Geometric arbitrage theory uses quantum mechanics to model market dynamics and arbitrage opportunities.
problem Modeling and managing arbitrage opportunities in financial markets.
method Quantum mechanical approach to geometric arbitrage theory, solving the Schroedinger equation.
result Results from quantum mechanics align with classical stochastic models, providing consistency.
New method finds better arbitrage opportunities in AMMs.
problem Finding optimal arbitrage trades in multi-token AMMs.
method Closed-form solutions using convex optimisation.
result Better arbitrage opportunities than traditional methods.
New techniques exploit market systems to manipulate prices.
problem Market manipulation through technical details and glitches.
method Analyzed and modeled market manipulation techniques and proposed mitigation measures.
result Technical solutions can significantly thwart market manipulation.
Blockchain MEV is unaffected by ordering changes.
problem Maximizing arbitrage opportunities on blockchain exchanges.
method Formalized MEV, proved invariance under certain conditions.
result Maximal extractable value is invariant under changes in ordering mechanism.
The paper extends collective arbitrage concepts to multi-agent markets with cooperation.
problem Understanding collective market completeness and pricing in multi-agent systems.
method Develops new techniques and theorems to establish collective pricing-hedging duality and collective replication.
result Established a Second Fundamental Theorem of Asset Pricing in cooperative multi-agent settings.
We formalize how markets aggregate via arbitrage and quantify liquidity loss.
problem How financial markets aggregate and the loss of liquidity.
method Characterize markets via utility functions, use thermodynamics analogy, derive limit order book representation, compute aggregation loss.
result Arbitrage-mediated aggregation leads to market-dynamical entropy quantifying liquidity loss.
The objective of this paper is to provide a comprehensive study no-arbitrage pricing of financial derivatives in the presence of funding costs, the counterparty credit risk and market frictions affecting the trading mechanism, such as collateralization and capital requirements. To achieve our goals, we extend in severa…
FluxLayer solves cross-chain liquidity fragmentation for better MEV capture.
problem Cross-chain fragmented liquidity and MEV optimization.
method Three-layer framework integrating settlement, intent, and leverage mechanisms.
result FluxLayer enhances cross-chain MEV by capturing more arbitrage opportunities.
Blockchain-based exchanges adopt based on token pair volatility and personal use.
problem Token value loss and arbitrage issues in decentralized exchanges.
method Investigation of Automated Market Makers (AMMs) using transaction-level data.
result AMMs are adopted for high personal use or highly correlated token price movements.
Automatically balances blockchain network resources to boost market efficiency.
problem Extractable value leakage and execution frictions in blockchain networks.
method Systematically uses idle network resources for arbitrage, incentivizing transactions.
result Reduces network inventory risk while enhancing price formation and liquidity.
This paper studies how AMMs can minimize losses from arbitrage while retaining uninformed trading activity.
problem Minimizing losses from arbitrage in AMMs while retaining uninformed trading activity.
method Modeling arbitrage dynamics and sensitivity to fee choices, mapping to a random walk with a reward scheme.
result AMMs can maximize value retention by optimizing fee structures.
PDLPs reduce borrowing costs for perpetual futures traders.
problem High capital costs for market makers and traders in decentralized settings.
method Formalize PDLPs and target weight mechanisms, describe pool arbitrage and expected payoffs.
result PDLPs are easy to delta hedge, improving capital efficiency.
Study examines how arbitrage between ETF and futures affects market liquidity during crashes.
problem Impact of arbitrage between leveraged ETF and futures on market liquidity during market crashes.
method Artificial market simulations to investigate liquidity changes in L-ETF and futures markets.
result Arbitrage trading affects liquidity supply from one market to another during market crashes.
The method constructs arbitrage-free option surfaces from noisy quotes using Chebyshev bases and a fog post-fit layer.
problem Constructing arbitrage-free option price surfaces from noisy bid-ask quotes.
method Chebyshev tensor bases, linear sampling, no-arbitrage operators, quadratic objective, OSQP solvers, fog post-fit layer, Hamiltonian energy.
result High inside-spread coverage (98-99%) and low no-arbitrage violations (below 1%) in stable periods, controlled leakage in stressed periods.
We derive integral tests for the existence and absence of arbitrage in a financial market with one risky asset which is either modeled as stochastic exponential of an Ito process or a positive diffusion with Markov switching. In particular, we derive conditions for the existence of the minimal martingale measure. We al…
Quantum probability theory constructs Martingales for non-Brownian financial models.
problem Constructing Martingales for financial models using fractional Brownian motion.
method Quantum probability theory and Wick product.
result Quantum probability framework allows for Martingale construction without Brownian integrals.
Develops a mathematical model for CLMM dynamics in DeFi.
problem Analyzing CLMMs in continuous time trading.
method Modeling CLMM dynamics as measure-valued processes, examining three arbitrage models.
result Trading fees limit admissible price processes, impacting CLMM design.
Study examines how crypto arbitrage affects XRP price and network correlation.
problem Impact of crypto arbitrage on XRP price and network correlation.
method Examined XRP price fluctuations and correlation tensor spectra of transaction networks across crypto exchanges.
result Arbitrage opportunities across crypto exchanges anti-correlate with XRP price during bubble periods.
This study examines fees in AMMs to reduce losses from informed orderflow.
problem Minimizing losses from informed orderflow in AMMs.
method Modeling arbitrage dynamics and sensitivity to fee choices.
result Identified fees that mimic price directionality to reduce losses.
The notion that economies should normally be in equilibrium is by now well-established; equally well-established is that economies are almost never precisely in equilibrium. Using a very general formulation, we show that under dynamics that are second-order in time a price system can remain away from equilibrium with p…
Dynamic-weight AMMs outperform traditional CEX rebalancing in tokenized funds, especially on L2s.
problem Improving asset allocation efficiency in decentralized finance (DeFi) protocols.
method Block-level arbitrage analysis and long-term performance benchmarks on two live pools.
result Dynamic-weight AMMs can achieve performance comparable to or better than traditional CEX rebalancing, especially on Layer 2 (L2) networks.
This paper uses DRL for long-short portfolio optimization, improving risk-adjusted returns.
problem Traditional portfolio optimization limits diversification by excluding short-selling.
method Developed a DRL framework with a short-selling mechanism for continuous trading.
result DRL model with short-selling achieves superior risk-adjusted returns.
We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. …
Optimal fees for G3Ms align LP value with market accuracy.
problem Optimal fees for G3Ms to attract liquidity without sacrificing accuracy.
method Developed a framework for determining LP value with fees for G3Ms under diffusion.
result LPs prefer G3Ms over other strategies as fees approach zero.
This study presents an agent-based computational cross-market model for Chinese equity market structure, which includes both stocks and CSI 300 index futures. In this model, we design several stocks and one index futures to simulate this structure. This model allows heterogeneous investors to make investment decisions …
New algorithm finds more arbitrage opportunities in DEXs.
problem Detecting arbitrage loops and non-loops in decentralized exchanges.
method Combining line graph and modified Moore-Bellman-Ford algorithm.
result Found more arbitrage loops and non-loops compared to existing methods.
Established a relation between short-term and long-term arbitrage measures.
problem Non-equilibrium effects in financial markets.
method Geometric Arbitrage Theory and Stochastic Portfolio Theory.
result A connection between short-term and long-term arbitrage measures.
This paper introduces strategies to maximize arbitrage profits in decentralized exchanges.
problem Maximizing profits from arbitrage loops in decentralized exchanges.
method Three strategies: MaxPrice, MaxMax, and Convex Optimization.
result The Convex Optimization strategy yields the highest monetized arbitrage profit in theory and practice.
This paper addresses AMMs for expiring assets, ensuring liquidity and risk management.
problem AMMs struggle with assets that expire, leading to liquidity issues and risk exposure.
method Combines AMM and limit-order book features, ensuring liveness and dynamic price adjustment.
result A DEX for expiring assets maintains liquidity and risk management.
Study upper hedging prices for contingent claims in models with various types of arbitrage.
problem Valuation of contingent claims in market models with different types of arbitrage.
method Analysis of market models with increasing profit, strong arbitrage, and arbitrage of the first kind.
result Option prices are reduced when increasing profit is present, and corporate stock price processes can be derived from issuance and repurchase plans.
We characterize the collective phenomena of a liquid market. By interpreting the behavior of a no-arbitrage N asset market in terms of a particle system scenario, (thermo)dynamical-like properties can be extracted from the asset kinetics. In this scheme the mechanisms of the particle interaction can be widely investiga…
The paper explores arbitrage in financial markets under uncertainty using Wasserstein distance.
problem Investigating arbitrage in financial markets with distributional uncertainty.
method Using Wasserstein distance, the paper considers weak and strong forms of arbitrage conditions and introduces a relaxation called statistical arbitrage.
result The paper derives dual formulations of robust arbitrage conditions and conducts computational experiments to answer questions about ambiguity and statistical arbitrage.
The paper investigates cyclic arbitrage opportunities in decentralized exchanges.
problem Price discrepancies in decentralized exchanges lead to arbitrage opportunities.
method Theoretical framework and analysis of transaction-level data.
result Traders have executed over 292,606 cyclic arbitrages over eleven months, exploiting more than 138 million USD in revenue.
This note develops an arbitrage theory for a discrete-time market model without the assumption of the existence of a numéraire asset. Fundamental theorems of asset pricing are stated and proven in this context. The distinction between the notions of investment-consumption arbitrage and pure-investment arbitrage provide…
We construct and study market models admitting optimal arbitrage. We say that a model admits optimal arbitrage if it is possible, in a zero-interest rate setting, starting with an initial wealth of 1 and using only positive portfolios, to superreplicate a constant c>1. The optimal arbitrage strategy is the strategy for…
We generalize the Arbitrage Pricing Theory (APT) to include the contribution of virtual arbitrage opportunities. We model the arbitrage return by a stochastic process. The latter is incorporated in the APT framework to calculate the correction to the APT due to the virtual arbitrage opportunities. The resulting relatio…
We first review empirical evidence that asset prices have had episodes of large fluctuations and been inefficient for at least 200 years. We briefly review recent theoretical results as well as the neurological basis of trend following and finally argue that these asset price properties can be attributed to two fundame…
No-arbitrage constraints on implied variance slope are weak, leading to almost guaranteed arbitrage in many cases.
problem Weak constraints on implied variance slope in the Black-Scholes model lead to arbitrage opportunities.
method Analysis of constraints on implied variance slope and their implications for arbitrage.
result Arbitrage is almost always guaranteed in a wide range of slope values where constraints are enforced.
We refute Taleb's claim that election forecasts are arbitrage-violating.
problem The validity of probabilistic election forecasts using no-arbitrage pricing techniques.
method We use mild assumptions to show all forecasts are arbitrage-free.
result Taleb's heuristic for evaluating forecasts is incorrect.
We have embedded the classical theory of stochastic finance into a differential geometric framework called Geometric Arbitrage Theory and show that it is possible to: --Write arbitrage as curvature of a principal fibre bundle. --Parameterize arbitrage strategies by its holonomy. --Give the Fundamental Theorem of Asset …
We apply Geometric Arbitrage Theory to obtain results in mathematical finance for credit markets, which do not need stochastic differential geometry in their formulation. We obtain closed form equations involving default intensities and loss given defaults characterizing the no-free-lunch-with-vanishing-risk condition …
We explore the role that random arbitrage opportunities play in hedging financial derivatives. We extend the asymptotic pricing theory presented by Fedotov and Panayides [Stochastic arbitrage return and its implication for option pricing, Physica A 345 (2005), 207-217] for the case of hedging a derivative when arbitrag…
Deep learning models reconstruct volatility surfaces from noisy data under no-arbitrage constraints.
problem Reconstructing implied volatility surfaces from sparse and noisy option quotes.
method Compared multiple neural architectures including Transformers, U-Nets, and variational autoencoders.
result Transformer and U-Net architectures achieve strong reconstruction accuracy, especially under sparse observation regimes.
In frictionless financial markets, no-arbitrage is a local property in time. This means that a discrete time model is arbitrage-free if and only if there does not exist a one-period-arbitrage. With capital gains taxes, this equivalence fails. For a model with a linear tax and one non-shortable risky stock, we introduce…
Extends Black-Scholes model to include arbitrage.
problem Formulating finance models without stochastic geometry.
method Geometric Arbitrage Theory applied to Black-Scholes PDE.
result Equivalence between market dynamics and utility maximization.
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.
We obtain a deterministic characterisation of the \emph{no free lunch with vanishing risk}, the \emph{no generalised arbitrage} and the \emph{no relative arbitrage} conditions in the one-dimensional diffusion setting and examine how these notions of no-arbitrage relate to each other.
New characterisation of no-arbitrage condition in discrete time with multiple-priors.
problem Characterizing no-arbitrage in a multiple-priors setting.
method Proposed a new characterisation equivalent to existing no-arbitrage conditions.
result The new characterisation is equivalent to several no-arbitrage conditions and allows proof of important results.