A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Innovative inequalities for divergences with applications in PAC-Bayesian bounds and Monte Carlo.
New PAC-Bayes bounds derived using Legendre transform and f-divergences.
The study provides a theory for causal machine learning with generalization bounds.
We study the stability of several no-arbitrage conditions with respect to absolutely continuous, but not necessarily equivalent, changes of measure. We first consider models based on continuous semimartingales and show that no-arbitrage conditions weaker than NA and NFLVR are always stable. Then, in the context of gene…
Corrects technical error in change of measure for HTB models.
The rBergomi model is improved with a regime switching change of measure to match market VIX smiles.
Unified framework for information-theoretic bounds on learning algorithms.
Develops methods to simulate option prices for a specific stochastic volatility model.
Unified framework for deriving generalization bounds in supervised learning.
The paper develops a new formula for financial pricing under multiple interest rates and collateralization.
Paper proposes a new algorithm to reduce derivative pricing computation time.
Study S-shaped utility maximization with VaR constraint and unobservable drift.
When dealing with Heston's stochastic volatility model, the change of measure from the subjective measure P to the objective measure Q is usually investigated under the assumption that the Feller condition is satisfied. This paper closes this gap in the literature by deriving sufficient conditions for the existence of …
In a 2006 article (\cite{A1}), Allouba gave his quadratic covariation differentiation theory for Itô's integral calculus. He defined the derivative of a semimartingale with respect to a Brownian motion as the time derivative of their quadratic covariation and a generalization thereof. He then obtained a systematic diff…
Paper introduces EEMs for pricing contingent claim returns.
Paper introduces infinite-dimensional generative models using Doob's h-transform.
No-arbitrage models of term structure have the feature that the return on zero-coupon bonds is the sum of the short rate and the product of volatility and market price of risk. Well known models restrict the behavior of the market price of risk so that it is not dependent on the type of asset being modeled. We show tha…
We derive measure change formulae required to price midcurve swaptions in the forward swap annuity measure with stochastic annuities' ratios. We construct the corresponding linear and exponential terminal swap rate pricing models and show how they capture the midcurve swaption correlation skew.
The paper introduces CoCoCat bonds for multi-region natural catastrophes, accounting for complex dependencies.
New framework controls generalization for heavy-tailed data in RLHF and SGLD.
In this paper, we are concerned with the valuation of Guaranteed Annuity Options (GAOs) under the most generalised modelling framework where both interest and mortality rates are stochastic and correlated. Pricing these type of options in the correlated environment is a challenging task and no closed form solution exis…
The paper addresses dynamic capital structure models with defaultable debt, proving existence and uniqueness.
In this paper we introduce a class of information-based models for the pricing of fixed-income securities. We consider a set of continuous- time information processes that describe the flow of information about market factors in a monetary economy. The nominal pricing kernel is at any given time assumed to be given by …
New findings show transfer learning is possible even when density ratios are unbounded.
A new method reduces Monte Carlo variance for financial payoffs.
URGE improves diffusion model quality without gradients or Hessian.
Solves risk-sensitive investment via duality, entropic regularization, and RL.
Sparse model selection by structural risk minimization leads to a set of a few predictors, ideally a subset of the true predictors. This selection clearly depends on the underlying loss function . For linear regression with square loss, the particular (functional) Gradient Boosting variant Boosting exce…
In electricity markets, it is sensible to use a two-factor model with mean reversion for spot prices. One of the factors is an Ornstein-Uhlenbeck (OU) process driven by a Brownian motion and accounts for the small variations. The other factor is an OU process driven by a pure jump Lévy process and models the characteri…
New bound matches exact generalization error for quadratic Gaussian problem.
We discuss the class of "Quadratic Normal Volatility" models, which have drawn much attention in the financial industry due to their analytic tractability and flexibility. We characterize these models as the ones that can be obtained from stopped Brownian motion by a simple transformation and a change of measure that o…
The stochastic multi-armed bandit model is a simple abstraction that has proven useful in many different contexts in statistics and machine learning. Whereas the achievable limit in terms of regret minimization is now well known, our aim is to contribute to a better understanding of the performance in terms of identify…
This paper studies a class of exponential family models whose canonical parameters are specified as linear functionals of an unknown infinite-dimensional slope function. The optimal minimax rates of convergence for slope function estimation are established. The estimators that achieve the optimal rates are constructed …
In this paper, a geometric function is introduced to reflect the attenuation speed of impact of one firm's default to its partner. If two firms are competitions (copartners), the default intensity of one firm will decrease (increase) abruptly when the other firm defaults. As time goes on, the impact will decrease gradu…
A key driver of Credit Value Adjustment (CVA) is the possible dependency between exposure and counterparty credit risk, known as Wrong-Way Risk (WWR). At this time, addressing WWR in a both sound and tractable way remains challenging: arbitrage-free setups have been proposed by academic research through dynamic models …
Optimizes variance reduction in Heston model using large and moderate deviations.
Researchers prove a new measure for a financial volatility model.
A single algebraic identity unifies information-theoretic variational results.
We study the sensitivity of the expected utility maximization problem in a continuous semi-martingale market with respect to small changes in the market price of risk. Assuming that the preferences of a rational economic agent are modeled with a general utility function, we obtain a second-order expansion of the value …
A deep BSDE approach tackles multi-layered xVA calculations for portfolio valuation.
Transform drift of diffusions without knowing if measure change is a martingale.
New constraints on space and adaptivity in bandits force more batches and memory use.
We find a simple expression for the probability density of in terms of its distribution function and the distribution function for the time integral of . The relation is obtained with a change of measure argument where expectations over events determined by the time integral…
Geometric Bass martingales linked to Brownian motion and geometric Brownian motion.
We study strict local martingales via h-transforms, a method which first appeared in Delbaen-Schachermayer. We show that strict local martingales arise whenever there is a consistent family of change of measures where the two measures are not equivalent to one another. Several old and new strict local martingales are i…
We develop generic and efficient importance sampling estimators for Monte Carlo evaluation of prices of single- and multi-asset European and path-dependent options in asset price models driven by Lévy processes, extending earlier works which focused on the Black-Scholes and continuous stochastic volatility models. Usin…
We review the nature of some well-known phenomena such as volatility smiles, convexity adjustments and parallel derivative markets. We propose that the market is incomplete and postulate the existence of intrinsic risks in every contingent claim as a basis for understanding these phenomena. In a continuous time framewo…
This paper presents a novel one-factor stochastic volatility model where the instantaneous volatility of the asset log-return is a diffusion with a quadratic drift and a linear dispersion function. The instantaneous volatility mean reverts around a constant level, with a speed of mean reversion that is affine in the in…