arXiv research

Study proves stability of big bang singularity in complex system.

We establish regularity results for critical points to energies of immersed surfaces depending on the first and the second fundamental form exclusively. These results hold for a large class of intrinsic elliptic Lagrangians which are sub-critical or critical. They are derived using uniform $ε-$regularity estimates whic…

We construct solutions of the constraint equation with non constant mean curvature on an asymptotically hyperbolic manifold by the conformal method. Our approach consists in decreasing a certain exponent appearing in the equations, constructing solutions of these sub-critical equations and then in letting the exponent …

We generalize the notion of integral Menger curvature introduced by Gonzalez and Maddocks by decoupling the powers in the integrand. This leads to a new two-parameter family of knot energies $intM^{p,q}$. We classify finite-energy curves in terms of Sobolev-Slobodeckij spaces. Moreover, restricting to the range of para…

In this article we introduce and investigate a new two-parameter family of knot energies $TP^{(p,q)}$ that contains the tangent-point energies. These energies are obtained by decoupling the exponents in the numerator and denominator of the integrand in the original definition of the tangent-point energies. We will firs…

In this paper we investigate the properties of a semi-linear problem on a spin manifold involving the Dirac operator, through the construction of Rabinowitz-Floer homology groups. We give several existence results for sub-critical and critical non-linearities as application of the computation of the different homologie…

Paper analyzes weak-to-strong generalization in CNNs, identifying data-scarce and data-abundant regimes.

We present a quantitative characterisation of the fluctuations of the annualized growth rate of the real US GDP per capita growth at many scales, using a wavelet transform analysis of two data sets, quarterly data from 1947 to 2015 and annual data from 1800 to 2010. Our main finding is that the distribution of GDP grow…

Study shows how close functions are to optimal in Riemannian manifolds.

We define functionals generalising the Seiberg-Witten functional on closed $spin^c$ manifolds, involving higher order derivatives of the curvature form and spinor field. We then consider their associated gradient flows and, using a gauge fixing technique, are able to prove short time existence for the flows. We then pr…

This paper improves risk control for financial markets by calibrating VaR forecasts using conformal methods.

Model predicts global financial market risks and asset allocation.

We analyze the Standard & Poor's 500 stock market index from the last 22 years. The probability density function of price returns exhibits two well-distinguished regimes with self-similar structure: the first one displays strong super-diffusion together with short-time correlations, and the second one corresponds to we…

We study the geodesic distance induced by right-invariant metrics on the group $\operatorname{Diff}_c(M)$ of compactly supported diffeomorphisms of a manifold $M$, and show that it vanishes for the critical Sobolev norms $W^{s,n/s}$, where $n$ is the dimension of $M$ and $s\in(0,1)$. This completes the proof that the g…

Decomposing market impact into diffusive components

Study symplectic embeddings of 4-manifolds using Lefschetz fibrations.

New method clusters financial time series into volatility regimes.

We study convergence properties of the full truncation Euler scheme for the Cox-Ingersoll-Ross process in the regime where the boundary point zero is inaccessible. Under some conditions on the model parameters (precisely, when the Feller ratio is greater than three), we establish the strong order 1/2 convergence in $L^…

Combinatorial dimensions play an important role in the theory of machine learning. For example, VC dimension characterizes PAC learning, SQ dimension characterizes weak learning with statistical queries, and Littlestone dimension characterizes online learning. In this paper we aim to develop combinatorial dimensions th…

Stochastic-gradient-based optimization has been a core enabling methodology in applications to large-scale problems in machine learning and related areas. Despite the progress, the gap between theory and practice remains significant, with theoreticians pursuing mathematical optimality at a cost of obtaining specialized…

Neural networks learn task-specific features, influenced by nonlinearity.

Data pruning algorithms struggle in high compression regimes, as shown by theoretical and empirical studies.

The Financial Chaos Index models stock market volatility across three regimes based on mutual price fluctuations.

Three training regimes found for scale-invariant neural networks on the sphere.

Model shows stock markets can be inefficiently mispriced.

Based on the tick-by-tick stock prices from the German and American stock markets, we study the statistical properties of the distribution of the individual stocks and the index returns in highly collective and noisy intervals of trading, separately. We show that periods characterized by the strong inter-stock coupling…

Two price regimes identified in limit order books: close and far from quotes.

Volatility forecasting and return prediction in high-frequency Chinese equity markets.

ALO-CV approximates leave-one-out error in proportional regime.

FR-LUX optimizes portfolio management by learning cost-aware policies robust to market conditions.

This study uses HMM and RL to dynamically allocate equities, Treasuries, and gold based on market regimes.

Randomized classifiers outperform deterministic ones in robustness against adversarial attacks.

One-bit quantization and sparsification improve multiclass classification with strong regularization.

The intraday pattern, long memory, and multifractal nature of the intertrade durations, which are defined as the waiting times between two consecutive transactions, are investigated based upon the limit order book data and order flows of 23 liquid Chinese stocks listed on the Shenzhen Stock Exchange in 2003. An inverse…

Optimal treatment regimes (OTR) are individualised treatment assignment strategies that identify a medical treatment as optimal given all background information available on the individual. We discuss Bayes optimal treatment regimes estimated using a loss function defined on the bivariate distribution of dichotomous po…

Study shows how a strong model can learn a task's feature while retaining other capabilities.

Proves long-time Ricci flow existence and topological rigidity for pinched integral curvature manifolds.

New findings show privacy affects generalization error in a non-monotonic way.

The study uses Ricci flow to prove flatness of certain Riemannian manifolds.

Theory captures feature learning effects in finite CNNs.

A remarkable similarity in the behavior of the US S&P500 index from 1996 to August 2002 and of the Japanese Nikkei index from 1985 to 1992 (11 years shift) is presented, with particular emphasis on the structure of the bearish phases. Extending a previous analysis of Johansen and Sornette [1999, 2000] on the Nikkei ind…

Hybrid AI system combines technical, sentiment analysis for adaptive equity trading.

We study minority games in efficient regime. By incorporating the utility function and aggregating agents with similar strategies we develop an effective mesoscale notion of state of the game. Using this approach, the game can be represented as a Markov process with substantially reduced number of states with explicitl…

The paper reveals three mechanisms for weak-to-strong generalization.

Many fits of Hawkes processes to financial data look rather good but most of them are not statistically significant. This raises the question of what part of market dynamics this model is able to account for exactly. We document the accuracy of such processes as one varies the time interval of calibration and compare t…

The paper establishes Sobolev inequalities between Riemannian metrics and their distance functions.

A new adaptive splitting method improves accuracy for Cox-Ingersoll-Ross model.

Our analysis of financial data, in terms of super-exponential growth, suggests that the seed of the 2002/03 crisis of the Dutch supermarket giant AHOLD was planted in 1996. It became quite visible in 1999 when the post-bubble destabilization regime was well-developed and acted as the precursor of an inevitable collapse…