New automated market makers for multi-asset trading.
problem Liquidity management in multi-asset trading.
method Derived from self-financing transactions and rebalancing principles.
result Constant product market maker as a special case.
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48 results for “multi-asset markets”
Improved Robust Price Bounds for Multi-Asset Derivatives under Market-Implied Dependence Informationq-fin.MF
Improved price bounds for multi-asset derivatives using market option data.
problem Creating robust price bounds for multi-asset derivatives under market-implied dependence.
method Extracting inter-asset dependence information from market option prices and applying modified martingale optimal transport.
result Improved price bounds for multi-asset derivatives, demonstrating relevance and tractability.
This paper provides formulas for minimum cost super-hedging in a multi-asset binomial market.
problem Finding minimum cost super-hedging strategies in a multi-asset, incomplete market model.
method Explicit formulas for minimum cost super-hedging strategies for various European type multi-asset contingent claims.
result Explicit formulas for non-negative local residuals of super-hedging strategies.
Paper proposes a CNN model for improved multi-asset portfolio risk prediction.
problem Challenges in risk management of multi-asset portfolios due to limited correlation capture.
method Uses CNN and image processing to convert financial data into images for enhanced feature extraction.
result CNN model significantly outperforms traditional methods in risk prediction accuracy.
Simulates multi-asset spot and option markets using normalizing flows.
problem High-dimensionality of market call prices and dynamic preservation across simulators.
method Normalizing flows for efficient low-dimensional representations, conditional invertibility for joint distribution calibration.
result Calibrated simulators maintain dynamics of each underlying and accurately represent market call prices.
Paper uses RL to optimize multi-asset portfolios in fluctuating markets.
problem Optimizing multi-asset portfolios in time-varying financial markets.
method Soft Actor-Critic (SAC) algorithm for policy learning, policy iteration process.
result SAC algorithm outperforms in various criteria in simulated and real financial markets.
New model explains market dynamics with phase transitions and non-linear interactions.
problem Understanding complex multi-asset market dynamics with phase transitions.
method Developed a Multi-Asset Non-Equilibrium Skew (MANES) model based on Langevin dynamics and McKean-Vlasov equation.
result The model accurately predicts market returns and phase transitions in both benign and distressed markets.
Improved bounds for multi-asset options using deep learning and market prices.
problem Computing model-free bounds for multi-asset options with uncertainty in dependence structure.
method Fundamental theorem of asset pricing, superhedging duality, penalization approach, deep learning.
result Deep learning approximations improve computational efficiency and accuracy.
Closed-form pricing method for multi-asset options.
problem Pricing multi-asset contingent claims in an incomplete market.
method Proving extremal martingale measures and constructing algorithms for bounds and hedging.
result Closed-form formulas for no-arbitrage price intervals and hedging strategies.
Deep learning improves portfolio optimization in volatile markets.
problem Challenges in long-only, multi-asset strategies across market cycles.
method Training DL models with limited regime data using pre-training techniques and transformer architectures.
result Models show resilience and improved predictive accuracy in volatile markets.
Study of a risk-averse informed trader in a multi-asset market with non-Gaussian prices.
problem Existence of equilibrium in a multi-asset market with non-Gaussian prices and a risk-averse informed trader.
method Constructed equilibrium using Fokker-Planck equation and coupled partial differential equations with an optimal transport constraint.
result Equilibrium exists in a market with multiple assets and non-Gaussian prices.
CFMMs solve complex multi-asset trades via convex optimization.
problem Complex multi-asset trades in decentralized exchanges.
method Formulate multi-asset trades as convex optimization problems.
result Efficiently solve multi-asset trades using convex optimization.
Study shows integrating OFI from multiple levels improves price impact explanation but not forecasting.
problem Explaining and forecasting price movements in equity markets using OFI.
method Systematic approach to combine OFIs from multiple levels into an integrated variable, testing multi-asset models with and without cross-impact terms.
result Lagged cross-asset OFIs improve future return forecasting but not contemporaneous price impact.
Multi-asset return risk measuresq-fin.MF
Extends return risk measures to multiple assets, proving properties and comparing different risk models.
problem Evaluating risk in financial markets with multiple assets.
method Develops multi-asset return risk measures (MARRMs), analyzes their properties, and compares them with other risk models.
result Proves that a positively homogeneous MARRM is quasi-convex if and only if it is convex, and provides conditions to avoid inconsistent risk evaluations.
Exponential Lévy processes have been used for modelling financial derivatives because of their ability to exhibit many empirical features of markets. Using their multidimensional analogue, a general analytic pricing formula is obtained, allowing for the direct valuation of multi-asset options on $n \in \z^+$ risky asse…
Market maker optimizes SPX and VIX spread using quadratic rough Heston model.
problem Maximizing profit from SPX and VIX spread while managing inventory risk.
method Uses quadratic rough Heston model to optimize multi-asset market making problem, approximating high-dimensional optimization.
result Asymptotic closed-form solution for optimization problem.
We are interested in the existence of equivalent martingale measures and the detection of arbitrage opportunities in markets where several multi-asset derivatives are traded simultaneously. More specifically, we consider a financial market with multiple traded assets whose marginal risk-neutral distributions are known,…
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while …
The paper develops bounds for multi-asset derivatives using option prices.
problem Computing model-free upper and lower bounds for multi-asset derivatives.
method Develops a fundamental theorem of asset pricing and superhedging duality, recasting the problem into a linear semi-infinite optimization problem and providing algorithms for exact computation.
result Provides -optimal upper and lower bounds for multi-asset derivatives, characterizing optimal pricing measures.
Multi-asset optimal execution and statistical arbitrage strategies under Ornstein-Uhlenbeck dynamicsq-fin.TR
The paper addresses optimal execution for multi-asset portfolios using Ornstein-Uhlenbeck dynamics.
problem Optimal execution for multi-asset portfolios with Ornstein-Uhlenbeck dynamics.
method Stochastic optimal control and simplification of Hamilton-Jacobi-Bellman equation to ODEs.
result Existence and uniqueness of solution to the execution problem using extit{a priori} estimates.
Investigates price dynamics of two assets with and without bubbles, deriving conditions for equilibrium prices.
problem Understanding price dynamics and bubbles in multi-asset markets.
method Derives sufficient and necessary conditions for average equilibrium price dynamics in a two-asset model.
result Assets with positive average dividends display hump-shaped bubbles, while those with constant fundamental values show misvaluation effects.
A large proportion of market making models derive from the seminal model of Avellaneda and Stoikov. The numerical approximation of the value function and the optimal quotes in these models remains a challenge when the number of assets is large. In this article, we propose closed-form approximations for the value functi…
Method detects and visualizes changes in financial markets' asset relationships.
problem Detecting and explaining changes in financial markets' asset relationships.
method Construct co-occurrence networks, calculate Graph-Based Entropy, apply Differential Network.
result Visualization of changes in financial markets with high interpretability.
In this paper we provide evidence that financial option markets for equity indices give rise to non-trivial dependency structures between its constituents. Thus, if the individual constituent distributions of an equity index are inferred from the single-stock option markets and combined via a Gaussian copula, for examp…
Generative Adversarial Network (GAN) simulates realistic multi-asset scenarios for tail risk.
problem Simulating realistic joint dynamics of multi-asset portfolios for tail risk estimation.
method Designing a GAN that preserves Value-at-Risk (VaR) and Expected Shortfall (ES) tail risk features.
result Correctly captures tail risk for a broad class of trading strategies and demonstrates strong generalization.
Shortfall Risk Approximations for American Options in the multidimensional Black--Scholes Modelq-fin.CP
We show that shortfall risks of American options in a sequence of multinomial approximations of the multidimensional Black--Scholes (BS) market converge to the corresponding quantities for similar American options in the multidimensional BS market with path dependent payoffs. In comparison to previous papers we conside…
In this paper we present a new multi-asset pricing model, which is built upon newly developed families of solvable multi-parameter single-asset diffusions with a nonlinear smile-shaped volatility and an affine drift. Our multi-asset pricing model arises by employing copula methods. In particular, all discounted single-…
Optimal market makingq-fin.TR
Market makers provide liquidity to other market participants: they propose prices at which they stand ready to buy and sell a wide variety of assets. They face a complex optimization problem with both static and dynamic components. They need indeed to propose bid and offer/ask prices in an optimal way for making money …
The paper prices swaps on generalized variance measures for multiple assets.
problem Hedging risk in financial markets with multi-asset swaps.
method Pricing generalized variance swaps using Barndorff-Nielsen and Shephard model.
result Results have implications for commodity sector risk management.
We extend to the multi-asset case the framework of a discrete time model of a single asset financial market developed in Ghoulmie et al (2005). In particular, we focus on adaptive agents with threshold behavior allocating their resources among two assets. We explore numerically the effect of this diversification as an …
This paper solves hedging in incomplete markets using neural networks.
problem Hedging in incomplete markets with risk factor, illiquidity, and discrete transaction dates.
method Proposes a jump-diffusion model and uses RNN, LSTM, and Mogrifier-LSTM neural networks for hedging strategies.
result Mogrifier-LSTM is the fastest and most effective model for hedging.
SBCA optimizes portfolios by fusing price data and text sentiment.
problem Insufficient integration of multi-modal information in traditional portfolio optimization models.
method Cross-modal BERT-driven Actor-Critic framework with gated fusion and constraint embedding.
result SBCA outperforms benchmarks in portfolio value, return, Sharpe ratio, and maximum drawdown.
This study optimizes crypto-market trading conditions without assuming convexity.
problem Optimizing crypto-market trading conditions without convexity.
method Rigorous mathematical analysis of constant function market makers under quasilinear trade functions.
result Quasilinear trade functions can replicate convex functions' robustness against arbitrage.
Efficient method for pricing multi-asset options with local volatility.
problem Pricing options on multiple assets with varying volatility.
method Generic hybrid numerical method for efficient pricing.
result Efficient pricing of multi-asset options with local volatility.
Estimates self- and cross-impact concavity and decay patterns in financial markets.
problem Understanding the impact of financial transactions on market dynamics.
method Nonparametric estimation of concave multi-asset propagator models using metaorders and order flow data.
result Concave self-impact with shifted power-law decay, significant gain from cross-impact, and improved predictive accuracy.
HRT uses bi-level reinforcement learning to optimize stock selection and execution in multi-asset equity markets.
problem Optimizing automated equity trading decisions under risk, turnover, and transaction costs.
method Hierarchical Reinforced Trader (HRT) framework that separates selection and execution decisions.
result HRT outperforms other methods in learning-based return-risk-cost trade-offs, improving Sharpe ratio and reducing turnover.
We show that financial correlations exhibit a non-trivial dynamic behavior. We introduce a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affe…
Develops a novel framework for pricing variance swaps in multi-asset stochastic volatility models.
problem Pricing variance swaps in multi-asset stochastic volatility models.
method Determinant-based instantaneous generalized variance, Heston and BNS stochastic volatility frameworks.
result Analytical pricing expressions for multi-asset Heston and BNS formulations.
We perform a large-scale simulation of an Ising-based financial market model that includes 300 asset time series. The financial system simulated by the model shows a fat-tailed return distribution and volatility clustering and exhibits unstable periods indicated by the volatility index measured as the average of absolu…
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.
Multi-asset minority gamesphysics.soc-ph
We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More s…
This paper proposes swaps on two important new measures of generalized variance, namely the maximum eigen-value and trace of the covariance matrix of the assets involved. We price these generalized variance swaps for financial markets with Markov-modulated volatilities. We consider multiple assets in the portfolio for …
We employ perturbation analysis technique to study multi-asset portfolio optimisation with transaction cost. We allow for correlations in risky assets and obtain optimal trading methods for general utility functions. Our analytical results are supported by numerical simulations in the context of the Long Term Growth Mo…
Solvability of Differential Riccati Equations and Applications to Algorithmic Trading with Signalsq-fin.TR
Study solves DREs for trading strategies using signals and past prices.
problem Solving DREs for optimal trading strategies.
method Analyzes DREs with indefinite matrix coefficients and applies to trading problems.
result Derives optimal trading strategies using signals and past prices.
A new method simulates implied volatility surfaces for multiple assets.
problem Generating consistent market scenarios for multiple asset implied volatilities.
method Combining functional data analysis and neural SDEs with a penalty for model misspecification.
result Simulated market scenarios are consistent with historical features and lie within the sub-manifold of essentially free static arbitrage.
Study consumption-investment problem in markets with rank-based returns.
problem Consumption-investment problem in markets with rank-based returns.
method Derives an HJB equation with Neumann boundary conditions for the value function and proves a corresponding verification theorem.
result Explicit solutions for unconstrained, open market constraints, and fully invested cases.
Study explores optimal portfolio control in financial markets with transaction costs.
problem Optimal portfolio control in financial markets with proportional transaction costs.
method Geometric approach to financial markets, set-valued techniques, stochastic Mayer control problem.
result Continuity of the optimal value and control under price approximations in a multi-asset framework.
Optimal Consumption under Habit Formation In Markets with Transaction Costs and Random Endowmentsq-fin.PM
This paper studies the optimal consumption under the addictive habit formation preference in markets with transaction costs and unbounded random endowments. To model the proportional transaction costs, we adopt the Kabanov's multi-asset framework with a cash account. At the terminal time T, the investor can receive unb…