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.
Proposes dynamic borrowing method for historical data in clinical trials.
This research investigated the potential for improving Peer-to-Peer (P2P) credit scoring by using "private information" about communications and travels of borrowers. We found that P2P borrowers' ego networks exhibit scale-free behavior driven by underlying preferential attachment mechanisms that connect borrowers in a…
Study quantifies information borrowing in hierarchical Bayesian models.
Paper uses BERT to assess P2P borrowers' credit risk from loan descriptions.
New DR-IC estimator reduces bias and variance in OPE.
Enhances early risk assessments for pediatric outcomes using contrastive learning.
Synthetic data improves credit scoring models' performance without compromising borrower privacy.
We propose an in-depth study of lending behaviors in Kiva using a mix of quantitative and large-scale data mining techniques. Kiva is a non-profit organization that offers an online platform to connect lenders with borrowers. Their site, kiva.org, allows citizens to microlend small amounts of money to entrepreneurs (bo…
Online Peer to Peer Lending (P2PL) systems connect lenders and borrowers directly, thereby making it convenient to borrow and lend money without intermediaries such as banks. Many recommendation systems have been developed for lenders to achieve higher interest rates and avoid defaulting loans. However, there has not b…
Study identifies two borrowing patterns in UK payday loan users.
Retail investors set interest rates for P2P loans based on borrower characteristics.
CONCERT improves transfer learning by borrowing partial information from auxiliary datasets.
Credit risk analysis improved with a joint model for spatial and temporal effects.
Shared Keyboard design improves phase I clinical trials by borrowing information across doses.
New methods improve subgroup analysis in trials with limited data.
This work examines the effects of allowing borrowing in betting-based hypothesis testing.
One of the key elements in the banking industry rely on the appropriate selection of customers. In order to manage credit risk, banks dedicate special efforts in order to classify customers according to their risk. The usual decision making process consists in gathering personal and financial information about the borr…
Study on optimal portfolio selection with varying borrowing and saving rates in continuous-time markets.
This paper studies the properties of the optimal portfolio-consumption strategies in a {finite horizon} robust utility maximization framework with different borrowing and lending rates. In particular, we allow for constraints on both investment and consumption strategies, and model uncertainty on both drift and volatil…
This paper provides a framework for modeling financial contagion in a network subject to fire sales and price impacts, but allowing for firms to borrow to cover their shortfall as well. We consider both uncollateralized and collateralized loans. The main results of this work are providing sufficient conditions for exis…
New algorithm borrows future randomness to stabilize model-free control.
Through a short sale, a person borrows a share of stock from a lender, sells the borrowed share to a third person at the current price, and purchases an identical share in the market at a future date and at a future price to replace the borrowed share of stock. This only makes sense if the short seller anticipates a do…
New TTP framework fuses control arms while controlling Type-I error.
We propose a simple model of inter-bank borrowing and lending where the evolution of the log-monetary reserves of banks is described by a system of diffusion processes coupled through their drifts in such a way that stability of the system depends on the rate of inter-bank borrowing and lending. Systemic risk is ch…
The paper examines smoothness of value function in consumption-investment models with borrowing constraints.
DeFi lending protocols faced challenges during Ethereum's merge, but avoided major liquidations.
Study optimal consumption and portfolio strategies with no-borrowing constraint in financial markets.
The study calculates securities lending haircuts and indemnification costs.
This article aims to explore an empirical approach to analyze the macroeconomicsdeterminants of default of borrowers. For this purpose, we have measured the impact of the adverse economic conditions on the degradation of the credit portfolio quality.In our paper, we have shed more light on the question of the aggravati…
Corrects technical error in change of measure for HTB models.
We develop a deep learning model of multi-period mortgage risk and use it to analyze an unprecedented dataset of origination and monthly performance records for over 120 million mortgages originated across the US between 1995 and 2014. Our estimators of term structures of conditional probabilities of prepayment, forecl…
We determine the optimal investment strategy of an individual who targets a given rate of consumption and who seeks to minimize the probability of going bankrupt before she dies, also known as {\it lifetime ruin}. We impose two types of borrowing constraints: First, we do not allow the individual to borrow money to inv…
Zero-Liquidation loans protect ETH borrowers from liquidation risks.
Interbank markets are fundamental for bank liquidity management. In this paper, we introduce a model of interbank trading with memory. Our model reproduces features of preferential trading patterns in the e-MID market recently empirically observed through the method of statistically validated networks. The memory mecha…
Alternative app data improves credit scoring for underserved borrowers.
This study measures liquidity risks in Aave, a blockchain lending protocol.
In this work we will develop a new approach to solve the non repayment problem in microfinance due to the problem of asymmetric information. This approach is based on modeling and simulation of ordinary differential systems where time remains a primordial component, they thus enable microfinance institutions to manage …
In this paper, we consider three problems related to survival, growth, and goal reaching maximization of an investment portfolio with proportional net cash flow. We solve the problems in a market constrained due to borrowing prohibition. To solve the problems, we first construct an auxiliary market and then apply the d…
We study the frictions in the patterns of trades in the Euro money market. We characterize the structure of lending relations during the period of recent financial turmoil. We use network-topology method on data from overnight transactions in the Electronic Market for Interbank Deposits (e-Mid) to investigate on two ma…
We propose a model of inter-bank lending and borrowing which takes into account clearing debt obligations. The evolution of log-monetary reserves of banks is described by coupled diffusions driven by controls with delay in their drifts. Banks are minimizing their finite-horizon objective functions which take into a…
We show that different rates should be used for borrowing and discount rates, and that the risk-free rate should be used for discounting when assessing and comparing the cost of energy accross diffferent producers and technologies, on the example of photovoltaics. Recent quantitative models using the same rate for borr…
Study uses FEM for HJB in option pricing with borrowing fees, improving accuracy and efficiency.
Model predicts loan default risk using dynamic multilayer graph neural networks.
In this paper we examine a formalization of feature distribution learning (FDL) in information-theoretic terms relying on the analytical approach and on the tools already used in the study of the information bottleneck (IB). It has been conjectured that the behavior of FDL algorithms could be expressed as an optimizati…
The study improves credit evaluation in peer-to-peer lending using machine learning.
Horseshoe priors improve small area estimation by borrowing strength globally but locally.
A stock loan is a loan, secured by a stock, which gives the borrower the right to redeem the stock at any time before or on the loan maturity. The way of dividends distribution has a significant effect on the pricing of the stock loan and the optimal redeeming strategy adopted by the borrower. We present the pricing mo…
Study loan contracts in DLPs using derivatives pricing and neural networks.