A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study shows how machine learning can improve human performance in deception detection.
AI system narrows human decision options for better outcomes.
Transportation agencies have an opportunity to leverage increasingly-available trajectory datasets to improve their analyses and decision-making processes. However, this data is typically purchased from vendors, which means agencies must understand its potential benefits beforehand in order to properly assess its value…
We introduce a model in which a regulator employs mechanism design to embed her human capital beta signal(s) in a firm's capital structure, in order to enhance the value of her post career change indexed executive stock option contract with the firm. We prove that the agency cost of this revolving door behavior increas…
New decision support systems use prediction sets to help experts update their predictions, improving performance.
A new hierarchy quantifies agency in systems based on information processing.
The credit crisis of 2007 and 2008 has thrown much focus on the models used to price mortgage backed securities. Many institutions have relied heavily on the credit ratings provided by credit agency. The relationships between management of credit agencies and debt issuers may have resulted in conflict of interest when …
TRIBE model uses LLMs to simulate human trading behavior in bond markets.
SPAC data shows premium investors get better terms, non-premium get quid pro quo deals.
Money is a technology for promoting economic prosperity. Over history money has become increasingly abstract, it used to be hardware, gold coins and the like, now it is mostly software, data structures located in banks. Here I propose the logical conclusion of the abstraction of money: to use as money the most general …
GARIM theory explains how conscious manipulation of internal representations enhances goal-directed behavior.
Central Counterparties (CCPs) are widely promoted as a requirement for safe banking with little dissent except on technical grounds (such as proliferation of CCPs). Whilst CCPs can have major operational positives, we argue that CCPs have many of the business characteristics of Rating Agencies, and face similar busines…
Research funding agencies routinely use a proportion of their total revenues to support internal administration and marketing costs. The ratio of administration to total costs, referred to as the administration ratio, is highly variable and within any single fund depends on many factors including the number and average…
HighRes-net enhances satellite imagery by fusing multiple low-res views.
We propose a betting strategy based on Bayesian logistic regression modeling for the probability forecasting game in the framework of game-theoretic probability by Shafer and Vovk (2001). We prove some results concerning the strong law of large numbers in the probability forecasting game with side information based on …
System uses conformal prediction to help experts make accurate decisions without understanding when to trust it.
According to Dennett, the same system may be described using a `physical' (mechanical) explanatory stance, or using an `intentional' (belief- and goal-based) explanatory stance. Humans tend to find the physical stance more helpful for certain systems, such as planets orbiting a star, and the intentional stance for othe…
LLMs can identify tax strategies, potentially revolutionizing tax enforcement.
In this paper the problem of optimal derivative design, profit maximization and risk minimization under adverse selection when multiple agencies compete for the business of a continuum of heterogenous agents is studied. The presence of ties in the agents' best-response correspondences yields discontinuous payoff functi…
This paper focuses on the problem of estimating historical traffic volumes between sparsely-located traffic sensors, which transportation agencies need to accurately compute statewide performance measures. To this end, the paper examines applications of vehicle probe data, automatic traffic recorder counts, and neural …
Fed-FEARE model extracts rules from multiple agencies' data securely.
Study examines human factors in radiographic testing to improve inspection performance.
Paper tackles ESG rating disagreement in sustainable investing portfolios.
We present an analysis of oil prices in US$ and in other major currencies that diagnoses unsustainable faster-than-exponential behavior. This supports the hypothesis that the recent oil price run-up has been amplified by speculative behavior of the type found during a bubble-like expansion. We also attempt to unravel t…
This paper examines how ESG factors influence sovereign bond yields and credit ratings.
We propose an indicator to measure the degree to which a particular news article is novel, as well as an indicator to measure the degree to which a particular news item attracts attention from investors. The novelty measure is obtained by comparing the extent to which a particular news article is similar to earlier new…
We reformulate the Cont-Bouchaud model of financial markets in terms of classical "super-spins" where the spin value is a measure of the number of individual traders represented by a portfolio manager of an investment agency. We then extend this simplified model by switching on interactions among the super-spins to mod…
Increasing energy efficiency in buildings can reduce costs and emissions substantially. Historically, this has been treated as a local, or single-agent, optimization problem. However, many buildings utilize the same types of thermal equipment e.g. electric heaters and hot water vessels. During operation, occupants in t…
This paper reviews deep learning techniques for face recognition and sketch matching.
This research uses reinforcement learning to find optimal emission offsets in greenhouse gas markets.
Paper presents a model for identifying informative COVID-19 tweets.
The study proposes an audit to assess user control over recommendations in collaborative filtering systems.
Framework classifies urban congestion into recurrent and non-recurrent types.
Collective motion is an intriguing phenomenon, especially considering that it arises from a set of simple rules governing local interactions between individuals. In theoretical models, these rules are normally \emph{assumed} to take a particular form, possibly constrained by heuristic arguments. We propose a new class …
Paper predicts in-situ metro passenger density using smart card data.
The paper defines fair profit sharing ratios in Islamic PL contracts.
Efficiently preserves privacy in logistic regression for IoT data.
Study optimal contracts for pandemic risk, offering fixed shares and prevention mechanisms.
Paper uses clustering to identify food assistance deserts in Ohio.
Machine learning methods have gained a great deal of popularity in recent years among public administration scholars and practitioners. These techniques open the door to the analysis of text, image and other types of data that allow us to test foundational theories of public administration and to develop new theories. …
The quality of machine translation is rapidly evolving. Today one can find several machine translation systems on the web that provide reasonable translations, although the systems are not perfect. In some specific domains, the quality may decrease. A recently proposed approach to this domain is neural machine translat…
Optimal linear contracts are possible even with memory in Gaussian settings.
PriceAggregator optimizes hotel price fetching to increase Agoda's bookings.
The paper proposes a new method to assess financial risk and total risk in EU using Markov chains and copulas.
Data science principles enhance AI interpretability for better user control.
Regshock visualizes financial risks to help regulators manage systemic shocks.
Optimal liquidation using VWAP strategies has been considered in the literature, though never in the presence of permanent market impact and only rarely with execution costs. Moreover, only VWAP strategies have been studied and the pricing of guaranteed VWAP contracts has never been addressed. In this article, we devel…
The objective of this article is to analyze the impact of capital structure on profitability. This impact can be explained by three essential theories: signaling theory, tax theory and the agency costs theory. A sample of 1846 French industrial firms are taken over the period 1999-2006, as a dynamic panel study by usin…