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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.

168,695 papers · 148 categories

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11223243 · Jun 202019922001200920172026
48 results for phenomenological richness

Ridge regression reveals surprising high-dimensional behaviors via random matrix theory.

problem Understanding power-law scalings in high-dimensional regression models.
method Random matrix theory and free probability.
result Analytic formulas for training and generalization errors derived from SS-transform.

A Kyle-inspired model with adaptive agents explains excess volatility and volatility clustering.

problem Reconciling asymmetrically informed traders with adaptive market hypothesis.
method Proposes a model with adaptive agents using inductive reasoning, reconciling Kyle model with Adaptive Market Hypothesis.
result Microfoundations for GARCH models and volatility clustering explained.

Efficient event generation for collider phenomenology using parallel Langevin sampling and learned Stein diagnostics.

problem Event generation for precision collider phenomenology.
method Parallel Langevin sampling with learned Stein diagnostics.
result Relaxation time is estimated using a data-driven approach.

Study detects P-type bifurcations in single system realizations using unreliable kernel density estimates.

problem Detecting P-type bifurcations in signals with unreliable kernel density estimates.
method Create persistence diagrams from single system realization, statistically analyze resulting set, compare point process modeling methods.
result Subsampling outperforms other point process modeling methods in predicting P-type bifurcations.

MaxEnt framework recovers standard model selection procedures and identifies the most generalizable model.

problem Model selection and characterization in data-scientific approaches.
method Starting from linear system of phenomenological constraints, asymptotically derive the distribution over all viable distributions.
result MaxEnt distribution is the most typical among all viable distributions and supports hypothesis testing in a fully-data driven manner.

We introduce a price impact model which accounts for finite market depth, tightness and resilience. Its coupled bid- and ask-price dynamics induce convex liquidity costs. We provide existence of an optimal solution to the classical problem of maximizing expected utility from terminal liquidation wealth at a finite plan…

2018-04-19abs ↗pdf ↗

We show that financial correlations exhibit a non-trivial dynamic behavior. We introduce a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affe…

2005-08-22abs ↗pdf ↗

We begin an exploration of parametric Backlund transformations for hyperbolic Monge-Ampere systems. We compute invariants for such transformations and explore the behavior of four examples regarding their invariants, symmetries, and conservation laws. We prove some preliminary results and indicate directions for furthe…

2002-08-05abs ↗pdf ↗

Noise-driven neural networks emerge modular structures, improving robustness and generalization.

problem Artificial neural networks struggle with modular solutions, leading to poor generalization and robustness.
method Inspired by brain's modular architecture, the study uses neural noise and nonlinear responses to drive the emergence of modular solutions.
result Noise-driven modularisation improves robustness and generalization in neural networks.

The study provides precise asymptotic theory for in-context learning by Transformers.

problem Understanding the sample complexity, pretraining task diversity, and context length for successful in-context learning.
method An exactly solvable model of linear regression task by linear attention, deriving sharp asymptotics.
result Double-descent learning curve with increasing pretraining examples, phase transition between low and high task diversity regimes.

Deep learning models can have low bias and variance, contrary to classical theory.

problem Understanding the performance of deep learning models at high complexity.
method Developed a fine-grained bias-variance decomposition for random feature kernel regression, analyzing the effects of sampling, initialization, and labels.
result The variance terms exhibit non-monotonic behavior and can diverge at the interpolation boundary, even in the absence of label noise.

Over the past three decades, black holes have played an important role in quantum gravity, mathematical physics, numerical relativity and gravitational wave phenomenology. However, conceptual settings and mathematical models used to discuss them have varied considerably from one area to another. Over the last five year…

2004-07-13abs ↗pdf ↗

This paper reviews some of the phenomenological models which have been introduced to incorporate the scaling properties of financial data. It also illustrates a microscopic model, based on heterogeneous interacting agents, which provides a possible explanation for the complex dynamics of markets' returns. Scaling and m…

2000-07-25abs ↗pdf ↗

A stochastic model for pure-jump diffusion (the compound renewal process) can be used as a zero-order approximation and as a phenomenological description of tick-by-tick price fluctuations. This leads to an exact and explicit general formula for the martingale price of a European call option. A complete derivation of t…

2012-02-20abs ↗pdf ↗

In the framework of Lorentzian warped products, we study the Friedmann-Robertson-Walker cosmological model to investigate non-smooth curvatures associated with multiple discontinuities involved in the evolution of the universe. In particular we analyze non-smooth features of the spatially flat Friedmann-Robertson-Walke…

2003-08-16abs ↗pdf ↗

The Epps effect helps distinguish between continuous and discrete financial tick data.

problem Determining whether financial tick data represents continuous or discrete events.
method Deriving and correcting the Epps effect, proposing experiments to discriminate between models.
result Tick data is better represented as discrete events rather than continuous Brownian diffusions.

This paper analyzes how diffusion models learn and generalize concepts.

problem Learning and generalizing concepts in compositional data-generating processes.
method Introduced a structured identity mapping (SIM) task to analyze neural network learning dynamics.
result SIM task captures key empirical observations on compositional generalization.

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 ↗

We introduce a combinatorial model based on measured foliations in surfaces which captures the phenomenology of open/closed string interactions. The predicted equations are derived in this model, and new equations can be discovered as well. In particular, several new equations together with known transformations genera…

2006-03-20abs ↗pdf ↗

New metric measures dynamical richness without relying on accuracy.

problem Lack of a reliable metric for measuring dynamical richness.
method Developed a computationally efficient, performance-independent metric based on low-rank bias.
result Metric recovers neural collapse as a special case and captures known transitions without accuracy.

In this paper are made some considerations of the application of phenomenological thermodynamics in risk analysis for the transaction on financial markets, using the concept of economic entropy and the macrostate parameter introduced by us in a previous works [15,16]. The investment risk diagrams for a number of Romani…

2011-01-24abs ↗pdf ↗

We discuss superstatistics theory of labour productivity. Productivity distribution across workers, firms and industrial sectors are studied empirically and found to obey power-distributions, in sharp contrast to the equilibrium theories of mainstream economics. The Pareto index is found to decrease with the level of a…

2008-09-21abs ↗pdf ↗

Heterotic vacua of string theory are realised, at large radius, by a compact threefold with vanishing first Chern class together with a choice of stable holomorphic vector bundle. These form a wide class of potentially realistic four-dimensional vacua of string theory. Despite all their phenomenological promise, there …

2016-05-17abs ↗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 ↗

Statistical mechanics explains learning in large neural networks near interpolation.

problem Understanding the learning dynamics of large neural networks near interpolation.
method Statistical physics analysis of a two-layer network with generic weight distribution and activation function.
result Learning transitions and feature learning emerge as the number of data increases.

Bayesian method identifies dynamical models with uncertainty quantification.

problem Uncertainty in selecting governing equations for dynamical systems.
method Bayesian sparse identification with model averaging.
result Accurately recovers sparse interaction structures with uncertainty quantification.

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 ↗

The article presents a translation of some widespread financial terminology into the language of decision theory. For instance, financial leverage can be regarded as an object of choice or a decision. We show how the optics of decision theory allows perceiving the recently introduced metrics of see-through-leverage, wh…

2010-09-15abs ↗pdf ↗

The present paper analyses the formal parallelism existing between the laws of thermodynamics and some economic principles. Based on previous works, we shall show how the existence in Economics of principles analogous to those in thermodynamics involves the occurrence of economic events that remind of well-known phenom…

2015-05-03abs ↗pdf ↗

Using an exhaustive list of Japanese bankruptcy in 1997, we discover a Zipf law for the distribution of total liabilities of bankrupted firms in high debt range. The life-time of these bankrupted firms has exponential distribution in correlation with entry rate of new firms. We also show that the debt and size are high…

2003-10-03abs ↗pdf ↗

We study a phenomenological model for the continuous double auction, equivalent to two independent M/M/1M/M/1 queues. The continuous double auction defines a continuous-time random walk for trade prices. The conditions for ergodicity of the auction are derived and, as a consequence, three possible regimes in the behavior …

2013-05-13abs ↗pdf ↗

Linear memory stores associations up to a logarithmic scale, but listwise retrieval can handle a quadratic scale.

problem How many key-value associations can a linear memory store?
method Analyzed linear memory models for top-1 and listwise retrieval, proving phase transitions and developing asymptotic theories.
result Linear memory has a logarithmic capacity for top-1 retrieval and a quadratic capacity for listwise retrieval.

This paper contains a phenomenological description of the whole U.S. forward rate curve (FRC), based on an data in the period 1990-1996. We find that the average FRC (measured from the spot rate) grows as the square-root of the maturity, with a prefactor which is comparable to the spot rate volatility. This suggests th…

1997-12-15abs ↗pdf ↗

Consider a Riemannian metric on two-torus. We prove that the question of existence of polynomial first integrals leads naturally to a remarkable system of quasi-linear equations which turns out to be a Rich system of conservation laws. This reduces the question of integrability to the question of existence of smooth (q…

2009-07-29abs ↗pdf ↗

The simplest field theory description of the multivariate statistics of forward rate variations over time and maturities, involves a quadratic action containing a gradient squared rigidity term. However, this choice leads to a spurious kink (infinite curvature) of the normalized correlation function for coinciding matu…

2004-03-29abs ↗pdf ↗

The mass, or binding energy, is the basis property of the atomic nucleus. It determines its stability, and reaction and decay rates. Quantifying the nuclear binding is important for understanding the origin of elements in the universe. The astrophysical processes responsible for the nucleosynthesis in stars often take …

2018-06-01abs ↗pdf ↗