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Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship between two time series. We propose a bootstrap test on unconditional and conditional Granger-causality spectra, as well as on their…

Statistical Finance · Quantitative Finance 2021-04-07 Matteo Farné , Angela Montanari

We study Doob's martingale convergence theorem for computable continuous time martingales on Brownian motion, in the context of algorithmic randomness. A characterization of the class of sample points for which the theorem holds is given.…

Logic in Computer Science · Computer Science 2015-07-01 Bjørn Kjos-Hanssen , Paul Kim Long V. Nguyen , Jason Rute

In this paper, we focus on the estimation of historical volatility of asset prices from high-frequency data. Stochastic volatility models pose a major statistical challenge: since in reality historical volatility is not observable, its…

Computational Finance · Quantitative Finance 2023-02-27 Camilla Damian , Rüdiger Frey

The main message in this paper is that there are surprisingly many different Brownian bridges, some of them - familiar, some of them - less familiar. Many of these Brownian bridges are very close to Brownian motions. Somewhat loosely…

Statistics Theory · Mathematics 2016-01-08 Estate Khmaladze

This paper considers the problem of testing for the presence of a continuous part in a semimartingale sampled at high frequency. We provide two tests, one where the null hypothesis is that a continuous component is present, the other where…

Statistics Theory · Mathematics 2016-08-14 Yacine Aït-Sahalia , Jean Jacod

We derive diffusion constants and martingales for senile random walks with the help of a time-change. We provide direct computations of the diffusion constants for the time-changed walks. Alternatively, the values of these constants can be…

Probability · Mathematics 2007-11-19 Wouter Kager

We complete the analysis of the phase diagram of the complex branching Brownian motion energy model by studying Phases I, III and boundaries between all three phases (I-III) of this model. For the properly rescaled partition function, in…

Probability · Mathematics 2017-04-19 Lisa Hartung , Anton Klimovsky

For any discrete-time $P$--local martingale $S$ there exists a probability measure $Q \sim P$ such that $S$ is a $Q$--martingale. A new proof for this result is provided. The core idea relies on an appropriate modification of an argument by…

Probability · Mathematics 2018-05-04 Vilmos Prokaj , Johannes Ruf

Speculative decoding is a promising approach for accelerating large language models. The primary idea is to use a lightweight draft model to speculate the output of the target model for multiple subsequent timesteps, and then verify them in…

Computation and Language · Computer Science 2025-11-06 Yepeng Weng , Qiao Hu , Xujie Chen , Li Liu , Dianwen Mei , Huishi Qiu , Jiang Tian , Zhongchao Shi

Trade prices of about 1000 New York Stock Exchange-listed stocks are studied at one-minute time resolution over the continuous five year period 2018--2022. For each stock, in dollar-volume-weighted transaction time, the discrepancy from a…

Pricing of Securities · Quantitative Finance 2023-05-16 William H. Press

In this paper we explore the fundamentals of the Martingale Representation Theorem (MRT) and a closely related result, the Clark-Ocone formula. We also investigate how far these theorems can be taken, notably beyond the regular Sobolev…

Probability · Mathematics 2013-06-25 Deborah Schneider-Luftman

In a Monte-Carlo test, the observed dataset is fixed, and several resampled or permuted versions of the dataset are generated in order to test a null hypothesis that the original dataset is exchangeable with the resampled/permuted ones.…

Methodology · Statistics 2025-05-05 Lasse Fischer , Aaditya Ramdas

We introduce a transform on the class of stochastic exponentials for d-dimensional Brownian motions. Each stochastic exponential generates another stochastic exponential under the transform. The new exponential process is often merely a…

Probability · Mathematics 2007-05-23 Victor Goodman

We study finite-horizon optimal switching with discrete intervention dates on a general filtration, allowing continuous-time observations between decision dates, and develop a deep-learning-based dual framework with computable upper bounds.…

Optimization and Control · Mathematics 2026-04-10 Junyan Ye , Hoi Ying Wong

In this paper, we study the functional convergence in law of the fluctuations of the derivative martingale of branching random walk on the real line. Our main result strengthens the results of Buraczewski et. al. [Ann. Probab., 2021] and is…

Probability · Mathematics 2023-11-29 Haojie Hou , Yan-Xia Ren , Renming Song

In this paper, we study the martingale property for a Scott correlated stochastic volatility model, when the correlation coefficient between the Brownian motion driving the volatility and the one driving the asset price process is…

Probability · Mathematics 2016-06-14 Khadija Akdim , M'hamed Eddahbi , Mouna Haddadi

This paper discusses the possibility to find and construct \textit{piecewise constant martingales}, that is, martingales with piecewise constant sample paths evolving in a connected subset of $\mathbb{R}$. After a brief review of standard…

Probability · Mathematics 2017-06-20 Christophe Profeta , Frédéric Vrins

We show that one can perform causal inference in a natural way for continuous-time scenarios using tools from stochastic analysis. This provides new alternatives to the positivity condition for inverse probability weighting. The probability…

Statistics Theory · Mathematics 2013-04-23 Kjetil Røysland

We present a new approach to noncommutative stochastic calculus that is, like the classical theory, based primarily on the martingale property. Using this approach, we introduce a general theory of stochastic integration and quadratic…

Operator Algebras · Mathematics 2025-10-28 David A. Jekel , Todd A. Kemp , Evangelos A. Nikitopoulos

We construct a class of nonnegative martingale processes that oscillate indefinitely with high probability. For these processes, we state a uniform rate of the number of oscillations and show that this rate is asymptotically close to the…

Machine Learning · Computer Science 2014-08-18 Jan Leike , Marcus Hutter