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Machine learning models are increasingly used to automate decisions that affect humans - deciding who should receive a loan, a job interview, or a social service. In such applications, a person should have the ability to change the decision…

Machine Learning · Statistics 2019-11-12 Berk Ustun , Alexander Spangher , Yang Liu

We consider the problem of optimal consumption from labor income and investment in a general incomplete semimartingale market. The economic agent cannot borrow against future income, so the total wealth is required to be positive at (all or…

Probability · Mathematics 2019-01-29 Oleksii Mostovyi , Mihai Sîrbu

In applied probability, the normal approximation is often used for the distribution of data with assumed additive structure. This tradition is based on the central limit theorem for sums of (independent) random variables. However, it is…

Probability · Mathematics 2020-10-27 Alexandra Dorofeeva , Victor Korolev , Alexander Zeifman

We introduce a necessary and sufficient criterion for determining the existence and the values of ratio limits of complex sequences generated by arbitrary linear recurrences.

Number Theory · Mathematics 2017-04-11 Igor Szczyrba

The negative externalities from an individual bank failure to the whole system can be huge. One of the key purposes of bank regulation is to internalize the social costs of potential bank failures via capital charges. This study proposes a…

General Finance · Quantitative Finance 2014-04-24 Xiaobing Feng , Haibo Hu

Inverse Reinforcement Learning (IRL) algorithms infer a reward function that explains demonstrations provided by an expert acting in the environment. Maximum Causal Entropy (MCE) IRL is currently the most popular formulation of IRL, with…

Machine Learning · Computer Science 2022-03-23 Adam Gleave , Sam Toyer

We present compelling empirical evidence for a new interpretation of the Forward Rate Curve (FRC) term structure. We find that the average FRC follows a square-root law, with a prefactor related to the spot volatility, suggesting a…

Condensed Matter · Physics 2007-05-23 Andrew Matacz , Jean-Philippe Bouchaud

The study analyzed the impact of financial inclusion on the effectiveness of monetary policy in developing countries. By using a panel data set of 10 developing countries during 2004-2020, the study revealed that the financial inclusion…

General Economics · Economics 2023-08-25 Gautam Kumar Biswas , Faruque Ahamed

Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, informative bounds on these effects can often be derived under plausible assumptions. Even when these bounds are…

Methodology · Statistics 2024-04-18 Julien D. Laurendeau , Aaron L. Sarvet , Mats J. Stensrud

A statistical characterization of the fundamental performance bounds of an intelligent reflective surface (IRS) intended for aiding wireless communications is presented. To this end, the outage probability, average symbol error probability,…

Signal Processing · Electrical Eng. & Systems 2020-02-14 Dhanushka Kudathanthirige , Dulaj Gunasinghe , Gayan Amarasuriya

The aim of this study is to present proofs for new theorems. Basic thoughts of new definitions emerge from the decision-making under uncertainty in economics and finance. Shape of the certain utility curve is central to standard definitions…

General Finance · Quantitative Finance 2025-10-15 Atilla Aras

This paper analyses the impact of credit expansions arising from decreases in collateral requirements or more expansionary monetary policies on long-term productivity in a model with endogenous growth. Credit expansions associated with…

Theoretical Economics · Economics 2026-02-23 Tomohiro Hirano , Joseph E. Stiglitz

Inverse reinforcement learning (IRL) is the problem of finding a reward function that generates a given optimal policy for a given Markov Decision Process. This paper looks at an algorithmic-independent geometric analysis of the IRL problem…

Machine Learning · Computer Science 2021-02-19 Abi Komanduru , Jean Honorio

The goal of the Inverse reinforcement learning (IRL) task is to identify the underlying reward function and the corresponding optimal policy from a set of expert demonstrations. While most IRL algorithms' theoretical guarantees rely on a…

Machine Learning · Statistics 2025-03-25 Ruijia Zhang , Siliang Zeng , Chenliang Li , Alfredo Garcia , Mingyi Hong

In this paper, we accomplish two objectives: First, we provide a new mathematical characterization of the value function for impulse control problems with implementation delay and present a direct solution method that differs from its…

Optimization and Control · Mathematics 2008-12-10 Erhan Bayraktar , Masahiko Egami

In several real-world applications involving decision making under uncertainty, the traditional expected value objective may not be suitable, as it may be necessary to control losses in the case of a rare but extreme event. Conditional…

Machine Learning · Computer Science 2018-08-07 Ravi Kumar Kolla , Prashanth L. A. , Sanjay P. Bhat , Krishna Jagannathan

General wrong way risk (WWR) estimation is necessary for regulatory CVA capital and useful for pricing CVA and FVA. We introduce a model independent method for calculating WWR and update the definition of WWR to deal with the lack of…

Pricing of Securities · Quantitative Finance 2021-10-11 Chris Kenyon , Mourad Berrahoui , Benjamin Poncet

We develop an axiomatic theory of balance functions (future value functions) in the theory of interest that is derived from financial considerations and which applies to general regulated payment streams, including continuous payment…

General Finance · Quantitative Finance 2012-08-08 David Spring

Randomized controlled trials typically analyze the effectiveness of treatments with the goal of making treatment recommendations for patient subgroups. With the advance of electronic health records, a great variety of data has been…

Machine Learning · Computer Science 2021-03-31 Zhiliang Wu , Yinchong Yang , Yunpu Ma , Yushan Liu , Rui Zhao , Michael Moor , Volker Tresp

We study loop corrections in the effective field theory of inflation with imaginary speed of sound, which has been shown to provide an effective description of multi-field inflationary models characterized by strongly non-geodesic motion…

High Energy Physics - Theory · Physics 2025-11-14 Sebastian Garcia-Saenz , Yizhou Lu , Sébastien Renaux-Petel