arXiv research

The paper investigates the singularity and extendibility of inflationary spacetimes.

New findings show cosmological constant as initial condition for non-isotropic spacetimes.

A proof is given that the maximal Fermi coordinate chart for any comoving observer in a broad class of Robertson-Walker spacetimes consists of all events within the cosmological event horizon, if there is one, or is otherwise global. Exact formulas for the metric coefficients in Fermi coordinates are derived. Sharp uni…

Investigates optimal life insurance and annuity decisions in inflationary economies.

Study shows inflation in 3+1D cosmologies with bounded scalar potential and specific symmetry.

Milne-like spacetimes are a class of FLRW models which admit $C^0$ spacetime extensions through the big bang. The boundary of a Milne-like spacetime can be identified with a null cone in the extension. We find that the comoving observers all emanate from a single point in the extension. This suggests that something phy…

The stability of money value is an important requisite for a functioning economy, yet it critically depends on the actions of participants in the market themselves. Here we model the value of money as a dynamical variable that results from trading between agents. The basic trading scenario can be recast into an Ising t…

The paper proposes a new model for financial order books without assuming prices or quantities.

The paper analyzes global inflation's systemic nature and its impact on equity markets.

Inflationary flows use DBMs for accurate Bayesian inference.

Study uses social network data to analyze regional inflation trends.

The main goal of this paper is to define a 1-1 correspondence between between substitution tilings constructed by inflation and the arithmetic of positional representation in the underlying real vector space. It introduces a generalization of inflationary tessellations to equivalence classes of tiles. Two tiles belong …

The aim of this paper is to compare statistical properties of a bubble period with those of the anti-bubble period in stock markets. We investigate the statistical properties of daily data for the Nikkei 225 index in the 28-year period from January 1975 to April 2003, corresponded to the periods of bubbles and anti-bub…

This paper is intended as an investigation of the statistical properties of {\it absolute log-returns}, defined as the absolute value of the logarithmic price change, for the Nikkei 225 index in the 28-year period from January 4, 1975 to December 30, 2002. We divided the time series of the Nikkei 225 index into two per…

New cosmological models with changing curvature slices.

Bitcoin reacts negatively to inflation surprises, contrary to belief.

This paper analyzes microstructure dynamics in coupled markets using CFMMs.

In general relativity, an IDEAL (Intrinsic, Deductive, Explicit, ALgorithmic) characterization of a reference spacetime metric $g_0$ consists of a set of tensorial equations $T[g]=0$, constructed covariantly out of the metric $g$, its Riemann curvature and their derivatives, that are satisfied if and only if $g$ is loc…

The analysis of dollar inflation performed by the authors through the approximation of empirical data for 1913-2012 with a power-law function with an accelerating log-periodic oscillation superimposed over it has made it possible to detect a quasi-singularity point around the 17th of December, 2012. It is demonstrated …

We present a novel analysis extending the recent work of Mizuno et al. [2002] on the hyperinflations of Germany (1920/1/1-1923/11/1), Hungary (1945/4/30-1946/7/15), Brazil (1969-1994), Israel (1969-1985), Nicaragua (1969-1991), Peru (1969-1990) and Bolivia (1969-1985). On the basis of a generalization of Cagan's model …

Research in deep learning for multi-speaker source separation has received a boost in the last years. However, most studies are restricted to mixtures of a specific number of speakers, called a specific scenario. While some works included experiments for different scenarios, research towards combining data of different…

Over the last two decades, many unexpected relations between exotic smoothness, e.g. exotic $\mathbb{R}^{4}$, and quantum field theory were found. Some of these relations are rooted in a relation to superstring theory and quantum gravity. Therefore one would expect that exotic smoothness is directly related to the quan…

Two new methods score stress test scenarios for risk managers.

Investigates cryptocurrency maturity through collective dynamics and diversification.

Extracts representative scenarios from large data panels.

Methodology measures financial impacts using existing credit loss infrastructure.

Proposes a new framework for environmental CVA with robust wrong-way risk.

This paper formed part of a preliminary research report for a risk consultancy and academic research. Stochastic Programming models provide a powerful paradigm for decision making under uncertainty. In these models the uncertainties are represented by a discrete scenario tree and the quality of the solutions obtained i…

Statistical depth metrics help identify risky power grid scenarios.

Two autoencoding models learn latent traffic scene representations.

A new method using energy distance for ensemble and scenario reduction.

Develops a method for reverse stress testing in multivariate scenarios.

Method generates plausible financial stress scenarios using large deviations.

Scenario discovery is the process of finding areas of interest, known as scenarios, in data spaces resulting from simulations. For instance, one might search for conditions, i.e., inputs of the simulation model, where the system is unstable. Subgroup discovery methods are commonly used for scenario discovery. They find…

Generates multimodal safety-critical scenarios for robustness evaluation of decision-making algorithms.

Adaptive framework generates challenging adversarial scenarios for autonomous vehicles.

We treat the so-called scenario approach, a popular probabilistic approximation method for robust minmax optimization problems via independent and indentically distributed (i.i.d) sampling from the uncertainty set, from various perspectives. The scenario approach is well-studied in the important case of convex robust o…

Algorithm reduces historical expected shortfall computation by focusing on worst-case scenarios.

Risk measures such as Expected Shortfall (ES) and Value-at-Risk (VaR) have been prominent in banking regulation and financial risk management. Motivated by practical considerations in the assessment and management of risks, including tractability, scenario relevance and robustness, we consider theoretical properties of…

Paper proposes a copula method to generate unfavorable VaR scenarios.

Study optimal timing to divest from assets with uncertain future scenarios.

Researchers validate ML scenario generators by checking dependencies and detecting memorization effects.

Standard artificial neural networks suffer from the well-known issue of catastrophic forgetting, making continual or lifelong learning difficult for machine learning. In recent years, numerous methods have been proposed for continual learning, but due to differences in evaluation protocols it is difficult to directly c…

Naturalistic driving trajectories are crucial for the performance of autonomous driving algorithms. However, most of the data is collected in safe scenarios leading to the duplication of trajectories which are easy to be handled by currently developed algorithms. When considering safety, testing algorithms in near-miss…

This paper presents a method for testing the decision making systems of autonomous vehicles. Our approach involves perturbing stochastic elements in the vehicle's environment until the vehicle is involved in a collision. Instead of applying direct Monte Carlo sampling to find collision scenarios, we formulate the probl…

We define scenarios, propose different methods of aggregating them, discuss their properties and benchmark them against quadrant requirements.

In this paper we propose a problem-driven scenario generation approach to the single-period portfolio selection problem which use tail risk measures such as conditional value-at-risk. Tail risk measures are useful for quantifying potential losses in worst cases. However, for scenario-based problems these are problemati…

The paper proposes an efficient nested simulation design using likelihood ratio method.