Study on ruin probabilities for Lévy processes with light-tailed jumps.
arXiv research
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.
Trend · papers per month
The paper optimizes utility for switching models using Lévy processes.
This paper presents generalized momentum mappings for covariant Hamiltonian field theories. The new momentum mappings arise from a generalization of symplectic geometry to , the bundle of vertically adapted linear frames over the bundle of field configurations . Specifically, the generalized field momentum obs…
Study on ruin probability with investment in risky assets modeled as semimartingales.
The paper provides a representation for dynamic risk measures and capital allocations.
We introduce a class of interest rate models, called the -CIR model, which gives a natural extension of the standard CIR model by adopting the -stable L{é}vy process and preserving the branching property. This model allows to describe in a unified and parsimonious way several recent observations on the sovereign …
The Wiener-Hopf factorization is obtained in closed form for a phase type approximation to the CGMY Lévy process. This allows, for the approximation, exact computation of first passage times to barrier levels via Laplace transform inversion. Calibration of the CGMY model to market option prices defines the risk neutral…
Let be a manifold, be a vector field on , and be a Banach space. For any fixed function and any fixed complex number , we study Hyers-Ulam stability of the global differential equation .
Modeling financial markets with a novel order flow model.
Constructs supermartingale couplings with full marginals constraints.
The paper explores risk-minimization for exponential additive models, providing mathematical expressions and numerical examples.
This paper considers multi-dimensional affine processes with continuous sample paths. By analyzing the Riccati system, which is associated with affine processes via the transform formula, we fully characterize the regions of exponents in which exponential moments of a given process do not explode at any time or explode…
Study optimal strategy for maximizing exponential utility in financial market with linear price impact.
Study optimizes inventory restocking for demand processes with exponential replenishment.
Paper evaluates squared-exponential covariance function for Gaussian processes with integral observations.
Develops European power option pricing under correlated interest rate and asset processes.
Optimizes spending by adjusting a discount factor modelled as an exponential CIR process.
We introduce an algorithm for the pricing of finite expiry American options driven by Lévy processes. The idea is to tweak Carr's `Canadisation' method, cf. Carr [9] (see also Bouchard et al [5]), in such a way that the adjusted algorithm is viable for any Lévy process whose law at an independent, exponentially distrib…
The purpose of this note is to describe, in terms of a power series, the distribution function of the exponential functional, taken at some independent exponential time, of a spectrally negative Lévy process ξwith unbounded variation. We also derive a Geman-Yor type formula for Asian options prices in a financial marke…
Hawkes processes have seen a number of applications in finance, due to their ability to capture event clustering behaviour typically observed in financial systems. Given a calibrated Hawkes process, of concern is the statistical fit to empirical data, particularly for the accurate quantification of self- and mutual-exc…
The study establishes conditions for stratified spaces to satisfy RCD(K, N) curvature-dimension condition.
Study optimal stopping times for multi-dimensional processes with non-exponential discounting.
Quantum systems with scrambling improve temporal information processing, but scaling requires exponential overhead.
We develop a new Monte Carlo variance reduction method to estimate the expectation of two commonly encountered path-dependent functionals: first-passage times and occupation times of sets. The method is based on a recursive approximation of the first-passage time probability and expected occupation time of sets of a Le…
The logistic regression model is known to converge to a Poisson point process model if the binary response tends to infinitely imbalanced. In this paper, it is shown that this phenomenon is universal in a wide class of link functions on binomial regression. The proof relies on the extreme value theory. For the logit, p…
We analyze exponential integrability properties of the Cox-Ingersoll-Ross (CIR) process and its Euler discretizations with various types of truncation and reflection at 0. These properties play a key role in establishing the finiteness of moments and the strong convergence of numerical approximations for a class of sto…
This work introduces a new probabilistic process for regularization in machine learning.
This paper sets baselines for reading comprehension benchmarks, finding simple models often perform well.
Paper explores duality in DPPs using embedding structure analysis.
Paper calculates the distribution of time spent below zero in risk models.
Exponential functionals of Brownian motion have been extensively studied in financial and insurance mathematics due to their broad applications, for example, in the pricing of Asian options. The Black-Scholes model is appealing because of mathematical tractability, yet empirical evidence shows that geometric Brownian m…
New model captures time-varying volatility with stochastic exponential tails.
Develops quasi-likelihood analysis for marked point processes and applies it to Hawkes processes.
The distribution of trade sizes and trading volumes are investigated based on the limit order book data of 22 liquid Chinese stocks listed on the Shenzhen Stock Exchange in the whole year 2003. We observe that the size distribution of trades for individual stocks exhibits jumps, which is caused by the number preference…
Modeling aggressive market order arrivals using Hawkes factor models.
In this paper we propose a transform method to compute the prices and greeks of barrier options driven by a class of Levy processes. We derive analytical expressions for the Laplace transforms in time of the prices and sensitivities of single barrier options in an exponential Levy model with hyper-exponential jumps. In…
Investigates stock models using tempered stable processes for option pricing.
We consider expected utility maximisation problem for exponential Levy models and HARA utilities in presence of illiquid asset in portfolio. This illiquid asset is modelled by an option of European type on another risky asset which is correlated with the first one. Under some hypothesis on Levy processes, we give the e…
In a Markovian stochastic volatility model, we consider financial agents whose investment criteria are modelled by forward exponential performance processes. The problem of contingent claim indifference valuation is first addressed and a number of properties are proved and discussed. Special attention is given to the c…
Study compares exponential and power-law kernels in modeling high-frequency trading data.
Optimal insurance and investment strategy under exponential preferences in a correlated market model.
Motivated by the pricing of lookback options in exponential Lévy models, we study the difference between the continuous and discrete supremum of Lévy processes. In particular, we extend the results of Broadie et al. (1999) to jump-diffusion models. We also derive bounds for general exponential Lévy models.
Extend classical theory of affine processes to path-dependent setting
Linear cost method approximates Gaussian Matérn processes with exponentially convergent accuracy.
Conjugate pairs of distributions over infinite dimensional spaces are prominent in statistical learning theory, particularly due to the widespread adoption of Bayesian nonparametric methodologies for a host of models and applications. Much of the existing literature in the learning community focuses on processes posses…
New method reduces sample complexity for learning Ising model dynamics exponentially.
Introduces a new stationary GE-process for gold price analysis.
Incorporates matrix exponential into generative flows for improved performance.