23 papers
This paper extends concentration inequality theory to simple random tensors with heavy-tailed sub-Weibull coefficients by establishing bounds that reveal a phase transition between sub-Gaussian and heavy-tailed regimes, utilizing a new Generalized Maximal Inequality and Nagaev-type martingale analysis.
This paper characterizes the approximate Nash equilibrium of competing decentralized exchanges setting dynamic fees, revealing that while the two-regime fee structure persists, competition shifts the fee-switching boundary to a weighted average of oracle and competitor rates, ultimately reducing slippage for strategic traders while having activity-dependent effects on noise traders.
This paper establishes global universal approximation theorems for path-dependent functionals on spaces of piecewise linear paths using linear functionals of discrete-time signatures, demonstrating their applicability to Brownian motion-driven systems such as random and stochastic ordinary differential equations.
This paper establishes a non-standard analysis framework that unifies coherent risk measures and their finite-sample estimators through hyperfinite representations, yielding discrete Kusuoka formulae, plug-in consistency results, and asymptotic normality via a transparent probability-to-statistics dictionary.
This paper introduces a canonical framework for jointly lifting Brownian motion and low-regularity stochastic rough paths to model rough volatility via a single rough differential equation, thereby extending existing partial rough path theories, providing a numerical approximation scheme for correlated settings, and demonstrating successful calibration to market data.
This paper solves an intertemporal utility maximization problem with a no-borrowing constraint and stochastic excess returns in the Kim-Omberg framework by employing Lagrange duality to transform the primal problem into a dual singular control problem, which is then characterized via an auxiliary two-dimensional optimal stopping problem to derive optimal consumption and portfolio strategies.
This paper reformulates continuous-time optimal stopping as a regularized singular stochastic control problem using randomized stopping times and cumulative residual entropy to encourage exploration, enabling the derivation of unique optimal strategies and the development of scalable, policy-improving reinforcement learning algorithms.
This paper proposes a model-independent framework that utilizes perturbed optimal transport and Fisher information linearization to rapidly generate accurate SPX and VIX risk scenarios and hedging strategies without requiring full recalibration after market shocks.
This paper proposes a two-tier stochastic control model for market making in aggregator-routed RFQ markets that links dealer quoting strategies to slowly varying win-score promotion gates, revealing how the interplay between fast inventory dynamics and slow score evolution can lead to bistability, hysteresis, and endogenous "campaign vs. harvest" quoting patterns.
This paper introduces a novel class of single- and multi-level Fourier-RQMC algorithms that leverage frequency-domain integration and randomized quasi-Monte Carlo sampling to achieve superior accuracy and computational efficiency in estimating multivariate shortfall risk and optimal capital allocations compared to traditional Monte Carlo methods.
This paper establishes the existence of equilibria for non-Markovian mean-field games with unbounded controls and quadratic running costs using a weak formulation approach grounded in new stability results for quadratic-growth generalized McKean-Vlasov BSDEs, thereby removing previous restrictions on model parameter boundedness and time horizons.
This paper develops a general framework for dynamic, non-concave portfolio choice under smooth ambiguity and Bayesian learning, demonstrating how a robust representation of ambiguity aversion yields explicit trading rules and, in the context of delegated management, leads to more conservative risk-taking and reduced volatility.
This paper extends existing valuation frameworks for differential swaps by deriving explicit pricing and hedging strategies for contracts with collateral denominated in a currency different from the cash flows, demonstrating that such foreign-currency collateral introduces significant non-trivial valuation adjustments and risk exposures that must be incorporated into modern multi-currency models.
This paper proposes a dynamic market-making framework for spot FX that jointly optimizes size-dependent quotes and trade rejection decisions to manage latency-driven adverse selection, while incorporating an endogenous feedback mechanism where past rejections modulate client order flow, ultimately solved via dynamic programming and approximated by a tractable adiabatic-quadratic method.
This paper investigates the relationship between long-only global minimum variance portfolios and asset factor exposures, providing explicit analytical solutions for single-factor models and geometric descriptions for multi-factor scenarios, validated through empirical US stock data.
This paper provides a comprehensive definition and complete implementation guide for a time-dependent SABR-type Libor Market Model (SABR/LMM) designed to flexibly match the volatility skew and smile of interest rate derivatives, addressing the practical limitations of existing models in global banking.
This paper extends Kyle's (1985) seminal insider trading model to an infinite-dimensional, many-asset setting, deriving a parsimonious equilibrium with closed-form solutions for trading strategies, cross-market price impacts, and information efficiency.
This paper presents a no-arbitrage-based data-driven ensemble approach for option pricing that establishes a common representation space for domain adaptation and validates its effectiveness through real-world data and experimental results.
This paper analyzes an optimal stopping problem with a discontinuous reward function motivated by variable annuity pricing, establishing conditions under which surrender occurs only at maturity and deriving new analytical representations for the value function and surrender region based on fee and surrender charge structures.
This paper demonstrates that for asset returns following normal mean-variance mixture distributions, closed-form mean-risk optimal portfolios under general law-invariant convex risk measures can be derived by optimizing an adjusted Markowitz mean-variance model, facilitated by a new sufficient condition for stochastic dominance.