arXiv research

SPADE improves demand forecasting accuracy by 4.5% for post-promotion periods.

We win EVA2025 by estimating extreme precipitation events using Peaks Over Thresholds and martingale testing.

Method identifies financial rogue waves close to their onset.

We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the b…

In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange…

Distributed, controllable energy storage devices offer several benefits to electric power system operation. Three such benefits include reducing peak load, providing standby power, and enhancing power quality. These benefits, however, are only realized during peak load or during an outage, events that are infrequent. T…

Study analyzes cryptocurrency pump-and-dump dynamics using minute-level data.

Study examines Bitcoin's price history and identifies recurring events.

Using publicly available traffic camera data in New York City, we quantify time-dependent patterns in aggregate pedestrian foot traffic. These patterns exhibit repeatable diurnal behaviors that differ for weekdays and weekends but are broadly consistent across neighborhoods in the borough of Manhattan. Weekday patterns…

The study explains stock return distributions using reaction functions.

We argue that the word ``critical'' in the title is not purely literary. Based on our and other previous work on nonlinear complex dynamical systems, we summarize present evidence, on the Oct. 1929, Oct. 1987, Oct. 1987 Hong-Kong, Aug. 1998 global market events and on the 1985 Forex event, for the hypothesis advanced f…

Model captures asymmetric extreme events in financial returns.

This paper develops the Jungle model in a credit portfolio framework. The Jungle model is able to model credit contagion, produce doubly-peaked probability distributions for the total default loss and endogenously generate quasi phase transitions, potentially leading to systemic credit events which happen unexpectedly …

Daytime hypoglycemia should be accurately predicted to achieve normoglycemia and to avoid disastrous situations. Hypoglycemia, an abnormally low blood glucose level, is divided into daytime hypoglycemia and nocturnal hypoglycemia. Many studies of hypoglycemia prevention deal with nocturnal hypoglycemia. In this paper, …

Financial markets are extremely data-driven and regulated. Participants rely on notifications about significant events and background information that meet their requirements regarding timeliness, accuracy, and completeness. As one of Europe's leading providers of financial data and regulatory solutions vwd processes a…

DiTSNe-Ia model accurately reconstructs supernovae spectra from light curves.

We study trade-based manipulation of stock prices from the perspective of complex trading networks constructed by using detailed information of trades. A stock trading network consists of nodes and directed links, where every trader is a node and a link is formed from one trader to the other if the former sells shares …

A robust method for decomposing spectral peaks robust to distortion and interference.

Survival analysis is a type of semi-supervised ranking task where the target output (the survival time) is often right-censored. Utilizing this information is a challenge because it is not obvious how to correctly incorporate these censored examples into a model. We study how three categories of loss functions, namely …

Study improves crash rate forecasting in Washington, D.C. using stochastic volatility model.

We find empirically a characteristic sharp peak-flat trough pattern in a large set of commodity prices. We argue that the sharp peak structure reflects an endogenous inter-market organization, and that peaks may be seen as local ``singularities'' resulting from imitation and herding. These findings impose a novel strin…

New model predicts financial tail events using RIA-EVT-Copula.

This study examines local co-movements in energy, agriculture, and metal markets using copulas.

Bayesian Neural Networks detect gravitational wave events with high accuracy and real-time potential.

Joint peak detection is a central problem when comparing samples in genomic data analysis, but current algorithms for this task are unsupervised and limited to at most 2 sample types. We propose PeakSegJoint, a new constrained maximum likelihood segmentation model for any number of sample types. To select the number of…

Mass spectrometry (MS) is an important technique for chemical profiling which calculates for a sample a high dimensional histogram-like spectrum. A crucial step of MS data processing is the peak picking which selects peaks containing information about molecules with high concentrations which are of interest in an MS in…

Study on-chain peak shaving to reduce Ethereum transaction costs.

The paper explains two distinct peaks in generalization error for neural networks and simpler models, each governed by different factors.

The heuristic identification of peaks from noisy complex spectra often leads to misunderstanding of the physical and chemical properties of matter. In this paper, we propose a framework based on Bayesian inference, which enables us to separate multipeak spectra into single peaks statistically and consists of two steps.…

Bayesian framework integrates spectral deconvolution with expert reasoning for robust peak estimation.

FLOPART solves peak detection by creating accurate train and test set predictions.

The paper shows how the generalization curve can have multiple peaks, influenced by data and learning algorithm biases.

PEAKS selects key training examples incrementally based on prediction error and kernel similarity.

We report on time-varying network connectedness within three banking systems: North America, the EU, and ASEAN. The original method by Diebold and Yilmaz is improved by using exponentially weighted daily returns and ridge regularization on vector autoregression (VAR) and forecast error variance decomposition (FEVD). We…

PEAK tests means of multiple data streams with sequential betting.

Data analysis in high-dimensional spaces aims at obtaining a synthetic description of a data set, revealing its main structure and its salient features. We here introduce an approach providing this description in the form of a topography of the data, namely a human-readable chart of the probability density from which t…

LLMs learn peaked distributions slowly due to power-law losses.

Finite-time queue peaks in stochastic networks have logarithmic scaling after geometric thresholds.

Bayesian Quadrature improves ensembling for neural networks with dispersed likelihood peaks.

During a stock market peak the price of a given stock ($i$) jumps from an initial level $p_1(i)$ to a peak level $p_2(i)$ before falling back to a bottom level $p_3(i)$. The ratios $A(i) = p_2(i)/p_1(i)$ and $B(i)= p_3(i)/p_1(i)$ are referred to as the peak- and bottom-amplitude respectively. The paper show…

In this paper, the fractional order curvature equation $(-Δ)^γu = (1 + \varepsilon K(x))u^{\frac{N + 2γ}{N - 2γ}}$ in $\mathbb{R}^N$ is considered. Assuming $K(x)$ has two critical points satisfying certain local conditions, we prove the existence of two-peak solutions.

A nonparametric method for time series analysis extracts envelopes, detects peaks, and clusters data.

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change increment…

A central area of research in nonlinear science is the study of instabilities that drive the emergence of extreme events. Unfortunately, experimental techniques for measuring such phenomena often provide only partial characterization. For example, real-time studies of instabilities in nonlinear fibre optics frequently …

Paper proposes a network framework for prosumers to manage peak loads in Iran.

Traditionally in regression one minimizes the number of fitting parameters or uses smoothing/regularization to trade training (TE) and generalization error (GE). Driving TE to zero by increasing fitting degrees of freedom (dof) is expected to increase GE. However modern big-data approaches, including deep nets, seem to…

Parts of Texas, Oklahoma, and Kansas have experienced increased rates of seismicity in recent years, providing new datasets of earthquake recordings to develop ground motion prediction models for this particular region of the Central and Eastern North America (CENA). This paper outlines a framework for using Artificial…

New algorithm tackles constrained Markov decision processes with peak constraints.