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Results for “consumer” · papers 14 · wiki 4
Academic Papers · 14arXiv q-fin live 0 · desk corpus 14
arXiv · arXiv · 2019

Neural Learning of Online Consumer Credit Risk

This paper takes a deep learning approach to understand consumer credit risk when e-commerce platforms issue unsecured credit to finance customers' purchase. The "NeuCredit" model can capture both serial dependences in multi-dimensional time series data when event frequencies in each dimension differ. It also captures nonlinear cross-sectional interactions among different time-evolving features. Also, the predicted d

Di Wang, Qi Wu, Wen Zhang
arXiv · arXiv · 2024

Consumer Transactions Simulation through Generative Adversarial Networks

In the rapidly evolving domain of large-scale retail data systems, envisioning and simulating future consumer transactions has become a crucial area of interest. It offers significant potential to fortify demand forecasting and fine-tune inventory management. This paper presents an innovative application of Generative Adversarial Networks (GANs) to generate synthetic retail transaction data, specifically focusing on

Sergiy Tkachuk, Szymon Łukasik, Anna Wróblewska
arXiv · arXiv · 2022

On the Convergence of Credit Risk in Current Consumer Automobile Loans

Loan seasoning and inefficient consumer interest rate refinance behavior are well-known for mortgages. Consumer automobile loans, which are collateralized loans on a rapidly depreciating asset, have attracted less attention, however. We derive a novel large-sample statistical hypothesis test suitable for loans sampled from asset-backed securities to populate a transition matrix between risk bands. We find all current

Jackson P. Lautier, Vladimir Pozdnyakov, Jun Yan
arXiv · arXiv · 2021

Risk and return prediction for pricing portfolios of non-performing consumer credit

We design a system for risk-analyzing and pricing portfolios of non-performing consumer credit loans. The rapid development of credit lending business for consumers heightens the need for trading portfolios formed by overdue loans as a manner of risk transferring. However, the problem is nontrivial technically and related research is absent. We tackle the challenge by building a bottom-up architecture, in which we mo

Siyi Wang, Xing Yan, Bangqi Zheng, Hu Wang, Wangli Xu
arXiv · arXiv · 2013

Evolutionary Model of a Anonymous Consumer Durable Market

An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion process for durable consumer goods governed by a variation-selection-reproduction mechanism and the growth dynamics can be described by a replicator equation. Describing the aggregate

Joachim Kaldasch
arXiv · arXiv · 2025

Geometric Dynamics of Consumer Credit Cycles: A Multivector-based Linear-Attention Framework for Explanatory Economic Analysis

This study introduces geometric algebra to decompose credit system relationships into their projective (correlation-like) and rotational (feedback-spiral) components. We represent economic states as multi-vectors in Clifford algebra, where bivector elements capture the rotational coupling between unemployment, consumption, savings, and credit utilization. This mathematical framework reveals interaction patterns invis

Agus Sudjianto, Sandi Setiawan
arXiv · arXiv · 2012

Consumer finance data generator - a new approach to Credit Scoring technique comparison

This paper aims to present a general idea of method comparison of Credit Scoring techniques. Any scorecard can be made in various methods based on variable transformations in the logistic regression model. To make a comparison and come up with the proof that one technique is better than another is a big challenge due to the limited availability of data. The same conclusion cannot be guaranteed when using other data f

Karol Przanowski, Jolanta Mamczarz
arXiv · arXiv · 2007

Hiking the hypercube: producers and consumers

We study the dynamics of co-evolution of producers and customers described by bit-strings representing individual traits. Individual ''size-like'' properties are controlled by binary encounters which outcome depends upon a recognition process. Depending upon the parameter set-up, mutual selection of producers and customers results in different types of attractors, either an exclusive niches regime or a competition re

Tanya Araújo, Gérard Weisbuch
arXiv · arXiv · 2026

Liquidity-Based Audit of Algorithmic Trading Strategies

We show that net demand for liquidity by algo strategies is identifiable from its trade and price history alone, with no knowledge of its signal or optimization problem. An exact multi-period regret decomposition implies that the sign of this statistic classifies a linear strategy as a net liquidity consumer or provider, recovering the Kyle (1985) informed-trader/market-maker dichotomy from observables alone. Under a

Irene Aldridge
arXiv · arXiv · 2022

Method of indirect estimation of default probability dynamics for industry-target segments according to the data of Bank of Russia

A direct method for calculating default rates by industry and target corporate segments is not possible given the lack of statistical data. The proposed paper considers a model for filtering the dynamics of the probability of default of corporate companies and other borrowers based on indirect data on the dynamics of overdue debt supplied by the Bank of Russia. The model is based on the equation of the balance of tot

Mikhail Pomazanov
arXiv · arXiv · 2019

Transaction Cost Analytics for Corporate Bonds

The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditi

Xin Guo, Charles-Albert Lehalle, Renyuan Xu
arXiv · arXiv · 2023

Deep Policy Gradient Methods in Commodity Markets

The energy transition has increased the reliance on intermittent energy sources, destabilizing energy markets and causing unprecedented volatility, culminating in the global energy crisis of 2021. In addition to harming producers and consumers, volatile energy markets may jeopardize vital decarbonization efforts. Traders play an important role in stabilizing markets by providing liquidity and reducing volatility. Sev

Jonas Hanetho
arXiv · arXiv · 2022

Nowcasting Stock Implied Volatility with Twitter

In this study, we predict next-day movements of stock end-of-day implied volatility using random forests. Through an ablation study, we examine the usefulness of different sources of predictors and expose the value of attention and sentiment features extracted from Twitter. We study the approach on a stock universe comprised of the 165 most liquid US stocks diversified across the 11 traditional market sectors using a

Thomas Dierckx, Jesse Davis, Wim Schoutens
arXiv · arXiv · 2022

Pricing Time-to-Event Contingent Cash Flows: A Discrete-Time Survival Analysis Approach

Prudent management of insurance investment portfolios requires competent asset pricing of fixed-income assets with time-to-event contingent cash flows, such as consumer asset-backed securities (ABS). Current market pricing techniques for these assets either rely on a non-random time-to-event model or may not utilize detailed asset-level data that is now available with most public transactions. We first establish a fr

Jackson P. Lautier, Vladimir Pozdnyakov, Jun Yan
Wiki Entities · 4
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