS-based funding, volatility, trading-friction, and financial-condition…

General Finance · Quantitative Finance 2026-05-26 Useong Shin

We consider the problem of option hedging in a market with proportional transaction costs. Since super-replication is very costly in such markets, we replace perfect hedging with an expected loss constraint. Asymptotic analysis for small…

Portfolio Management · Quantitative Finance 2014-09-12 Bruno Bouchard , Ludovic Moreau , Mete H. Soner