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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.

168,742 papers · 148 categories

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4999148197 · Jun 202019922001200920172026
48 results for periodic behavior

This paper reveals periodic behavior in neural network training with BN and weight decay.

problem Understanding the dynamics of neural network training with BN and weight decay.
method Rigorous investigation of empirical and theoretical mechanisms.
result Periodic behavior in training is a generalization of previously opposing perspectives.

Log-periodic oscillations have been used to predict price trends and crashes on financial markets. So far two types of log-periodic oscillations have been associated with the real markets. The first type are oscillations which accompany a rising market and which ends in a crash. The second type oscillations, called "an…

2003-07-14abs ↗pdf ↗

Empirical study shows carriers ignore past shippers' behavior, focusing only on current actions.

problem Opportunistic behavior by shippers and carriers in dynamic freight markets.
method Empirical analysis of carrier reciprocity in US truckload transportation sector.
result Carriers do not remember shippers' past behaviors but respond to current actions.

Model explains herding and volatility in urban housing prices.

problem Understanding non-linear price dynamics in urban housing markets.
method Agent-based model with rational households and trend-following behavior.
result Model accurately predicts price variability and herding behavior.

The paper analyzes the non-Gaussian behavior of inflation and unemployment over 70 years using multifractal methods.

problem Capturing unusual fluctuations in inflation and unemployment over long periods.
method Coupled multifractal approach to analyze non-Gaussian distributions of inflation and unemployment over 70 years.
result The non-Gaussianity of unemployment is noticeable only for periods smaller than 1 year, while inflation's non-Gaussianity persists across all time scales.

The paper uses persistent homology to estimate recurrence times in multi-variate time series.

problem Estimating recurrence times in multi-variate time series with different cyclic behaviors.
method Persistent homology framework with three specialized methods.
result Validated methods on real-world data, including a new benchmark dataset.

Critical learning periods found in deep linear networks too.

problem Understanding why critical learning periods emerge in both biological and artificial networks.
method Focused on deep linear network models, analyzed depth and data distribution, and examined multi-task learning.
result Critical periods depend on model depth and data distribution structure, and pre-training can affect transfer performance.

To identify emerging interdependencies between traded stocks we investigate the behavior of the stocks of FTSE 100 companies in the period 2000-2015, by looking at daily stock values. Exploiting the power of information theoretical measures to extract direct influences between multiple time series, we compute the infor…

2016-11-08abs ↗pdf ↗

The main result is a computation of the Nahm transform of a SU(2)-instanton over RxT^3, called spatially-periodic instanton. It is a singular monopole over T^3, a solution to the Bogomolny equation, whose rank is computed and behavior at the singular points is described.

2004-10-26abs ↗pdf ↗

This letter revisits the informational efficiency of the Bitcoin market. In particular we analyze the time-varying behavior of long memory of returns on Bitcoin and volatility 2011 until 2017, using the Hurst exponent. Our results are twofold. First, R/S method is prone to detect long memory, whereas DFA method can dis…

2017-09-23abs ↗pdf ↗

Relative moduli spaces of periodic monopoles provide novel examples of Asymptotically Locally Flat hyperkahler manifolds. By considering the interactions between well-separated periodic monopoles, we infer the asymptotic behavior of their metrics. When the monopole moduli space is four-dimensional, this construction yi…

2001-09-19abs ↗pdf ↗

Extends tracking guarantees for time-varying variational inequalities.

problem Tracking solutions of time-varying variational inequalities.
method Extends existing results to sublinear solution paths and periodic problems.
result Discrete dynamical systems of periodic time-varying VI can exhibit chaotic behavior or converge to the solution.

We propose and analyze numerically a simple dynamical model that describes the firm behaviors under uncertainty of demand forecast. Iterating this simple model and varying some parameters values we observe a wide variety of market dynamics such as equilibria, periodic and chaotic behaviors. Interestingly the model is a…

2017-01-23abs ↗pdf ↗

This paper presents empirical evidence using recently developed techniques in econophysics suggesting that the degree of long-range dependence in interest rates depends on the conduct of monetary policy. We study the term structure of interest rates for the US and find evidence that global Hurst exponents change dramat…

2006-07-26abs ↗pdf ↗

Through the analysis of a dataset of ultra high frequency order book updates, we introduce a model which accommodates the empirical properties of the full order book together with the stylized facts of lower frequency financial data. To do so, we split the time interval of interest into periods in which a well chosen r…

2013-12-02abs ↗pdf ↗

We introduce a mathematical criterion defining the bubbles or the crashes in financial market price fluctuations by considering exponential fitting of the given data. By applying this criterion we can automatically extract the periods in which bubbles and crashes are identified. From stock market data of so-called the …

2006-08-01abs ↗pdf ↗

A graph GG is said to be pp-periodic, if the automorphism group Aut(G)Aut(G) contains an element of order pp which preserves no edges. In this paper, we investigate the behavior of graph polynomials (Negmai and Tutte) with respect to graph periodicity. In particular, we prove that if pp is a prime, then the coefficient…

2011-03-31abs ↗pdf ↗

Researchers adaptively analyze market regimes to reveal investor behavior shifts.

problem Market relationships shift across different regimes, affecting investor behavior.
method Combining Kalman filtering, Markov-switching, and asymmetric response estimation.
result Foreign investors' predictive power increases during crises, while individual investors react more strongly to positive shocks.

The study examines cross-border lending behavior from G7 countries, showing changes in driving factors after the 2008 financial crisis.

problem Understanding the factors affecting cross-border lending behavior among G7 countries.
method Employed a gravity model to analyze bilateral and global factors influencing cross-border lending.
result Driving factors for cross-border lending have changed since the 2008 financial crisis, with continent variable becoming more significant.

Calendar graph neural networks model user behavior with location and time data.

problem Modeling user behavior with location and time information for demographic prediction.
method Graph neural networks with a tripartite network of items, sessions, and locations, and a hierarchical calendar network.
result User embeddings preserve spatial and temporal patterns of various periodicity.

This paper addresses the problem of change-point detection on sequences of high-dimensional and heterogeneous observations, which also possess a periodic temporal structure. Due to the dimensionality problem, when the time between change-points is on the order of the dimension of the model parameters, drifts in the und…

2018-09-11abs ↗pdf ↗

Using ultra-high-frequency data extracted from the order flows of 23 stocks traded on the Shenzhen Stock Exchange, we study the empirical regularities of order placement in the opening call auction, cool period and continuous auction. The distributions of relative logarithmic prices against reference prices in the thre…

2007-12-06abs ↗pdf ↗

Learning three data points can generate all types of periodic orbits in a neural network.

problem Can learning three data points generate all types of periodic orbits in a neural network?
method Investigated a continuous one-dimensional map with period three in a random neural network in its thermodynamic limit.
result Almost all learned periods are unstable, and each network has its own characteristic attractors.

This note summarizes results that were obtained by the author in his habilitation thesis (arXiv:1607.08792) concerning the development of a spectral theory for simply periodic, 2-dimensional, complex-valued solutions of the sinh-Gordon equation. Spectral data for such solutions are defined for periodic Cauchy data on a…

2017-01-11abs ↗pdf ↗

Gold prices show seasonal behavior, with January and July having opposite returns.

problem Seasonal behavior in gold prices during the turn of the year.
method Statistical analysis and decomposition techniques.
result Gold prices exhibit strong cyclical behavior during the turn-of-the-year period, with January showing the highest return and July showing significant negative returns.

The paper proposes a dynamic risk measure approach for evaluating defined-contribution pension funds.

problem Periodic evaluation of defined-contribution pension funds to manage risk and improve projections.
method Dynamic risk measure criterion, model-free reinforcement learning, Lee-Carter mortality model.
result Periodic evaluations lead to more risk-averse strategies, while mortality improvements encourage risk-seeking behaviors.

The presence of log-periodic structures before and after stock market crashes is considered to be an imprint of an intrinsic discrete scale invariance (DSI) in this complex system. The fractal framework of the theory leaves open the possibility of observing self-similar log-periodic structures at different time scales.…

2005-01-21abs ↗pdf ↗

Study on investment strategy for agents with periodic preferences and discounting.

problem Investment decisions by agents with periodic S-shaped preferences and present bias.
method Infinite-horizon, continuous-time portfolio selection problem with quasi-hyperbolic discounting.
result Time-consistent planning strategy can be formulated as an equilibrium to a static mean field game.

We study the distribution of fluctuations over a time scale ΔtΔt (i.e., the returns) of the S&P 500 index by analyzing three distinct databases. Database (i) contains approximately 1 million records sampled at 1 min intervals for the 13-year period 1984-1996, database (ii) contains 8686 daily records for the 35-year pe…

1999-05-20abs ↗pdf ↗

A generalized complex manifold which satisfies the \partial \overline{\partial}-lemma admits a Hodge decomposition in twisted cohomology. Using a Courant algebroid theoretic approach we study the behavior of the Hodge decomposition in smooth and holomorphic families of generalized complex manifolds. In particular we …

2012-05-01abs ↗pdf ↗

Generative model captures repetitive industrial processes with varying durations and dynamics.

problem Capturing repetitive industrial processes with varying durations and dynamics using Gaussian Processes.
method Posterior-weighted Gaussian Process with a novel kernel to decouple intra-repetition and inter-repetition variability.
result Generative model produces realistic synthetic trajectories from toy datasets.

Modeling financial bubbles and crashes with a cubic momentum function.

problem Capturing the micro-level dynamics of investor behavior and panic selling.
method Introducing a cubic function of market momentum to model trend-following and sudden crashes.
result The model successfully replicates complex, nonlinear bubble dynamics.

We construct most symmetric Saddle towers in Heisenberg space i.e. periodic minimal surfaces that can be seen as the desingularization of vertical planes intersecting equiangularly. The key point is the construction of a suitable barrier to ensure the convergence of a family of bounded minimal disks. Such a barrier is …

2014-06-25abs ↗pdf ↗

Exponential inequalities are main tools in machine learning theory. To prove exponential inequalities for non i.i.d random variables allows to extend many learning techniques to these variables. Indeed, much work has been done both on inequalities and learning theory for time series, in the past 15 years. However, for …

2018-08-27abs ↗pdf ↗

Imitative and contrarian behaviors are the two typical opposite attitudes of investors in stock markets. We introduce a simple model to investigate their interplay in a stock market where agents can take only two states, bullish or bearish. Each bullish (bearish) agent polls m "friends'' and changes her opinion to bear…

2001-09-21abs ↗pdf ↗

We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes t…

2006-01-31abs ↗pdf ↗

For n5n \geq 5, we consider positive solutions uu of the biharmonic equation \[ Δ^2 u = u^\frac{n+4}{n-4} \qquad \text{on}\ \mathbb R^n \setminus \{0\} \] with a non-removable singularity at the origin. We show that xn42u|x|^{\frac{n-4}{2}} u is a periodic function of lnx\ln |x| and we classify all periodic functions obta…

2017-11-02abs ↗pdf ↗