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Related papers: Empirical Study of the 1-2-3 Trend Indicator

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Walking droplets -- millimetric oil droplets that self-propel across the surface of a vibrating fluid bath -- exhibit striking emergent statistics that remain only partially understood. In particular, in a variety of experiments, a robust…

Fluid Dynamics · Physics 2026-01-28 Skyler Mao , David Darrow

Fluctuations in stock prices are influenced by a complex interplay of factors that go beyond mere historical data. These factors, themselves influenced by external forces, encompass inter-stock dynamics, broader economic factors, various…

Statistical Finance · Quantitative Finance 2026-02-12 Ambedkar Dukkipati , Kawin Mayilvaghanan , Naveen Kumar Pallekonda , Sai Prakash Hadnoor , Ranga Shaarad Ayyagari

A statistical inference method is developed and tested for pairwise interacting systems whose degrees of freedom are continuous angular variables, such as planar spins in magnetic systems or wave phases in optics and acoustics. We…

Statistical Mechanics · Physics 2015-06-15 P. Tyagi , A. Pagnani , F. Antenucci , M. Ibáñez Berganza , L. Leuzzi

Real-world applications often require improved models by leveraging a range of cheap incidental supervision signals. These could include partial labels, noisy labels, knowledge-based constraints, and cross-domain or cross-task annotations…

Machine Learning · Computer Science 2021-09-13 Hangfeng He , Mingyuan Zhang , Qiang Ning , Dan Roth

With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the…

We introduce an improved variational autoencoder (VAE) for text modeling with topic information explicitly modeled as a Dirichlet latent variable. By providing the proposed model topic awareness, it is more superior at reconstructing input…

Computation and Language · Computer Science 2018-11-02 Yijun Xiao , Tiancheng Zhao , William Yang Wang

Besides the well-known effect of autocorrelations in time series of Monte Carlo simulation data resulting from the underlying Markov process, using the same data pool for computing various estimates entails additional cross correlations.…

Statistical Mechanics · Physics 2014-11-20 Martin Weigel , Wolfhard Janke

We propose two specifications of a real-time mixed-frequency semi-structural time series model for evaluating the output potential, output gap, Phillips curve, and Okun's law for the US. The baseline model uses minimal theory-based…

Econometrics · Economics 2023-04-03 Thomas Hasenzagl , Filippo Pellegrino , Lucrezia Reichlin , Giovanni Ricco

In this paper, we propose a new test for the detection of a change in a non-linear (auto-)regressive time series as well as a corresponding estimator for the unknown time point of the change. To this end, we consider an at-most-one-change…

Statistics Theory · Mathematics 2025-04-15 Claudia Kirch , Stefanie Schwaar

Recent work has emphasized the diversification benefits of combining trend signals across multiple horizons, with the medium-term window-typically six months to one year-long viewed as the "sweet spot" of trend-following. This paper…

Pricing of Securities · Quantitative Finance 2025-10-29 Alban Etienne , Jean-Jacques Ohana , Eric Benhamou , Béatrice Guez , Ethan Setrouk , Thomas Jacquot

Real-world autonomous systems operate under uncertainty about both their pose and dynamics. Autonomous control systems must simultaneously perform estimation and control tasks to maintain robustness to changing dynamics or modeling errors.…

Systems and Control · Computer Science 2018-08-03 Patrick Slade , Zachary N. Sunberg , Mykel J. Kochenderfer

We introduce a wavelet-based model of local stationarity. This model enlarges the class of locally stationary wavelet processes and contains processes whose spectral density function may change very suddenly in time. A notion of…

Statistics Theory · Mathematics 2008-08-12 Sébastien Van Bellegem , Rainer von Sachs

Binary $m$-sequences are ones with the largest period $n=2^m-1$ among the binary sequences produced by linear shift registers with length $m$. They have a wide range of applications in communication since they have several desirable…

Information Theory · Computer Science 2022-12-01 Xiaoyan Jing , Aixian Zhang , Keqin Feng

Classical technical analysis methods of stock evolution are recalled, i.e. the notion of moving averages and momentum indicators. The moving averages lead to define death and gold crosses, resistance and support lines. Momentum indicators…

Condensed Matter · Physics 2009-11-07 M. Ausloos , K. Ivanova

High-dimensional time series are a core ingredient of the statistical modeling toolkit, for which numerous estimation methods are known.But when observations are scarce or corrupted, the learning task becomes much harder.The question is:…

Signal Processing · Electrical Eng. & Systems 2022-05-06 Guillaume Dalle , Yohann de Castro

Time-averaged autocorrelation functions of a dichotomous random process switching between 1 and 0 and governed by wide power law sojourn time distribution are studied. Such a process, called a L\'evy walk, describes dynamical behaviors of…

Statistical Mechanics · Physics 2007-05-23 Gennady Margolin , Eli Barkai

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure.…

Neural and Evolutionary Computing · Computer Science 2009-06-29 Siddhivinayak Kulkarni , Imad Haidar

Trading volume movement prediction is the key in a variety of financial applications. Despite its importance, there is few research on this topic because of its requirement for comprehensive understanding of information from different…

Statistical Finance · Quantitative Finance 2021-08-26 Liang Zhao , Wei Li , Ruihan Bao , Keiko Harimoto , YunfangWu , Xu Sun

Prediction is a key issue in time series analysis. Just as classical mean regression models, classical autoregressive methods, yielding L$^2$ point-predictions, provide rather poor predictive summaries; a much more informative approach is…

Statistics Theory · Mathematics 2025-10-06 Alberto González-Sanz , Marc Hallin , Yisha Yao

Machine learning models deployed in real-world applications are often evaluated with precision-based metrics such as F1-score or AUC-PR (Area Under the Curve of Precision Recall). Heavily dependent on the class prior, such metrics make it…

Machine Learning · Computer Science 2020-04-29 Wissam Siblini , Jordan Fréry , Liyun He-Guelton , Frédéric Oblé , Yi-Qing Wang
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