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arXiv research

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.

168,695 papers · 148 categories

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295886115 · Jun 202019922001200920172026
48 results for agent lender

Contextual bandit framework improves revenue optimization in securities lending market.

problem Optimizing revenue for agent lenders in a dynamic securities lending market.
method Utilized contextual bandit frameworks to address dynamic pricing problems in an e-commerce-like securities lending market.
result Contextual bandit approach consistently outperforms traditional methods by at least 15% in total revenue generated.

We consider a fundamental dynamic allocation problem motivated by the problem of securities lending\textit{securities lending} in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of identical copies of some scarce resource to nn clients, each of whom has a priv…

2019-12-12abs ↗pdf ↗

A new framework integrates credit scoring into profit scoring for better P2P lending investments.

problem Maximizing profit while minimizing risk in P2P lending investments.
method Two-stage framework using Light Gradient Boosting Machine (lightGBM) to integrate credit scoring into profit scoring.
result The proposed framework identifies more profitable loans and provides better investment guidance.

Systemic risks of default contagion in the Russian interbank market are investigated. The analysis is based on considering the bow-tie structure of the weighted oriented graph describing the structure of the interbank loans. A probabilistic model of interbank contagion explicitly taking into account the empirical bow-t…

2014-09-03abs ↗pdf ↗

Inspired by recent ideas on how the analysis of complex financial risks can benefit from analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk---a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of net…

2015-04-22abs ↗pdf ↗

In this empirical paper we show that in the months following a crash there is a distinct connection between the fall of stock prices and the increase in the range of interest rates for a sample of bonds. This variable, which is often referred to as the interest rate spread variable, can be considered as a statistical m…

1999-10-14abs ↗pdf ↗

We introduce an innovative theoretical framework to model derivative transactions between defaultable entities based on the principle of arbitrage freedom. Our framework extends the traditional formulations based on Credit and Debit Valuation Adjustments (CVA and DVA). Depending on how the default contingency is accoun…

2011-12-07abs ↗pdf ↗

We derive a "semi-analytic" solution for a stock loan in which the lender forces liquidation when the loan-to-collateral ratio drops beneath a certain threshold. We use this to study the sensitivity of the contract to model parameters.

2016-02-01abs ↗pdf ↗

The study calculates securities lending haircuts and indemnification costs.

problem Managing borrower default risk in securities markets.
method Repo haircut model applied to securities lending transactions; quantifies haircuts and indemnification costs.
result Computed borrower-dependent haircuts and indemnification costs for US Treasuries and equities.

Study loan contracts in DLPs using derivatives pricing and neural networks.

problem Optimizing and hedging risks in decentralized lending contracts.
method Derivatives pricing theory, deep neural networks, and statistical arbitrage.
result Developed a method to hedge risks in lending contracts and exploit arbitrage opportunities.

The paper analyzes sterling bills of exchange during the first globalization, revealing their global financial role.

problem Understanding the global financial role of sterling bills of exchange during the first globalization.
method Descriptive statistics and network analysis of a unique data set of 23,493 bills re-discounted by the Bank of England in 1906.
result Sterling bills of exchange had a truly global dimension and were crucial for overcoming information asymmetries.

The study examines biases in Kiva.org's microfinance platform and proposes methods to mitigate them.

problem Identifying and mitigating hidden biases in lender preferences for different sectors on Kiva.org.
method The study uses causal inference and regression models with Bayesian variable selection methods to investigate and quantify biases. Fairness constraints are then incorporated to maintain comparable results.
result The influence of economic factors and loan attributes on lender preferences varies by sector, and models can be adjusted to mitigate biases.

Dynamic pricing improves DeFi lending efficiency by reducing regret to logarithmic levels.

problem Static pricing mechanisms in DeFi lending protocols lead to suboptimal welfare and revenue.
method Online learning model for static and dynamic pricing models in DeFi lending.
result Adaptive supply models achieve logarithmic regret, outperforming static models.

Model proposes how regulators should oversee complex algorithms in high-stakes applications.

problem Regulating complex algorithms used in high-stakes applications like lending, testing, and hiring.
method Proposes a model where regulators are limited in learning about complex algorithms with misaligned preferences, and explores different regulatory approaches.
result Complex algorithms can improve welfare, but regulation should focus on the source of incentive misalignment for optimal results.

The paper reduces estimation error in predicting borrower repayment by accounting for lender's credit decisions.

problem Estimation error in predicting borrower repayment due to confounding effects.
method Proposes new estimators to reduce estimation error, combining theoretical analysis and numerical testing.
result The proposed estimators are unbiased, consistent, and robust, showing substantial reduction in estimation error.

The definition of deposit substitutes in Philippine tax law fails to consider the maturity of a debt instrument. This makes it possible for long-term bonds to be considered as deposit substitutes if they meet the 20-lender rule, taxable at 20% final tax. However, long-term debt instruments cannot realistically function…

2017-12-28abs ↗pdf ↗

This paper proposes a two-stage scoring approach to help lenders decide their fund allocations in the peer-to-peer (P2P) lending market. The existing scoring approaches focus on only either probability of default (PD) prediction, known as credit scoring, or profitability prediction, known as profit scoring, to identify…

2018-10-05abs ↗pdf ↗

Game theory applied to financial networks, focusing on debt repayment strategies.

problem Understanding financial stability in interconnected systems.
method Modeling financial systems as networks, analyzing utility-maximizing strategies under priority-proportional payments.
result Existence and uniqueness of payment profiles are not guaranteed, even under fixed strategies.

Paper uses BERT to assess P2P borrowers' credit risk from loan descriptions.

problem Information asymmetry in P2P lending due to lack of borrower data.
method Fine-tunes BERT on Lending Club dataset to generate risk scores from loan descriptions.
result BERT-generated risk scores improve XGBoost classifier's performance in loan granting.

I sketch a program for a microeconomic theory of the main component of the business cycle as a recurring disequilibrium, driven by incompleteness of the financial market and by information asymmetries between borrowers and lenders. This proposal seeks to incorporate five distinct but connected processes that have been …

2013-12-02abs ↗pdf ↗

The study predicts bankruptcy in Indian companies using financial ratios.

problem Predicting early signs of corporate bankruptcy in Indian companies.
method Logistic regression considering profitability, leverage, and efficiency ratios for one and two years before bankruptcy.
result The model accurately predicts bankruptcy with 81.4% and 85.1% accuracy one and two years before filing, respectively.

Current auto loans converge to super-prime credit despite remaining underwater.

problem Inefficient consumer behavior in auto loans leading to suboptimal credit risk.
method Large-sample statistical hypothesis test on transition matrix between risk bands.
result All current risk bands converge to super-prime credit, despite remaining underwater.

Retail investors set interest rates for P2P loans based on borrower characteristics.

problem Understanding how individual investors price credit risk in online consumer loan auctions.
method Reverse auction framework, analyzing interest rate variance and borrower characteristics.
result Retail investors exhibit strong predictability in pricing, with gender and marital status influencing interest rates.

Private credit markets have expanded significantly, offering unique lending technology to private equity firms.

problem Understanding the growth and characteristics of private credit markets.
method Systematic survey of academic literature, development of integrated theoretical framework, empirical evidence.
result Private credit markets offer a distinct lending technology with higher spreads over syndicated loans.

Method models other agents' behaviors without requiring direct observation.

problem Understanding and interacting effectively with other agents in reinforcement learning.
method Extracts representations from local observations of the controlled agent using encoder-decoder architectures.
result The method achieves higher returns than baseline methods in multi-agent environments.

Agent-to-agent finance aims to manage payments and trust for AI agents.

problem Managing financial interactions between autonomous AI agents.
method Develops agent-to-agent finance concept and explores blockchain solutions.
result Agent-to-agent finance can address coordination frictions in financial markets.

AI agents manage portfolios, improving on human oversight.

problem Improving strategic asset allocation for institutional investors.
method 50 specialized agents produce capital market assumptions, construct portfolios, critique, and vote on each other's output.
result Meta-agent compares forecasts with realized returns and improves agent performance.

New algorithm reduces learning regret in multi-agent systems with unknown dynamics.

problem Challenges in decentralized learning due to unknown dynamics and lack of communication.
method Proposed MARL algorithm for two-agent LQ systems with unknown dynamics and one-directional communication.
result Achieved O(T)O(\sqrt{T}) regret bound for multi-agent LQ systems with certain communication patterns.

Agents learn to give rewards to others in a shared learning environment.

problem How to encourage cooperation among RL agents in a shared environment.
method Each agent learns a reward function to influence others, optimizing for its own and others' extrinsic objectives.
result Agents significantly outperform standard RL in Markov games, often finding near-optimal division of labor.

New algorithm reduces regret in multi-agent bandits with malicious agents.

problem Collaboration between honest and malicious agents in multi-armed bandits.
method Dynamic reduction of communication with malicious agents, learning who is malicious.
result Algorithm reduces regret even with a single malicious agent, assuming mm is small compared to KK.

We formulate and analyze a multi-agent model for the evolution of individual and systemic risk in which the local agents interact with each other through a central agent who, in turn, is influenced by the mean field of the local agents. The central agent is stabilized by a bistable potential, the only stabilizing force…

2015-07-29abs ↗pdf ↗