The paper explores risk measures and arbitrage in financial markets.
problem Quantifying and managing risk in financial markets.
method Introduces new risk measure axioms and characterizes arbitrage conditions.
result Derives the consistent price interval for financial contracts.
The paper examines how markets can anticipate and react to arbitrage opportunities, revealing biases and risks.
problem The tension between no arbitrage, information efficiency, and risk anticipation in markets.
method Continuous time analysis with model- or event-risk, allowing pre-horizon risk-resolution and Risk-Neutral Equivalent pricing.
result Optimised trading can suppress the anticipation of predictable risk-outcomes, creating an apparent Status Quo Bias.
Ineffective risk measures fail to control risky investor behavior in markets with arbitrage opportunities.
problem Ineffectiveness of coherent risk measures in managing risky investor behavior in markets with arbitrage opportunities.
method Analytical determination of ρ-arbitrage portfolios and consideration of realistic numerical examples of incomplete markets. result Expected shortfall constraints can be ineffective in realistic markets, but reasonable expected utility constraints are effective.
Study on portfolio selection and risk arbitrage in financial markets.
problem Analyzing optimal portfolios and risk arbitrage in financial markets with coherent risk measures.
method Characterization of optimal portfolios, dual representation, and interplay between EMMs and absolutely continuous measures.
result The absence of ρ-arbitrage is linked to the interplay between EMMs and absolutely continuous measures. Blockchain trading faces limits due to time-consuming settlement, exposing arbitrageurs to price risk.
problem Time-consuming settlement in blockchain trading limits arbitrage opportunities.
method Analysis of Bitcoin network and order book data.
result Cross-exchange price differences coincide with high settlement latency and low default risk.
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 …
Paper proposes a risk-averse approach to energy storage price arbitrage using conformal uncertainty quantification.
problem Inherent volatility and uncertainty of real-time electricity prices create financial risks for storage arbitrage.
method Two-layer prediction model with conformal uncertainty quantification for high coverage of real-time price uncertainty.
result The framework achieves good profit margins with minimal losses, demonstrating effectiveness in real-time market.
Proposes a method to construct risk-neutral marginals from arbitrage-free option prices.
problem Lack of risk-neutral marginals that are free of arbitrage and easy to use.
method Explicit construction of risk-neutral marginals from discrete arbitrage-free option prices.
result Explicit construction guarantees risk-neutral marginals free of butterfly and calendar arbitrage.
Study uncovers CDS anomalies leading to arbitrage profits.
problem Identifying arbitrage opportunities in CDS term structures.
method Derive No-arbitrage conditions for CDS term structures, analyze extensive dataset.
result Presented 2,416 pairs of anomalous CDS contracts.
Faster Ethereum slots boost CEX-DEX arbitrage by 535% and 203%.
problem Reducing Ethereum slot time impacts CEX-DEX arbitrage opportunities.
method Developed a trading model to simulate and compare agent behavior under different slot times.
result Faster slot times increase CEX-DEX arbitrage activity and returns.
Reflected geometric Brownian motion models are not arbitrage-free.
problem No-arbitrage condition violation in financial markets.
method Analysis of reflected geometric Brownian motion models.
result Models violate even the weakest no-arbitrage condition.
Develops a deep learning approach for statistical arbitrage.
problem Temporal price differences between similar assets.
method Constructs arbitrage portfolios using latent asset pricing factors and a convolutional transformer for time series signals.
result High risk-adjusted returns and Sharpe ratios with optimal trading policy.
Study arbitrage and utility in insider markets, proving criteria and strategies.
problem Arbitrage opportunities and market viability in insider markets.
method Criteria for No Unbounded Profits with Bounded Risk, optimal arbitrage strategies, utility maximization proofs.
result Characterization of optimal strategies and duality results for utility maximization.
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.
The study finds no evidence of stochastic arbitrage opportunities in S&P 500 index options.
problem Identifying arbitrage opportunities in S&P 500 index options.
method Developed linear and mixed-integer linear programs to compute the maximum option premium.
result No evidence of systematic stochastic arbitrage opportunities in S&P 500 index options.
The paper sets criteria for no arbitrage in complex financial models.
problem Determining conditions for the absence of arbitrage in financial markets.
method Established deterministic conditions for no arbitrage, NUPBR, and NFLVR in diffusion market models.
result Provided criteria in terms of scale function and speed measure.
Study systemic risk measures adjusted to financial markets.
problem Systemic risk in financial systems with market adjustments.
method Dual representation for convex robust systemic risk measures adjusted to the financial market.
result Relation to no-arbitrage conditions.
Determines conditions for arbitrage in complex financial markets.
problem Identifying markets without arbitrage opportunities.
method Derives deterministic criteria for equivalent martingale measures.
result Constructs financial markets with specific risk conditions.
ARBITER learns SPX-VIX term structures without arbitrage constraints.
problem Arbitrage-free modeling of SPX-VIX term structures.
method Risk-neutral neural operator mapping market states to operator outputs enforcing static arbitrage constraints.
result ARBITER outperforms other models in derivatives term structure evaluation metrics.
Study tests if deep hedging differs from delta hedging in a GARCH market model.
problem Whether deep hedging includes speculative components in a GARCH market.
method Tested in a GARCH-based market model, comparing deep hedging and delta hedging.
result The difference between deep hedging and delta hedging is speculative if risk measure does not prioritize adverse outcomes.
Extends classical model of transaction costs to convex costs and multivariate positions.
problem Risk arbitrage and hedging under transaction costs with convex costs and multivariate positions.
method Extends classical model to convex transaction costs and multivariate acceptable positions, using results for unbounded and non-closed random sets.
result Formulates no arbitrage conditions and explores their connections, leading to a decrease in superhedging prices.
This paper completes the analysis of Choulli et al. Non-Arbitrage up to Random Horizons and after Honest Times for Semimartingale Models and contains two principal contributions. The first contribution consists in providing and analysing many practical examples of market models that admit classical arbitrages while the…
We introduce the concept of spontaneous symmetry breaking to arbitrage modeling. In the model, the arbitrage strategy is considered as being in the symmetry breaking phase and the phase transition between arbitrage mode and no-arbitrage mode is triggered by a control parameter. We estimate the control parameter for mom…
Study shows cooperation can reduce investment risk and price gaps.
problem Investment risk and price gaps in cooperative markets.
method Introduced Collective Arbitrage and Collective Super-replication, established asset pricing theorems.
result Reduction of price intervals through collective super-replication.
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…
Short selling is key to exploiting arbitrage opportunities in financial markets.
problem Theoretical basis for differences in financial service regulations.
method Analyzing semimartingales to show arbitrage opportunities require short selling.
result Arbitrage opportunities can only be exploited through short selling.
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 …
Authors prove the existence of a martingale measure in credit risk models.
problem Existence of an equivalent martingale measure in hazard process models of credit risk.
method By identifying a no-arbitrage condition, the authors construct a measure that turns discounted stock and bond prices into martingales.
result The existence of a martingale measure is demonstrated in credit risk models.
We propose a unified analysis of a whole spectrum of no-arbitrage conditions for financial market models based on continuous semimartingales. In particular, we focus on no-arbitrage conditions weaker than the classical notions of No Arbitrage and No Free Lunch with Vanishing Risk. We provide a complete characterisation…
Modeling gas fee competition in decentralized exchanges to optimize arbitrage profits.
problem Gas fees and transaction ordering in decentralized exchanges create arbitrage opportunities.
method Developed a first equilibrium model of gas fee competition between two arbitrageurs under three transaction reversion settings.
result Mixed equilibria exist, and their characteristics depend on inventory risk and transaction settings.
Introduces ambiguity in credit risk markets using intensity-based models.
problem Uncertainty in default intensity in credit markets.
method Introduces a framework considering ambiguity in default intensity, constructs equivalent martingale measures using Girsanov theorem, and derives no-arbitrage price intervals.
result Derives the interval of no-arbitrage prices for bond prices under ambiguity in default intensity.
This paper generalizes the framework for arbitrage-free valuation of bilateral counterparty risk to the case where collateral is included, with possible re-hypotecation. We analyze how the payout of claims is modified when collateral margining is included in agreement with current ISDA documentation. We then specialize…
This paper introduces an arbitrage-free conic martingale model for credit risk.
problem The lack of an arbitrage-free conic martingale model for credit risk.
method Developed an arbitrage-free conic martingale called Φ-martingale.
result The Φ-martingale model satisfies the immersion property and is suitable for practical applications in credit risk.
Unified market making controls risk, arbitrage, and volatility surfaces.
problem Market making risk, arbitrage, and volatility surface consistency.
method Constrained RL and stochastic control for risk-sensitive execution and hedging.
result Agent achieves positive P&L with zero calendar and butterfly violations.
Machine learning helps estimate risk premiums of stocks without knowing their factors.
problem Estimate risk premiums of stocks without knowing their underlying factors.
method Used elastic-net machine learning to project stock returns onto peers and construct replicate portfolios.
result Unique stocks have higher SARP and excess returns than ubiquitous stocks.
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.
The paper identifies inconsistencies in post-crisis derivative pricing methods and derives no-arbitrage expressions.
problem Inconsistencies in post-crisis derivative pricing methods, particularly regarding cost components to a risk-free money account.
method Derives no-arbitrage expressions for default-risky derivative contracts with and without collateral.
result Avoids inconsistencies in derivative pricing methods by deriving no-arbitrage expressions.
Develops a method to predict stock returns with time-varying risk premia.
problem Predicting stock returns with time-varying risk premia while maintaining no-arbitrage restrictions.
method Penalized two-pass regression with time-varying factor loadings, incorporating penalization in the first pass and grouping in the second pass.
result The proposed method reduces prediction errors compared to other approaches.
We price financial models using optimization and probability theory.
problem Financial model pricing under risk-averse investors.
method Infinite dimensional optimization, probabilistic and functional analytic tools.
result Existence of optimal strategies and convergence of reservation prices.
A model-free framework extracts risk-neutral densities from short-dated options.
problem Arbitrage and bid-ask spread issues in short-dated options.
method Develops ARIES for filtering static arbitrage and SEDEx for density extraction.
result Robust density extraction across various market conditions and volatility smiles construction.
This paper considers a sequence of discrete-time random walk markets with a safe and a single risky investment opportunity, and gives conditions for the existence of arbitrages or free lunches with vanishing risk, of the form of waiting to buy and selling the next period, with no shorting, and furthermore for weak conv…
We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks listed on the JSE. Under the assumption of general no-arbitrage conditions, we arg…
Develops a new model for pricing without arbitrage opportunities.
problem Arbitrage opportunities in standard jump-diffusion models.
method Introduces a multi-type jump-diffusion model with diffusion-dependent jumps.
result Derives no-arbitrage condition linking drift to model parameters.
Study arbitrage-free models in financial markets under uncertainty.
problem Arbitrage-free modeling in financial markets with Knightian Uncertainty.
method Functional analytic approach, no specific assumptions on priors or state space.
result Absence of arbitrage equivalent to approximate martingale measures sharing the same polar set of priors.
Deep Hedging learns risk-neutral vol dynamics for option pricing.
problem Statistical arbitrage in market dynamics without transaction costs.
method Numerical approach to train market simulator and find risk-neutral density.
result Risk-neutral model for stochastic implied volatility can be used for pricing or Deep Hedging.
Develops framework for XVA calculation with no-arbitrage constraints.
problem Calculating XVA with no-arbitrage constraints.
method Derives BSDEs and PDEs for XVA calculation, identifies no-arbitrage intervals.
result Provides explicit expressions for XVA under various funding conditions.
Based on a criterium of mathematical simplicity and consistency with empirical market data, a stochastic volatility model has been obtained with the volatility process driven by fractional noise. Depending on whether the stochasticity generators of log-price and volatility are independent or are the same, two versions …
PolySwarm uses a swarm of LLMs to predict and arbitrage prediction markets.
problem Real-time prediction market trading and latency arbitrage inefficiencies.
method PolySwarm employs a swarm of 50 diverse LLMs, Bayesian combination, and risk-controlled execution.
result Swarm aggregation outperforms single-model baselines in prediction tasks.