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 finds strict collection policies improve portfolio quality of microfinance banks.
Study shows how macroprudential policies affect credit growth in Israel, especially in housing and business sectors.
A variety of cooperative multi-agent control problems require agents to achieve individual goals while contributing to collective success. This multi-goal multi-agent setting poses difficulties for recent algorithms, which primarily target settings with a single global reward, due to two new challenges: efficient explo…
Estimates RL data for dynamic treatment effects using GMM.
Credit assignment in Meta-reinforcement learning (Meta-RL) is still poorly understood. Existing methods either neglect credit assignment to pre-adaptation behavior or implement it naively. This leads to poor sample-efficiency during meta-training as well as ineffective task identification strategies. This paper provide…
This paper proposes a definition of system health in the context of multiple agents optimizing a joint reward function. We use this definition as a credit assignment term in a policy gradient algorithm to distinguish the contributions of individual agents to the global reward. The health-informed credit assignment is t…
Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging control tasks. However, these methods typically suffer from three core difficulties: temporal credit assignment with sparse rewards, lack of effective exploration, and brittle convergence properties that are extremely …
LICA learns credit assignment for cooperative agents without explicit formulation.
We present a model of credit card profitability, assuming that the card-holder always pays the full outstanding balance. The motivation for the model is to calculate an optimal credit limit, which requires an expression for the expected outstanding balance. We derive its Laplace transform, assuming that purchases are m…
Unified view on selective credit assignment for reinforcement learning.
We explain a persistent cost-of-carry spread in EUA market and suggest ECB policy change.
New method learns credit prices offline without interaction.
Optimizes loan recovery timing by forecasting cash flows.
This article examines arbitrage investment in a mispriced asset when the mispricing follows the Ornstein-Uhlenbeck process and a credit-constrained investor maximizes a generalization of the Kelly criterion. The optimal differentiable and threshold policies are derived. The optimal differentiable policy is linear with …
Assessment of risk levels for existing credit accounts is important to the implementation of bank policies and offering financial products. This paper uses cluster analysis of behaviour of credit card accounts to help assess credit risk level. Account behaviour is modelled parametrically and we then implement the behav…
With negative growth in real production in many countries and debt levels which become an increasing burden on developed societies, the calls for a change in economic policy and even the monetary system become louder and increasingly impatient. We research the consequences of a system of credit and debt, that still all…
Paper models transition risk using jump-diffusion model to price credit swaps.
Study examines factors influencing lending to SMEs by Kenyan banks.
Optimizes credit index option hedging with reinforcement learning.
We use a simple agent based model of value investors in financial markets to test three credit regulation policies. The first is the unregulated case, which only imposes limits on maximum leverage. The second is Basle II and the third is a hypothetical alternative in which banks perfectly hedge all of their leverage-in…
Improved GFlowNets learn more efficiently with trajectory balance.
This paper studies the optimal timing to liquidate credit derivatives in a general intensity-based credit risk model under stochastic interest rate. We incorporate the potential price discrepancy between the market and investors, which is characterized by risk-neutral valuation under different default risk premia speci…
Interbank lending and borrowing occur when financial institutions seek to settle and refinance their mutual positions over time and circumstances. This interactive process involves money creation at the aggregate level. Coordination mismatch on interbank credit may trigger systemic crises. This happened when, since sum…
Study assesses risks of European Safe Bonds using credit risk models.
Study uses RL to optimize credit card limits, achieving better results than traditional methods.
Designs a single policy for collecting data to train near-optimal policies.
Adapting policy learning for data collected from evolving systems.
Study finds implicit government guarantee improves municipal investment bond ratings.
We model a network economy with three sectors: downstream firms, upstream firms, and banks. Agents are linked by productive and credit relationships so that the behavior of one agent influences the behavior of the others through network connections. Credit interlinkages among agents are a source of bankruptcy diffusion…
Study finds public procurement awards, especially NGEU-funded ones, boost new lending.
New framework for modular reinforcement learning reduces sample complexity.
COCOA improves credit assignment in reinforcement learning by measuring contributions to rewards.
The paper proposes an iterative approach to batch reinforcement learning for safer and more informative data collection.
Optimizes loan recovery timing across various portfolios.
New method combines value function decomposition and policy gradients for cooperative multi-agent reinforcement learning.
Modeling business cycles via collective risk fluctuations in economic agents' risk space.
The Basel II internal ratings-based (IRB) approach to capital adequacy for credit risk plays an important role in protecting the Australian banking sector against insolvency. We outline the mathematical foundations of regulatory capital for credit risk, and extend the model specification of the IRB approach to a more g…
This paper proposes a new algorithm for learning guidance rewards in RL.
New guarantees for ERM with adaptively collected data.
The insufficient understanding of the credit network structure was recognized as a key factor for regulators' underestimation of the destructive systematic risk during the financial crisis that started in 2007. The existing credit network research either took a macro perspective to clarify the topological properties of…
We model the quantities appearing in Internal Revenue Service (IRS) tax guidance for calculating the health insurance premium tax credit created by the Patient Protection and Affordable Care Act, also called Obamacare. We ask the question of whether there is a procedure, computable by hand, which can calculate the appr…
Transforming sparse outcomes into dense process rewards for efficient reinforcement learning.
Optimal online data collection for semiparametric inference reduces regret.
Agents buy and sell services. All services are of equal quality. Buyers choose sellers at random. Monetary and fiscal policies are imposed by a central bank and a central government. Credit is supplied by a commercial banking system. Propensities to buy, sell, and lend depend on account balances, interest rates, tax ra…
Develops a method to efficiently use offline data for RL policy optimization.
Credit scoring plays a vital role in the field of consumer finance. Survival analysis provides an advanced solution to the credit-scoring problem by quantifying the probability of survival time. In order to deal with highly heterogeneous industrial data collected in Chinese market of consumer finance, we propose a nonp…
Client appraisal improves efficiency in microfinance banks in Adamawa State.
Presents SPEED, an algorithm for optimal policy evaluation in linear bandits with heteroscedastic noise.