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相关论文: Minimizing the Repayment Cost of Federal Student L…

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Student loans occupy a significant portion of the federal budget, as well as, the largest financial burden in terms of debt for graduates. This paper explores data-driven approaches towards understanding the repayment of such loans. Using…

应用统计 · 统计学 2018-05-07 Bin Luo , Qi Zhang , Somya D. Mohanty

An alternative to the dependence on traditional student loans may offer a viable relief from the tremendous burden that those loans usually incur. This article establishes that it is desirable for governmental intervention to grant students…

理论经济学 · 经济学 2024-11-11 Limor Hatsor , Ronen Bar-El

A principal with cheap capital optimally forces her counterparty to borrow at above-market rates. The reason: the form of finance is a screening device. Advances provide liquidity but pool types; contingent transfers separate types, but,…

理论经济学 · 经济学 2026-04-09 Rui Sun

This literature review elucidates the implications of behavioral biases, particularly those stemming from overconfidence and framing, on the intertemporal choices made by students on their underline demand preferences for student loans. A…

综合经济学 · 经济学 2023-10-04 Praful Raj

The Consumer Financial Protection Bureau defines the notion of payoff amount as the amount that has to be payed at a particular time in order to completely pay off the debt, in case the lender intends to pay off the loan early, way before…

数理金融 · 定量金融 2023-07-03 Fausto Di Biase , Stefano Di Rocco , Alessandra Ortolano , Maurizio Parton

Receivable financing is the process whereby cash is advanced to firms against receivables their customers have yet to pay: a receivable can be sold to a funder, which immediately gives the firm cash in return for a small percentage of the…

数据结构与算法 · 计算机科学 2020-06-25 Ilaria Bordino , Francesco Gullo , Giacomo Legnaro

With the deepening of the digitization degree of financial business, financial fraud presents more complex and hidden characteristics, which poses a severe challenge to the risk prevention and control ability of financial institutions. At…

计算工程、金融与科学 · 计算机科学 2024-05-08 Xinye Sha

Federated learning (FL) is a privacy-preserving learning technique that enables distributed computing devices to train shared learning models across data silos collaboratively. Existing FL works mostly focus on designing advanced FL…

机器学习 · 计算机科学 2023-02-20 Yash Travadi , Le Peng , Xuan Bi , Ju Sun , Mochen Yang

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…

证券定价 · 定量金融 2022-01-07 Min Dai , Zuo Quan Xu

Online lending, a phenomenon which is becoming mainstream due to the migration of consumer finance to the Internet and the adoption of AI based lending models, is an example of learning by doing. This paper studies optimal policies for a…

理论经济学 · 经济学 2025-11-18 Mendelson Haim , Zhu Mingxi

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…

最优化与控制 · 数学 2008-12-02 Erhan Bayraktar , Virginia R. Young

Federated learning (FL) is a distributed learning technique that trains a shared model over distributed data in a privacy-preserving manner. Unfortunately, FL's performance degrades when there is (i) variability in client characteristics in…

机器学习 · 计算机科学 2021-10-28 Muhammad Tahir Munir , Muhammad Mustansar Saeed , Mahad Ali , Zafar Ayyub Qazi , Ihsan Ayyub Qazi

A principal selects a team of agents for collaborating on a joint project. The principal aims to design a revenue-optimal contract that incentivize the team of agents to exert costly effort while satisfying fairness constraints. We show…

计算机科学与博弈论 · 计算机科学 2025-12-23 Matteo Castiglioni , Junjie Chen , Yingkai Li

This paper works out fair values of stock loan model with automatic termination clause, cap and margin. This stock loan is treated as a generalized perpetual American option with possibly negative interest rate and some constraints. Since…

证券定价 · 定量金融 2015-03-17 Shuqing Jiang , Zongxia Liang , Weiming Wu

We analyze recently proposed mortgage contracts that aim to eliminate selective borrower default when the loan balance exceeds the house price (the ``underwater'' effect). We show contracts that automatically reduce the outstanding balance…

证券定价 · 定量金融 2022-06-01 Yerkin Kitapbayev , Scott Robertson

Federated Learning is an emerging distributed collaborative learning paradigm used by many of applications nowadays. The effectiveness of federated learning relies on clients' collective efforts and their willingness to contribute local…

计算机科学与博弈论 · 计算机科学 2022-05-24 Shuyu Kong , You Li , Hai Zhou

We study the incentives of banks in a financial network, where the network consists of debt contracts and credit default swaps (CDSs) between banks. One of the most important questions in such a system is the problem of deciding which of…

风险管理 · 定量金融 2020-02-19 Pál András Papp , Roger Wattenhofer

Debt recycling is an aggressive equity extraction strategy that potentially permits faster repayment of a mortgage. While equity progressively builds up as the mortgage is repaid monthly, mortgage holders may obtain another loan they could…

风险管理 · 定量金融 2025-01-28 Sabrina Aufiero , Preben Forer , Pierpaolo Vivo , Fabio Caccioli , Silvia Bartolucci

A mean-reverting financial instrument is optimally traded by buying it when it is sufficiently below the estimated `mean level' and selling it when it is above. In the presence of linear transaction costs, a large amount of value is paid…

交易与市场微观结构 · 定量金融 2011-03-28 Richard Martin , Torsten Schöneborn

Federated learning (FL) is a distributed learning paradigm that enables a large number of devices to collaboratively learn a model without sharing their raw data. Despite its practical efficiency and effectiveness, the iterative on-device…

机器学习 · 计算机科学 2020-12-16 Bing Luo , Xiang Li , Shiqiang Wang , Jianwei Huang , Leandros Tassiulas
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