Computable contracts simplify financial transactions and reduce legal costs.
problem Difficulty in querying, executing, and analyzing text-based financial contracts.
method Develop a Contract Definition Language and illustrate use cases.
result Substantial improvements in customer experience and cost reduction.
Optimal execution strategy for merger & acquisition contracts with price impact.
problem Optimal execution and pricing of financial derivatives in M&A deals.
method Indifference utility arguments, considering linear and nonlinear contracts.
result Linear contracts are more expensive and vulnerable to manipulation.
This paper explores how insurance contracts can be traded in financial markets.
problem The exclusion of arbitrage in insurance contracts due to their non-tradability.
method Defining strategies on insurance portfolios and combining them with financial trading strategies.
result The existence of an insurance-finance-consistent probability, leading to the expected discounted cash-flows.
In this note we describe the application of existing smart contract technologies with the aim to construct a new digital representation of a financial derivative contract. We compare several existing DLT based technologies. We provide a detailed description of two separate prototypes which are able to be executed on a …
The paper explores perpetual contracts in a financial market without arbitrage.
problem Modeling perpetual contracts in a continuous-time financial market.
method Derive model-free and semi-robust expressions for perpetual contracts' funding and discount rates.
result Explicit replication strategies for perpetual contracts are derived, relating them to traditional financial instruments.
The research presented in this work is motivated by some recent papers regarding hedging and valuation of financial securities subject to funding costs, collateralization and counterparty credit risk. Our goal is to provide a sound theoretical underpinning for some results presented in these papers by developing a unif…
Graph learning categorizes DeFi services into similar functionalities.
problem Identifying similar financial services in decentralized finance protocols.
method Graph representation learning (GRL) to categorize smart contract blocks into clusters.
result Purity of clustering reaches .888 in the best-case scenario.
Paper improves ISDA margin calculation using LSMC.
problem Efficiently calculating initial margin for financial contracts.
method Extends Least Squares Monte-Carlo (LSMC) technique.
result Improved efficiency in estimating margin sensitivities.
A financial contract's value is determined by a quantum measurement outcome, and a pricing state exists to value it.
problem Valuing financial contracts contingent on quantum measurement outcomes.
method Proving the existence of a pricing state equivalent to the physical state on null spaces, and solving optimization problems for optimal contract payouts.
result There exists a pricing state equivalent to the physical state on null spaces, leading to a pricing function for financial contracts.
The main purpose of this paper is to formalize the modelling process, analysis and mathematical definition of corruption when entering into a contract between principal agent and producers. The formulation of the problem and the definition of concepts for the general case are considered. For definiteness, all calculati…
Study loan contracts in DLPs using derivatives pricing and neural networks.
problem Optimizing and hedging risks in decentralized lending contracts.
method Derivatives pricing theory, deep neural networks, and statistical arbitrage.
result Developed a method to hedge risks in lending contracts and exploit arbitrage opportunities.
Quantum crypto-economics models price risks in blockchain technology.
problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.
Study financial contracts pricing in markets with nonproportional costs and constraints.
problem Financial contract pricing in markets with nonproportional transaction costs and portfolio constraints.
method Direct and dual characterization of market-consistent prices with acceptable risk thresholds.
result Extension of the Fundamental Theorem of Asset Pricing to include good deals and scalable good deals.
Model clarifies network effects on CVA, revealing significant differences in derivative contract values.
problem Network effects on CVA in financial contracts.
method Developed a model to analyze default probabilities in a network of contracts.
result Network effects can significantly alter CVA values, leading to multi-modal distributions.
Deep reinforcement learning improves trading performance in financial markets.
problem Improving trading performance in financial markets.
method Deep Q-network (DQN) for designing long-short trading strategies.
result Trained reinforcement learning agent outperformed an index benchmark in trading E-mini S&P 500 futures contracts.
The paper explores local-correlation models for pricing complex financial contracts.
problem Calibrating synthetic quanto forward contracts and composite options.
method Design on-line calibration procedures for local and stochastic volatility models.
result Calibration performance of local-correlation models compared to simpler approximations.
We introduce a two-agent problem which is inspired by price asymmetry arising from funding difference. When two parties have different funding rates, the two parties deduce different fair prices for derivative contracts even under the same pricing methodology and parameters. Thus, the two parties should enter the deriv…
SFC aims to protect the Amazon with a digital currency and smart contracts.
problem Protecting the Amazon's ecosystem and ensuring resource credibility.
method Blockchain, digital contracts, smart contracts with oracles.
result Ensures credibility and security for financial resources invested in Amazon projects.
TradeMech nets trades without changing counterparty relationships.
problem Netting trades without altering counterparty exposure in complex financial networks.
method Transforms contracts into chains and cycles, nets designated object multilaterally, and replaces contracts with new multiparty agreements.
result Maximal multilateral netting of a designated object while preserving each agent's profit and counterparty risk.
The paper develops a valuation framework for GLWB-LTC contracts with Levy dynamics and stochastic interest rates.
problem Valuation of GLWB-LTC contracts with financial guarantees, longevity protection, and health-contingent LTC payments.
method Coupling a recombining Hull-White trinomial tree with an IMEX finite difference scheme, incorporating a seven-state health model.
result Hybrid tree-IMEX method delivers stable long-maturity prices consistent with simulation benchmarks.
Swapping debt contracts can mitigate risk in financial networks.
problem Mitigating risk in financial networks through debt swaps.
method Analysis of debt swapping operations in financial networks under various conditions.
result Positive debt swaps can exist in worst-case shock models to minimize losses.
This paper investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex-post variation in asset prices as well as option-implied volatility. We work in the flexible quantile regression framework and rely on recently developed model-free measures of int…
We introduce a class of financial contracts involving several parties by extending the notion of a two-person game option (see Kifer (2000)) to a contract in which an arbitrary number of parties is involved and each of them is allowed to make a wide array of decisions at any time, not restricted to simply `exercising t…
Bailouts in financial networks are hard to optimize due to NP-hardness.
problem Optimizing bailouts in a network of insolvent banks.
method Modeling bailouts as an optimization problem, proving NP-hardness and inapproximability.
result Banks can strategically alter debt contracts to increase their market value in the event of a bailout.
Proposes a probabilistic framework for smart contract risk quantification.
problem Quantifying financial risk of smart contract cyber attacks and failures.
method Probabilistic graph-theoretical framework using bond percolation models.
result Analytical results and numerical examples for aggregate loss distribution.
In this paper we investigate the local risk-minimization approach for a combined financial-insurance model where there are restrictions on the information available to the insurance company. In particular we assume that, at any time, the insurance company may observe the number of deaths from a specific portfolio of in…
The research presented in this work is motivated by recent papers by Brigo et al. (2011), Burgard and Kjaer (2009), Crépey (2012), Fujii and Takahashi (2010), Piterbarg (2010) and Pallavicini et al. (2012). Our goal is to provide a sound theoretical underpinning for some results presented in these papers by developing …
Paper presents a risk management framework for blockchain protocols.
problem Blockchain protocol risks affecting DLT and digital assets.
method Developed a comprehensive risk management framework using traditional taxonomy.
result Structured approach to identify, measure, monitor and report blockchain protocol risks.
Bounds derived for contract values in life insurance with financial market interaction.
problem Incompleteness in life tables for modern insurance products.
method Derivation of upper and lower bounds for hybrid functionals of lifetime under different assumptions.
result Characterization of worst- and best-case contract values over compatible mortality processes.
New MKABSDEs help calculate initial margins in financial contracts.
problem Calculating initial margins in financial contracts with dependencies.
method Introduced MKABSDEs, provided existence and uniqueness, applied to CVaR, used deterministic and Monte-Carlo methods for numerical approximations.
result MKABSDEs provide a new way to solve for initial margins in financial contracts.
We study insolvency cascades in an interbank system when banks are allowed to insure their loans with credit default swaps (CDS) sold by other banks. We show that, by properly shifting financial exposures from one institution to another, a CDS market can be designed to rewire the network of interbank exposures in a way…
It is suggested to consider long term trends of financial markets as a growth phenomenon. The question that is asked is what conditions are needed for a long term sustainable growth or contraction in a financial market? The paper discuss the role of traditional market players of long only mutual funds versus hedge fund…
The paper prices and replicates various financial contracts on a risky asset with stochastic volatility and jumps.
problem Pricing and replicating financial contracts on assets with stochastic volatility and jumps.
method Develops pricing and hedging formulas for various financial contracts, independent of the volatility process dynamics.
result Pricing and hedging formulas for financial contracts are derived without dependence on the volatility process dynamics.
Game theory applied to financial networks, focusing on debt repayment strategies.
problem Understanding financial stability in interconnected systems.
method Modeling financial systems as networks, analyzing utility-maximizing strategies under priority-proportional payments.
result Existence and uniqueness of payment profiles are not guaranteed, even under fixed strategies.
We consider a market model that consists of financial investors and producers of a commodity. Producers optionally store some production for future sale and go short on forward contracts to hedge the uncertainty of the future commodity price. Financial investors take positions in these contracts in order to diversify t…
The article reviews how to set stochastic volatility model parameters.
problem Choosing parameters for stochastic volatility models.
method Examines existing literature on various methods.
result Different approaches to setting stochastic volatility parameters.
The guaranteed minimum withdrawal benefit (GMWB) rider, as an add on to a variable annuity (VA), guarantees the return of premiums in the form of peri- odic withdrawals while allowing policyholders to participate fully in any market gains. GMWB riders represent an embedded option on the account value with a fee structu…
The 2008 financial crisis has been attributed to "excessive complexity" of the financial system due to financial innovation. We employ computational complexity theory to make this notion precise. Specifically, we consider the problem of clearing a financial network after a shock. Prior work has shown that when banks ca…
The paper compares machine learning methods with traditional techniques for pricing and sensitivities of financial products with path-dependent structures.
problem Evaluating financial products with early-termination clauses, especially those with path-dependent structures.
method The paper compares regression methods including randomized recurrent and feed-forward neural networks, and a novel approach using signatures of the underlying price process, with traditional polynomial basis functions for pricing and sensitivities.
result Machine learning algorithms often match the accuracy and efficiency of traditional methods for Asian and look-back options, while randomized neural networks are best for callable certificates.
This paper explores how decentralized finance mitigates traditional finance's shortcomings.
problem Lack of transparency and moral hazard in centralized finance.
method Analysis of smart contracts and decentralized governance in DeFi.
result DeFi mitigates traditional finance's shortcomings through decentralized governance and smart contracts.
We propose an algorithm for the non-negative factorization of an occurrence tensor built from heterogeneous networks. We use l0 norm to model sparse errors over discrete values (occurrences), and use decomposed factors to model the embedded groups of nodes. An efficient splitting method is developed to optimize the non…
Algorithmic insurance tackles financial risks from AI errors, proving CVaR-optimal thresholds reduce tail risk.
problem High-stakes AI errors lead to heterogeneous losses, challenging traditional insurance assumptions.
method Analyzed binary classification performance to tail risk exposure, using CVaR to quantify extreme losses.
result CVaR-optimal thresholds reduce tail risk up to 13-fold compared to accuracy maximization.
This paper argues that the fundamental principle of contemporary financial economics is balanced reciprocity, not the principle of utility maximisation that is important in economics more generally. The argument is developed by analysing the mathematical Fundamental Theory of Asset Pricing with reference to the emergen…
Monte Carlo Tree Search improves financial derivative hedging efficiency.
problem Optimizing pricing and hedging of derivative contracts in incomplete markets.
method Integrates tree search techniques with Reinforcement Learning for optimal control problems.
result Monte Carlo Tree Search outperforms Q-learning in sample efficiency and learning speed. Data science detects Ethereum honeypots using transaction behavior.
problem Detecting and identifying new Ethereum honeypots.
method Data science approach based on transaction behavior features.
result Data science approach detects new and previously unknown honeypots.
This paper studies a valuation framework for financial contracts subject to reference and counterparty default risks with collateralization requirement. We propose a fixed point approach to analyze the mark-to-market contract value with counterparty risk provision, and show that it is a unique bounded and continuous fi…
Study analyzes smart contract adoption under bounded risk, showing stable adoption but fragile financial outcomes.
problem Understanding smart contract adoption in derivative markets under risk constraints.
method Structural theory linked with simulation and real-world validation.
result Adoption intensity is stable but profitability and service outcomes are sensitive to volatility.
Financial networks reveal systemic risk, suggesting new regulatory strategies.
problem Global financial interconnectedness and inadequacy of traditional risk models.
method Network-based models of financial systems to understand contagion and risk.
result Financial networks exhibit 'robust-yet-fragile' properties, informing cost-effective regulation.