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Register a new userFunding Liquidity, Debt Tenor Structure, and Creditors Belief: An Exogenous Dynamic Debt Run Model
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We propose a unified structural credit risk model incorporating both insolvency and illiquidity risks, in order to investigate how a firms default probability depends on the liquidity risk associated with its financing structure. We assume the firm finances its risky assets by mainly issuing short- and long-term debt. Short-term debt can have either a discrete or a more realistic staggered tenor structure. At rollover dates of short-term debt, creditors face a dynamic coordination problem. We show that a unique threshold strategy (i.e., a debt run barrier) exists for short-term creditors to decide when to withdraw their funding, and this strategy is closely related to the solution of a non-standard optimal stopping time problem with control constraints. We decompose the total credit risk into an insolvency component and an illiquidity component based on such an endogenous debt run barrier together with an exogenous insolvency barrier.
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This paper considers an optimal control of a big financial company with debt liability under bankrupt probability constraints. The company, which faces constant liability payments and has choices to choose various production/business policies from an available set of control policies with different expected profits and risks, controls the business policy and dividend payout process to maximize the expected present value of the dividends until the time of bankruptcy. However, if the dividend payout barrier is too low to be acceptable, it may result in the companys bankruptcy soon. In order to protect the shareholders profits, the managements of the company impose a reasonable and normal constraint on their dividend strategy, that is, the bankrupt probability associated with the optimal dividend payout barrier should be smaller than a given risk level within a fixed time horizon. This paper aims at working out the optimal control policy as well as optimal return function for the company under bankrupt probability constraint by stochastic analysis, PDE methods and variational inequality approach. Moreover, we establish a risk-based capital standard to ensure the capital requirement of can cover the total given risk by numerical analysis and give reasonable economic interpretation for the results.
JUBILEE is a securely computed mechanism for debt relief and forgiveness in a frictionless manner without involving trusted third parties, leading to more harmonious debt settlements by incentivising the parties to truthfully reveal their private information. JUBILEE improves over all previous methods: - individually rational, incentive-compatible, truthful/strategy-proof, ex-post efficient, optimal mechanism for debt relief and forgiveness with private information - by the novel introduction of secure computation techniques to debt relief, the blessing of the debtor is hereby granted for the first time: debt settlements with higher expected profits and a higher probability of success than without using secure computation A simple and practical implementation is included for The Secure Spreadsheet. Another implementation is realised using Raziel smart contracts on a blockchain with Pravuil consensus.
We provide a UTXO model of blockchain transactions that is able to represent both credit and debt on the same blockchain. Ordinarily, the UTXO model is solely used to represent credit and the representation of credit and debit together is achieved using the account model because of its support for balances. However, the UTXO model provides superior privacy, safety, and scalability when compared to the account model. In this work, we introduce a UTXO model that has the flexibility of balances with the usual benefits of the UTXO model. This model extends the conventional UTXO model, which represents credits as unmatched outputs, by representing debts as unmatched inputs. We apply our model to solving the problem of transparency in reverse mortgage markets, in which some transparency is necessary for a healthy market but complete transparency leads to adverse outcomes. Here the pseudonymous properties of the UTXO model protect the privacy of loan recipients while still allowing an aggregate view of the loan market. We present a prototype of our implementation in Tendermint and discuss the design and its benefits.
Technical Debt is a metaphor used to describe the situation in which long-term code quality is traded for short-term goals in software projects. In recent years, the concept of self-admitted technical debt (SATD) was proposed, which focuses on debt that is intentionally introduced and described by developers. Although prior work has made important observations about admitted technical debt in source code, little is known about SATD in build systems. In this paper, we coin the term Self-Admitted Build Debt (SABD) and through a qualitative analysis of 500 SABD comments in the Maven build system of 300 projects, we characterize SABD by location and rationale (reason and purpose). Our results show that limitations in tools and libraries, and complexities of dependency management are the most frequent causes, accounting for 49% and 23% of the comments. We also find that developers often document SABD as issues to be fixed later. To automate the detection of SABD rationale, we train classifiers to label comments according to the surrounding document content. The classifier performance is promising, achieving an F1-score of 0.67-0.75. Finally, within 16 identified ready-to-be-addressed SABD instances, the three SABD submitted by pull requests and the five SABD submitted by issue reports were resolved after developers were made aware. Our work presents the first step towards understanding technical debt in build systems and opens up avenues for future work, such as tool support to track and manage SABD backlogs.
Expanding on techniques of concentration of measure, we develop a quantitative framework for modeling liquidity risk using convex risk measures. The fundamental objects of study are curves of the form $(rho(lambda X))_{lambda ge 0}$, where $rho$ is a convex risk measure and $X$ a random variable, and we call such a curve a emph{liquidity risk profile}. The shape of a liquidity risk profile is intimately linked with the tail behavior of the underlying $X$ for some notable classes of risk measures, namely shortfall risk measures. We exploit this link to systematically bound liquidity risk profiles from above by other real functions $gamma$, deriving tractable necessary and sufficient conditions for emph{concentration inequalities} of the form $rho(lambda X) le gamma(lambda)$, for all $lambda ge 0$. These concentration inequalities admit useful dual representations related to transport inequalities, and this leads to efficient uniform bounds for liquidity risk profiles for large classes of $X$. On the other hand, some modest new mathematical results emerge from this analysis, including a new characterization of some classical transport-entropy inequalities. Lastly, the analysis is deepened by means of a surprising connection between time consistency properties of law invariant risk measures and the tensorization of concentration inequalities.
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