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Technical debt is a metaphor used to convey the idea that doing things in a "quick and dirty" way when designing and constructing a software leads to a situation where one incurs more and more deferred future expenses. Similarly to…

Software Engineering · Computer Science 2019-04-03 Alvine Boaye Belle

We consider a financial network represented at any time instance by a random liability graph which evolves over time. The agents connect through credit instruments borrowed from each other or through direct lending, and these create the…

Risk Management · Quantitative Finance 2022-12-23 Indrajit Saha , Veeraruna Kavitha

We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from…

General Finance · Quantitative Finance 2024-05-24 Jaehyung Choi

We study financial networks where banks are connected by debt contracts. We consider the operation of debt swapping when two creditor banks decide to exchange an incoming payment obligation, thus leading to a locally different network…

Risk Management · Quantitative Finance 2021-07-13 Pál András Papp , Roger Wattenhofer

Prepayment risk embedded in fixed-rate mortgages forms a significant fraction of a financial institution's exposure, and it receives particular attention because of the magnitude of the underlying market. The embedded prepayment option…

Computational Finance · Quantitative Finance 2024-10-29 Leonardo Perotti , Lech A. Grzelak , Cornelis W. Oosterlee

Market timing is an investment technique that tries to continuously switch investment into assets forecast to have better returns. What is the likelihood of having a successful market timing strategy? With an emphasis on modeling…

Portfolio Management · Quantitative Finance 2018-07-20 Guy Metcalfe

Volatility is the language in which finance often describes risk, but it is not the language in which institutions experience risk. Allocators live through drawdowns, liquidity needs, spending rules, rebalance decisions, board oversight,…

Portfolio Management · Quantitative Finance 2026-05-12 Gregory A. Fanous

We consider a financial market in which the risk-free rate of interest is modeled as a Markov diffusion. We suppose that home prices are set by a representative home-buyer, who can afford to pay only a fixed cash-flow per unit time for…

Mathematical Finance · Quantitative Finance 2022-03-17 Matthew Lorig , Natchanon Suaysom

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…

Statistical Finance · Quantitative Finance 2018-03-13 Justin Sirignano , Apaar Sadhwani , Kay Giesecke

We study the problem of asset liquidation in financial systems. During financial crises, asset liquidation is often inevitable but can lead to substantial losses if a significant amount of illiquid assets are sold simultaneously at…

Risk Management · Quantitative Finance 2026-03-18 Dohyun Ahn , Hongyi Jiang

We analyze the stability of financial investment networks, where financial institutions hold overlapping portfolios of assets. We consider the effect of portfolio diversification and heterogeneous investments using a random matrix dynamical…

Risk Management · Quantitative Finance 2025-02-03 Preben Forer , Barak Budnick , Pierpaolo Vivo , Sabrina Aufiero , Silvia Bartolucci , Fabio Caccioli

We build a state-of-the-art dynamic model of private asset allocation that considers five key features of private asset markets: (1) the illiquid nature of private assets, (2) timing lags between capital commitments, capital calls, and…

Portfolio Management · Quantitative Finance 2025-03-04 Hui Chen , Giovanni Gambarotta , Simon Scheidegger , Yu Xu

The estimate of a Multiperiod probability of default applied to residential mortgages can be obtained using the mean of the observed default, so called the Mean of ratios estimator, or aggregating the default and the issued mortgages and…

Applications · Statistics 2014-09-18 Matteo Formenti

We develop a finite horizon continuous time market model, where risk averse investors maximize utility from terminal wealth by dynamically investing in a risk-free money market account, a stock written on a default-free dividend process,…

Pricing of Securities · Quantitative Finance 2011-12-23 Agostino Capponi , Martin Larsson

This paper considers the problem of measuring the credit risk in portfolios of loans, bonds, and other instruments subject to possible default under multi-factor models. Due to the amount of the portfolio, the heterogeneous effect of…

Computational Finance · Quantitative Finance 2019-04-10 Cheng-Der Fuh , Chuan-Ju Wang

In this paper, we propose a method that provides a useful technique to compare relationship between risks involved that takes customer become defaulter and debt collection process that might make this defaulter recovered. Through estimation…

Applications · Statistics 2014-08-20 Mauro R. Oliveira , Francisco Louzada

We postulates, and then show experimentally, that liquidity deficit is the driving force of the markets. In the first part of the paper a kinematic of liquidity deficit is developed. The calculus-like approach, which is based on…

Computational Finance · Quantitative Finance 2016-12-07 Vladislav Gennadievich Malyshkin , Ray Bakhramov

Smart beta, also known as strategic beta or factor investing, is the idea of selecting an investment portfolio in a simple rule-based manner that systematically captures market inefficiencies, thereby enhancing risk-adjusted returns above…

Portfolio Management · Quantitative Finance 2018-08-13 Phil Maguire , Karl Moffett , Rebecca Maguire

In the frictionless discrete time financial market of Bouchard et al.(2015) we consider a trader who, due to regulatory requirements or internal risk management reasons, is required to hedge a claim $\xi$ in a risk-conservative way relative…

Mathematical Finance · Quantitative Finance 2019-02-19 Laurence Carassus , Jan Obloj , Johannes Wiesel

As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these…

Machine Learning · Computer Science 2023-10-12 Martin Pawelczyk , Teresa Datta , Johannes van-den-Heuvel , Gjergji Kasneci , Himabindu Lakkaraju