Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

149297446594 · Jun 202019922001200920172026
48 results for waiting times

We investigate the waiting-time distribution of the absolute return in the Korean stock-market index KOSPI. We define the waiting time as a time interval during which the normalized absolute return remains continuously below a threshold rcr_c. Through an exponential bin plot, we observe that the waiting-time distributi…

2005-08-30abs ↗pdf ↗

We investigate intra-day foreign exchange (FX) time series using the inverse statistic analysis developed in [1,2]. Specifically, we study the time-averaged distributions of waiting times needed to obtain a certain increase (decrease) ρρ in the price of an investment. The analysis is performed for the Deutsch mark (DM…

2004-02-24abs ↗pdf ↗

In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows …

2005-05-31abs ↗pdf ↗

In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows …

2003-10-14abs ↗pdf ↗

In high frequency financial data not only returns but also waiting times between trades are random variables. In this work, we analyze the spectra of the waiting-time processes for tick-by-tick trades. The numerical problem, strictly related with the real inversion of Laplace transforms, is analyzed by using Tikhonov's…

2008-01-19abs ↗pdf ↗

Continuous time random walks (CTRWs) are used in physics to model anomalous diffusion, by incorporating a random waiting time between particle jumps. In finance, the particle jumps are log-returns and the waiting times measure delay between transactions. These two random variables (log-return and waiting time) are typi…

2006-08-29abs ↗pdf ↗

Continuous time random walks impose a random waiting time before each particle jump. Scaling limits of heavy tailed continuous time random walks are governed by fractional evolution equations. Space-fractional derivatives describe heavy tailed jumps, and the time-fractional version codes heavy tailed waiting times. Thi…

2008-09-09abs ↗pdf ↗

A theory which describes the share price evolution at financial markets as a continuous-time random walk has been generalized in order to take into account the dependence of waiting times t on price returns x. A joint probability density function (pdf) which uses the concept of a Lévy stable distribution is worked out.…

2003-10-15abs ↗pdf ↗

Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.

problem Optimizing business expansion under exposure constraints and opportunity costs.
method Formulated as a novel stochastic control problem combined with optimal stopping time, derived an explicit solution for exponential utility.
result Firms are incentivized to expand but may wait due to opportunity costs and other factors.

In this paper, the survival function of waiting times between orders and the corresponding trades in a double-auction market is studied both by means of experiments and of empirical data. It turns out that, already at the level of order durations, the survival function cannot be represented by a single exponential, thu…

2006-08-28abs ↗pdf ↗

Inverse statistics in economics is considered. We argue that the natural candidate for such statistics is the investment horizons distribution. This distribution of waiting times needed to achieve a predefined level of return is obtained from (often detrended) historic asset prices. Such a distribution typically goes t…

2002-11-02abs ↗pdf ↗

New approach uses deep reinforcement learning for vehicle dispatching, reducing waiting times.

problem Dynamic vehicle dispatching problem in various contexts.
method Event-based semi-Markov decision process with deep q-learning.
result Deep reinforcement learning policies outperform heuristic methods in New York City data.

New algorithm reduces costs and latency for large language model inference.

problem Optimizing inference costs and latency for large language models with GPU constraints.
method Formulated as an online scheduling problem with endogenous memory growth, introduced fluid model and WAIT algorithms.
result Reduced costs and latency, especially in near-overloaded and overloaded regimes.

We propose a useful approach for investigating the statistical properties of foreign currency exchange rates. Our approach is based on queueing theory, particularly, the so-called renewal-reward theorem. For the first passage processes of the Sony Bank US dollar/Japanese yen (USD/JPY) exchange rate, we evaluate the ave…

2006-06-05abs ↗pdf ↗

The level crossing and inverse statistics analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, να+ν_α^+, where Tα=1/να+T_α =1/ν_α^+ is the average waiting time for observing the level αα again. We estimate the probability P(K,α)P(K, α), which provides us the probab…

2010-01-25abs ↗pdf ↗

A new algorithm reduces training time for distributed machine learning by dynamically assigning backup workers.

problem Time-consuming synchronization phase due to slow workers (stragglers).
method Dynamic allocation of backup workers to minimize waiting time.
result Achieves linear speedup in convergence performance with more workers.

The inverse statistics is the distribution of waiting times needed to achieve a predefined level of return obtained from (detrended) historic asset prices \cite{optihori,gainloss}. Such a distribution typically goes through a maximum at a time coined the {\em optimal investment horizon}, τρτ^*_ρ, which defines the most…

2006-01-02abs ↗pdf ↗

Algorithm maximizes rewards with a budget and giving up option.

problem Sequential decision-making with stochastic rewards and resource consumption.
method Upper Confidence Bound (UCB) algorithm for maximizing cumulative reward.
result Logarithmic regret bound with improved dependence on problem parameters.

Exploiting a precise reproduction of a stock exchange, the robustness of the Continuous Double Auction (CDA) mechanism, evaluated by means of the waiting time distributions, has been proved versus 36 different set ups made by varying both the operators' behaviour and the market micro structure. The obtained results dem…

2008-02-22abs ↗pdf ↗

We apply the Continuous Time Random Walk (CTRW) framework, introduced in finance by Scalas et al., to the analysis of the probability distribution of time intervals between two consecutive trades in the case of BTP futures prices traded at LIFFE in 1997. Results corroborate the validity of the CTRW approach for the des…

2000-12-28abs ↗pdf ↗

New algorithm reduces federated learning rounds and improves privacy.

problem Inefficient synchronous federated learning causing scalability issues.
method Asynchronous federated learning with reduced communication and differential privacy via Gaussian noise.
result The algorithm reduces waiting times and network communication, making federated learning more scalable and private.

In this paper we consider the steepest descent H1H^{-1}-gradient flow of the length functional for immersed plane curves, known as the curve diffusion flow. It is known that under this flow there exist both initially immersed curves which develop at least one singularity in finite time and initially embedded curves whi…

2012-01-18abs ↗pdf ↗

Time and Sales of corn futures traded electronically on the CME Group Globex are studied. Theories of continuous prices turn upside down reality of intra-day trading. Prices and their increments are discrete and obey lattice probability distributions. A function for systematic evolution of futures trading volume is pro…

2017-04-03abs ↗pdf ↗

In this paper we present a rather general phenomenological theory of tick-by-tick dynamics in financial markets. Many well-known aspects, such as the Lévy scaling form, follow as particular cases of the theory. The theory fully takes into account the non-Markovian and non-local character of financial time series. Predi…

2000-01-10abs ↗pdf ↗

We analyze empirical data from the internet auction site Aukro.cz. The time series of activity shows truncated fractal structure on scales from about 1 minute to about 1 day. The distribution of waiting times as well as the distribution of number of auctions within fixed interval is a power law, with exponents 1.51.5 an…

2014-01-13abs ↗pdf ↗

Improves distributed SGD convergence speed with reduced computation load.

problem Mitigating stragglers in distributed SGD to speed up convergence.
method Modeling communication and computation times, adapting number of workers and computation load dynamically.
result Significantly reduces computation load while improving convergence speed.

In recent publications, the authors have considered inverse statistics of the Dow Jones Industrial Averaged (DJIA) [1-3]. Specifically, we argued that the natural candidate for such statistics is the investment horizons distribution. This is the distribution of waiting times needed to achieve a predefined level of retu…

2005-11-10abs ↗pdf ↗

This paper shows how to combine optimal tests into log-optimal processes.

problem How to combine optimal sequential tests into log-optimal processes.
method Using a new class of WAIT e-processes, the paper aggregates asymptotically optimal sequential tests into asymptotically log-optimal processes.
result It is possible to aggregate asymptotically optimal sequential tests into asymptotically log-optimal e-processes.

We derive an upper bound on the waiting time for a variational weak solution to Inverse Mean Curvature Flow in Rn+1\mathbb{R}^{n+1} to become star-shaped. As a consequence, we demonstrate that any connected surface moving by the flow which is not initially a topological sphere develops a singularity or self-intersection …

2019-09-03abs ↗pdf ↗

We review ideas on temporal dependences and recurrences in discrete time series from several areas of natural and social sciences. We revisit existing studies and redefine the relevant observables in the language of copulas (joint laws of the ranks). We propose that copulas provide an appropriate mathematical framework…

2013-11-20abs ↗pdf ↗

SGLDiff approximates Bayesian posterior distributions with subsampling error.

problem Approximating Bayesian posterior distributions in large-scale data settings.
method Stochastic Gradient Langevin Diffusion (SGLDiff) with subsampling.
result The Wasserstein distance between the posterior and SGLDiff's limiting distribution is bounded by a fractional power of the mean waiting time.

Stock markets can be characterized by fat tails in the volatility distribution, clustering of volatilities and slow decay of their time correlations. For an explanation models with several mechanisms and consequently many parameters as the Lux-Marchesi model have been used. We show that a simple herding model with only…

2002-07-11abs ↗pdf ↗

Assuming that the stock price Z=(Zt)0tTZ=(Z_t)_{0\leq t\leq T} follows a geometric Brownian motion with drift μRμ\in\mathbb{R} and volatility σ>0σ>0, and letting Mt=max0stZsM_t=\max_{0\leq s\leq t}Z_s for t[0,T]t\in[0,T], we consider the optimal prediction problems \[V_1=\inf_{0\leqτ\leq T}\mathsf{E}\biggl(\frac{M_T}{Z_τ}\biggr)\quadand\qu…

2009-08-07abs ↗pdf ↗