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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.

169,181 papers · 148 categories

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9182635 · Jul 202019922001200920182026
48 results for Time-changing Intensity

The present paper introduces a jump-diffusion extension of the classical diffusion default intensity model by means of subordination in the sense of Bochner. We start from the bi-variate process (X,D)(X,D) of a diffusion state variable XX driving default intensity and a default indicator process DD and time change it wi…

2014-03-21abs ↗pdf ↗

The paper optimizes RV estimation by efficient sampling in time-changed diffusion models.

problem Improving realized variance (RV) estimation in time-changed diffusion models.
method Theoretical analysis and simulations of hitting time and realized business time sampling schemes.
result Realized business time sampling is empirically most efficient for high noise levels.

We compute the value of a variance swap when the underlying is modeled as a Markov process time changed by a Lévy subordinator. In this framework, the underlying may exhibit jumps with a state-dependent Lévy measure, local stochastic volatility and have a local stochastic default intensity. Moreover, the Lévy subordina…

2012-09-04abs ↗pdf ↗

The paper examines how curvature-dimension conditions transform under time change for diffusions.

problem Transforming curvature-dimension conditions for diffusions under time change.
method Derives precise transformation formulas for synthetic lower Ricci bounds and curvature-dimension conditions.
result Precise formulas for curvature-dimension conditions under time change for diffusions and metric measure spaces.

A new method samples CGMY processes efficiently by decomposing their time changes.

problem Sampling CGMY processes with finite or infinite variation.
method Exploiting time change representation, decomposing into two independent components.
result The method is advantageous over existing methods in simulations.

We introduce a class of randomly time-changed fast mean-reverting stochastic volatility models and, using spectral theory and singular perturbation techniques, we derive an approximation for the prices of European options in this setting. Three examples of random time-changes are provided and the implied volatility sur…

2010-10-25abs ↗pdf ↗

In quantitative finance, we often model asset prices as a noisy Ito semimartingale. As this model is not identifiable, approximating by a time-changed Levy process can be useful for generative modelling. We give a new estimate of the normalised volatility or time change in this model, which obtains minimax convergence …

2013-12-20abs ↗pdf ↗

Paper evaluates geometric Asian power options using a mixed fractional model.

problem Evaluating geometric Asian power options under specific stochastic processes.
method Mixed fractional subdiffusive Black-Scholes model applied to time changed mixed fractional Brownian motion.
result Derives a pricing formula for geometric Asian options.

Motivated by the interplay between structural and reduced form credit models, we propose to model the firm value process as a time-changed Brownian motion that may include jumps and stochastic volatility effects, and to study the first passage problem for such processes. We are lead to consider modifying the standard f…

2009-04-15abs ↗pdf ↗

New findings show independent subordination is not relevant for accurate option pricing.

problem Determining if independent subordination improves option pricing accuracy.
method Utilized a class of additive processes (ATS) to demonstrate that independent subordination is incompatible with market data and shows worse calibration performances.
result Independent subordination is not relevant for accurate option pricing, as shown by the ATS class of processes.

Study shows subordinated Cramér-Lundberg model increases ruin probability.

problem Analyzing the impact of subordinated time-changed claims on insurance ruin probability.
method Examined a compound Poisson process modified by a Lévy subordinator.
result Probability of ruin decreases slowly with initial capital, despite unchanged total claim amount.

The paper improves energy contract pricing models by incorporating jumps and varying parameters.

problem Inaccurate pricing of energy contracts using the Black-Scholes-Merton model.
method Integrates regime switching and time-changed Levy processes with a two-state Markov chain.
result Improved accuracy in pricing energy contracts through a new model.

Study new Ricci bounds for metric measure spaces, preserving properties under time changes.

problem Extend Ricci bounds to non-synthetic spaces and understand their behavior under time changes.
method Introduce distribution-valued lower Ricci bounds BE1(κ,)_1(κ,\infty), prove equivalence with gradient estimates, and show preservation under time changes.
result Distribution-valued Ricci bounds BE1(κ,)_1(κ,\infty) are preserved under arbitrary time changes and imply sharp gradient estimates.

Develops a new model for multi-currency volatility using CBI-time-changed Lévy processes.

problem Capturing the risk characteristics of FX markets and their self-exciting dynamics.
method CBI-time-changed Lévy processes, affine processes, Fourier methods, deep-learning techniques.
result An analytically tractable model with a semi-closed pricing formula for currency options.

This paper extends subordinated models to include stochastic time changes, improving financial modeling.

problem Improving financial models to better capture market features like jump clustering and volatility persistence.
method Subordinated processes with Levy and stochastic arrival mechanisms.
result Strong consistency and asymptotic normality results for VG and VGSA processes under various stochastic arrival models.

We prove that the variance swap rate (fair strike) equals the price of a co-terminal European-style contract when the underlying is an exponential Markov process, time-changed by an arbitrary continuous stochastic clock, which has arbitrary correlation with the driving Markov process, provided that the payoff function …

2017-05-02abs ↗pdf ↗

The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data. However, some of the most popular models suffer from a) overfitting problems and multiple local optima, b) failure to capture shifts in market conditions and c) large computational costs. To addr…

2013-05-18abs ↗pdf ↗

The accurate prediction of time-changing variances is an important task in the modeling of financial data. Standard econometric models are often limited as they assume rigid functional relationships for the variances. Moreover, function parameters are usually learned using maximum likelihood, which can lead to overfitt…

2014-02-13abs ↗pdf ↗

We introduce a new class of processes for the evaluation of multivariate equity derivatives. The proposed setting is well suited for the application of the standard copula function theory to processes, rather than variables, and easily enables to enforce the martingale pricing requirement. The martingale condition is i…

2016-07-06abs ↗pdf ↗

Paper solves PDEs for optimal investment strategies in volatile markets.

problem Finding optimal investment strategies in volatile markets.
method Numerical methods using time-changed Bessel bridges.
result Solves PDEs for relative arbitrage opportunities in volatility-stabilized markets.

Paper presents adaptive minimax risk classifiers for multidimensional concept drift.

problem Multidimensional concept drift in supervised classification.
method Adaptive minimax risk classifiers (AMRCs) tracking multivariate and high-order distribution changes.
result AMRCs provide computable tight performance guarantees and improve classification.

We derive asymptotic expansions for option data to detect infinite variation volatility.

problem Detecting infinite variation volatility in high-frequency option data.
method Nonparametric higher-order asymptotic expansions for small-time changes of characteristic functions of Itô semimartingales.
result Evidence of infinite variation volatility in high-frequency option data.

Time changes of noise level at Warsaw Stock Market are analyzed using a recently developed method basing on properties of the coarse grained entropy. The condition of the minimal noise level is used to build an efficient portfolio. Our noise level approach seems to be a much better tool for risk estimations than standa…

2005-03-31abs ↗pdf ↗

For a given Markov process XX and survival function H\overline{H} on R+\mathbb{R}^+, the inverse first-passage time problem (IFPT) is to find a barrier function b:R+[,+]b:\mathbb{R}^+\to[-\infty,+\infty] such that the survival function of the first-passage time τb=inf{t0:X(t)<b(t)}τ_b=\inf \{t\ge0:X(t)<b(t)\} is given by H\overline{H}. In …

2013-06-12abs ↗pdf ↗

Introduces new financial models using subordinated processes.

problem Modeling asset returns with behavioral finance considerations.
method Introduces multiple internally embedded financial time-clocks, subordinated to Brownian motion, with a behavioral subordinator.
result New log-price process with multiple embedded subordinations, requiring estimation of new parameters.

Neural Diffusion Intensity Models simplify Cox processes inference.

problem Intractable nonparametric estimation and posterior inference of latent stochastic intensity in Cox processes.
method Variational framework using neural SDEs, with theoretical guarantee of ELBO maximization coinciding with maximum likelihood estimation.
result Accurate recovery of latent intensity dynamics and posterior paths with significant speedup.

Enlargement of filtrations is a classical topic in the general theory of stochastic processes. This theory has been applied to stochastic finance in order to analyze models with insider information. In this paper we study initial enlargement in a Markov chain market model, introduced by R. Norberg. In the enlargened fi…

2011-08-12abs ↗pdf ↗