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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.

169,291 papers · 148 categories

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4181122162 · Jun 202019922001200920182026
48 results for time-periodic field

Study finds solutions for spacetimes with negative cosmological constant.

problem Existence of spacetimes with negative cosmological constant.
method Proved existence of solutions for Einstein-complex scalar field equations.
result Found large families of solutions with negative cosmological constant.

We construct one-parameter families of solutions to the Einstein--Klein--Gordon equations bifurcating off the Kerr solution such that the underlying family of spacetimes are each an asymptotically flat, stationary, axisymmetric, black hole spacetime, and such that the corresponding scalar fields are non-zero and time-p…

2015-10-27abs ↗pdf ↗

Paper introduces Floer theory for field theories, proving periodic solutions for particle-field systems.

problem Defining Hamiltonian Floer theory for covariant field theories, especially those with degenerate action functionals.
method Regularization procedure to handle degeneracy, leading to Floer curves that converge to periodic solutions.
result Existence of Floer curves and space-time periodic solutions for coupled particle-field systems.

No time-periodic Majorana fermions found in Kerr-Newman spacetimes with nontrivial charge.

problem Existence of Majorana fermions in Kerr-Newman spacetimes with nontrivial charge.
method Analysis of Dirac equation in Kerr-Newman spacetimes, leading to algebraic identities.
result No differentiable time-periodic Majorana fermions in Kerr-Newman spacetimes with nontrivial charge.

We provide a geometric framework for the construction of non-vacuum black holes whose metrics are stationary and axisymmetric. Under suitable assumptions we show that the Einstein equations reduce to an Einstein-harmonic map type system and analyze the compatibility of the resulting equations. This framework will be fu…

2015-10-27abs ↗pdf ↗

We prove that smooth asymptotically flat solutions to the Einstein vacuum equations which are assumed to be periodic in time, are in fact stationary in a neighborhood of infinity. Our result applies under physically relevant regularity assumptions purely at the level of the initial data. In particular, our work removes…

2015-04-17abs ↗pdf ↗

GBST model improves credit risk quantification using survival analysis.

problem Quantifying credit risk in heterogeneous consumer finance data.
method Gradient boosting survival tree (GBST) model integrating survival analysis and gradient boosting.
result GBST model outperforms existing survival models in credit risk quantification.

The cohomology theory for financial market can allow us to deform Kolmogorov space of time series data over time period with the explicit definition of eight market states in grand unified theory. The anti-de Sitter space induced from a coupling behavior field among traders in case of a financial market crash acts like…

2016-06-09abs ↗pdf ↗

Constructs periodic solutions for wave equations, including Einstein's, with negative cosmological constant.

problem Finding periodic solutions for nonlinear wave equations, especially Einstein's equations with negative cosmological constant.
method Analytic continuation to construct periodic solutions.
result Infinite-dimensional families of time-periodic solutions for vacuum and Einstein-Maxwell-dilaton-scalar fields.

This study examines how ChiNext IPOs' initial returns are influenced by regulation regime changes.

problem Investors' behavior and pricing of ChiNext IPOs under different regulation regimes.
method Analysis of three time periods with two different regulation regimes and three sets of listing day trading restrictions.
result Regulation regime changes significantly impact ChiNext IPO pricing and overreaction.

Paper uses DRL for dynamic pricing on e-commerce platforms.

problem Dynamic pricing on e-commerce platforms.
method Deep reinforcement learning, Markov Decision Process (MDP), continuous price sets, difference of revenue conversion rates (DRCR).
result DRCR is a more appropriate reward function than revenue.

Gaussian processes improved for ocean current reconstruction and divergence identification.

problem Reconstructing ocean currents from sparse buoy data.
method Proposed a Helmholtz decomposition-based approach to Gaussian processes for better physical modeling.
result Improved inference on ocean currents and divergence identification with minimal computational cost.

Study measures economic growth sources in Iran's mining sector using neoclassical growth accounting.

problem Determining the share of economic growth sources in Iran's mining sector.
method Neoclassical growth accounting approach, using production function and Solow residual equation.
result Average annual growth rate of TFP was 2.94% over 30 years.

Investigates the relationship between US money supply and asset indices over 2001-2019.

problem Determining the relationship between US money supply and asset indices growth.
method Information entropy methodology applied to US asset indices (Property, Russell 2000, S&P 500, NASDAQ) over 2001-2019.
result Growth in US broad money supply is the main determinant of US asset indices growth, especially the NASDAQ and Russell 2000.

Study improves S&P 500 volatility forecasting through regime-switching methods.

problem Accurate prediction of S&P 500 volatility for risk management and investment.
method Regime-switching methods including soft Markov switching, spectral clustering, and coefficient-based clustering.
result Coefficient-based clustering algorithm outperformed other models during all time periods.

This review covers predictive uncertainty estimation in machine learning.

problem Improving the communication of uncertainty in machine learning predictions.
method A comprehensive review of probabilistic prediction methods from early statistical models to recent machine learning algorithms.
result The review highlights the importance of consistent scoring functions and proper scoring rules for assessing probabilistic predictions.

New visual tool detects financial market changes using multiscaling analysis.

problem Detecting relevant changes in financial time series.
method Time-dependent Generalized Hurst Exponents (GHE) and Change-Point Analysis.
result Identifies patterns distinguishing between uniscaling and multiscaling, and provides warning signals.

Network anomaly detection is still a vibrant research area. As the fast growth of network bandwidth and the tremendous traffic on the network, there arises an extremely challengeable question: How to efficiently and accurately detect the anomaly on multiple traffic? In multi-task learning, the traffic consisting of flo…

2014-03-17abs ↗pdf ↗

New MSMs model time-series data with tensors to handle heterogeneity and longer intervals.

problem Causal inference from time-series data with subject heterogeneity and scalability issues.
method Proposes a new family of MSMs using a three-dimensional tensor of low rank, allowing dimensions to grow with data.
result The proposed method converges to the true model under certain conditions and can be efficiently solved.

An empirical analysis of interest rates in money and capital markets is performed. We investigate a set of 34 different weekly interest rate time series during a time period of 16 years between 1982 and 1997. Our study is focused on the collective behavior of the stochastic fluctuations of these time-series which is in…

2004-01-23abs ↗pdf ↗

Paper tackles temporal overfitting in wind power curve modeling.

problem Temporal overfitting in wind power curve modeling.
method Proposes a Gaussian process-based method to partition and model time-invariant and time-varying components.
result Significant improvement in predicting responses for different time periods.

FinTMMBench benchmarks RAG systems for finance tasks across multiple data types and time periods.

problem Evaluating temporal-aware multi-modal retrieval augmented generation in finance.
method TMMHybridRAG method that converts and integrates data from various modalities and temporal information.
result Demonstrated effectiveness of TMMHybridRAG in diverse financial analysis tasks.

The paper models US inflation and hyperinflation using monetary and GDP data.

problem Understanding and predicting inflation and hyperinflation.
method Developed economic models to predict US CPI growth based on BMS, GDP, and savings.
result An exact relationship between CPI growth and BMS growth minus GDP and savings growth was found, with a residual term.

In this paper, we establish a fluid limit for a two--sided Markov order book model. Our main result states that in a certain asymptotic regime, a pair of measure-valued processes representing the "sell-side shape" and "buy-side shape" of an order book converges to a pair of deterministic measure-valued processes in a c…

2014-11-27abs ↗pdf ↗

Derives a new formula for measuring risk aversion in markets.

problem Measuring the degree of risk aversion in markets accurately.
method Closed-form expression based on three variables: Treasury yields, returns, and market capitalization.
result Investors exhibit Decreasing Absolute Risk Aversion (DARA) but the degree of Relative Risk Aversion (RRA) varies.

Improved binomial model for American put prices with error analysis.

problem Improving the accuracy of American put price approximations.
method Binomial approximation in the Black-Scholes model with consideration of continuous dividend yield.
result Error in approximation is O((lnn)α/n)O((ln n) ^{α} /n), where α depends on interest rate and dividend yield.

A simple quantum model explains the Levy-unstable distributions for individual stock returns observed by ref.[1]. The probability density function of the returns is written as the squared modulus of an amplitude. For short time intervals this amplitude is proportional to a Cauchy-distribution and satisfies the Schroedi…

2002-05-20abs ↗pdf ↗

Study optimizes resource allocation in noisy systems for better control.

problem Limited attention in stochastic systems with multiplicative noise.
method Analytical and numerical methods for optimal attention allocation.
result Effective resource allocation enhances noise estimation and control decisions.

New policy optimizes product assortment in the presence of unpredictable customers.

problem Optimizing product assortment in the presence of outlier customers.
method Developed a robust online assortment optimization policy using an active elimination strategy.
result Established upper and lower bounds on regret, showing optimality up to logarithmic factor in TT.