In this paper we study the spectral asymmetry of (possibly nonselfadjoint) elliptic PsiDO's in terms of the difference of zeta functions coming from different cuttings. Refining previous formulas of Wodzicki in the case of odd class elliptic PsiDO's, our main results have several consequence concerning the local indepe…
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48 results for “Local Asymmetry”
Myopic investors make suboptimal choices that benefit others, leading to market inefficiencies.
problem Myopic investors make suboptimal decisions that lag the market.
method Constrained optimisation and overlapping examples of different investor types.
result Myopic investors' suboptimal choices lead to market inefficiencies and profit opportunities for others.
Researchers study spectral asymmetry using pseudodifferential projections on the massless Dirac operator.
problem Understanding spectral asymmetry for the massless Dirac operator.
method Constructing a negative order pseudodifferential asymmetry operator from spectral projections.
result Computed the principal symbol of the asymmetry operator, accounting for gauge invariance.
Develops a new approach to spectral asymmetry using microlocal analysis.
problem Spectral asymmetry on 3-manifolds.
method Constructs an asymmetry operator using microlocal analysis.
result The asymmetry operator generalizes the eta invariant and contains spectral asymmetry information.
Research builds an index measuring analysts' perception of informational asymmetry.
problem Measuring the level of informational asymmetry among companies.
method Developed an algorithm based on Elo rating to capture analysts' perception.
result The model shows good fit with significant variables: coverage, volatility, Tobin q, and size.
Distributed securities exchanges may become de facto fragmented if they span geographical regions with asymmetric computer infrastructure. First, we build an economic model of a decentralized exchange with two miner clusters, standing in for compact areas of economic activity (e.g., cities). "Local" miners in the area …
An efficient algorithm for aligning diffusion trees to networks with information asymmetry.
problem Aligning diffusion trees to networks with information asymmetry.
method Tree correlation tests for extracting alignment information.
result Explicit lower bounds on the probability of correct matches for each vertex on the diffusion tree.
Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returnsq-fin.ST
All too often measuring statistical dependencies between financial time series is reduced to a linear correlation coefficient. However this may not capture all facets of reality. We study empirical dependencies of daily stock returns by their pairwise copulas. Here we investigate particularly to which extent the non-st…
New measures detect asymmetries, non-linearity in stock returns.
problem Detecting asymmetries and non-linearity in stock returns.
method Proposed non-linear, local, invariant dependence measures; nonparametric estimator proven.
result Measures show tail asymmetry, non-linearity, risk buildup during market distress.
By decomposing asset returns into potential maximum gain (PMG) and potential maximum loss (PML) with price extremes, this study empirically investigated the relationships between PMG and PML. We found significant asymmetry between PMG and PML. PML significantly contributed to forecasting PMG but not vice versa. We furt…
The paper tackles multi-player information asymmetry bandits in metric spaces.
problem Information asymmetry in rewards, actions, or both in multiplayer bandit problems.
method Adopted CAB and zooming algorithms for information asymmetry in rewards and actions.
result Regret bounds of the same order in all 3 problem settings.
Bayesian analysis reveals asymmetry in financial data.
problem Quantifying asymmetry in financial time series data.
method Bayesian approach, t-Test generalization, two data distribution models, sensitivity analysis.
result Statistical significance of gain/loss asymmetry amounts.
Study finds time-varying volatility and multifractality in Bitcoin, with asymmetry weakening as market efficiency increases.
problem Investigating time-varying properties of Bitcoin's volatility and multifractality.
method Rolling window method to examine daily Bitcoin returns and multifractal properties over time.
result Volatility asymmetry in Bitcoin changes over time, becoming less pronounced as market efficiency increases.
Synthetic Augmentation in Imbalanced Learning: When It Helps, When It Hurts, and How Much to Addstat.ML
Synthetic augmentation helps but not always in imbalanced learning.
problem Imbalanced learning causes poor performance on rare classes.
method Developed a statistical framework for synthetic augmentation in imbalanced learning.
result Synthetic augmentation is not always beneficial and depends on the imbalance regime.
Research shows that information asymmetry affects how quickly companies adjust their capital structure and expected returns.
problem The relationship between capital structure adjustment speed and expected returns is influenced by information asymmetry.
method A hybrid data regression model was used to test the hypotheses based on data from 120 companies in the Tehran Stock Exchange.
result Information asymmetry positively affects the relationship between capital structure adjustment speed and expected returns.
The Finslerian extension of the Euclidean metric is proposed and studied under rigorous conditions that the associated indicatrix is regular and convex. The relativistic pseudo-Euclidean metric is extended, too. The extensions show distinct violation of the parity, so that the future-past asymmetry of the physical …
Novel threefold partitioning of -spinor space on cone links.
problem Understanding equivariant Riemann-Roch defects in complex spaces with conic singularities.
method Investigates supertraces over local cohomology groups and spectral asymmetry.
result Novel complex equivariant and invariants defined.
Leveraging reference-only samples for two-sample testing under size asymmetry
problem Two-sample testing under size imbalance
method Adaptive aggregation of reference-dependent representations
result Strong performance with type I error control
Inverse statistics in economics is considered. We argue that the natural candidate for such statistics is the investment horizons distribution. This distribution of waiting times needed to achieve a predefined level of return is obtained from (often detrended) historic asset prices. Such a distribution typically goes t…
Python package cegpy models processes with asymmetries.
problem Leveraging CEGs for processes with structural asymmetries.
method Developed cegpy, a Python package for CEGs with Bayesian model selection and probability propagation.
result First CEG package in any language that can model symmetric and asymmetric structures.
The study reveals asymmetries in US financial shocks' international impacts.
problem Analyzing nonlinearities in international financial spillovers.
method Developed a flexible nonlinear multi-country model to capture asymmetries in responses to financial shocks.
result Adverse shocks trigger stronger declines in output, inflation, and stock markets than benign shocks.
Time-reversal asymmetry in Cont-Bouchaud stock market modelcond-mat.stat-mech
The percolation model of stock market speculation allows an asymmetry (in the return distribution) leading to fast downward crashes and slow upward recovery. We see more small upturns and more intermediate downturns.
Asymmetry PRISM outperforms CPU and GPU solvers for institutional rebalancing.
problem Institutional rebalancing with deadline constraints
method Asymmetry PRISM
result Asymmetry PRISM-CPU is 4.5x to 24.1x faster than the fastest completed reference row in the same lane.
Investment horizon approach has been used to analyze indexes of Polish stock market.Optimal time horizon for each return value is evaluated by fitting appropriate function form of the distribution. Strong asymmetry of gain-loss curves is observed for WIG index, whereas gain and loss curves look similar for WIG20 and fo…
This paper tackles online strategic decision making with asymmetry and knowledge transportability.
problem Strategic decision making with information asymmetry and knowledge transportability challenges.
method Developed a sample-efficient algorithm for online learning under these conditions.
result Proved sample complexity of for learning an -optimal policy.
New method automates asymmetric choice for better skill transfer in reinforcement learning.
problem Improving sample efficiency and transferability of reinforcement learning agents.
method Attentive Priors for Expressive and Transferable Skills (APES) using hierarchical KL-regularization.
result APES automates asymmetric choice, leading to better skill transfer across sequential tasks.
We define a measure of spectral asymmetry for G_2 and Spin(7) manifolds. We show that this invariant can be computed in terms of characteristic classes and the covariant constant form defining the G_2 or Spin(7) structure.
We demonstrate that the gain/loss asymmetry observed for stock indices vanishes if the temporal dependence structure is destroyed by scrambling the time series. We also show that an artificial index constructed by a simple average of a number of individual stocks display gain/loss asymmetry - this allows us to explicit…
Market Mill is a complex dependence pattern leading to nonlinear correlations and predictability in intraday dynamics of stock prices. The present paper puts together previous efforts to build a dynamical model reflecting the market mill asymmetries. We show that certain properties of the conditional dynamics at a sing…
Previous research has shown that for stock indices, the most likely time until a return of a particular size has been observed is longer for gains than for losses. We establish that this so-called gain/loss asymmetry is present also for individual stocks and show that the phenomenon is closely linked to the well-known …
Gradient-based methods can be biased by distributional asymmetries in bivariate categorical data.
problem Gradient-based causal discovery methods can be biased by distributional asymmetries in bivariate categorical data.
method Identified and examined two distributional biases: Marginal Distribution Asymmetry and Marginal Distribution Shift Asymmetry. Employed two simple models to demonstrate and control these biases.
result Gradient-based methods can be biased by distributional asymmetries, and these biases can be controlled.
The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock marketsq-fin.ST
Study examines asymmetry impacts on Japanese stock market volatility modeling and forecasting.
problem Understanding asymmetry's impact on modeling and forecasting realized volatility in Japanese stock markets.
method Employed heterogeneous autoregressive (HAR) models with three types of asymmetry: positive and negative realized semivariance, asymmetric jumps, and leverage effects.
result Leverage effects significantly influence realized volatility modeling and forecast performance in Japanese stock markets.
The abstract discusses financial irreversibility using quantum mechanics and projective geometry.
problem Financial irreversibility and its limitations in trading strategies.
method Projective geometry and Taylor expansion of directed distance in quantum systems.
result Fundamental asymmetry under state exchange is a key factor in financial irreversibility.
New algorithms learn and interpret asymmetry-labeled DAGs for COVID-19 fear.
problem Bayesian networks' strict symmetric independence assumption limits their applicability in real-world scenarios.
method Developed novel structural learning algorithms for asymmetry-labeled DAGs.
result Efficient algorithms allow for straightforward interpretation of the underlying dependence structure.
A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenonphysics.soc-ph
Study shows gain-loss asymmetry in stock indices using a q-spin Potts model.
problem Understanding the dynamics of stock indices in complex markets.
method Developed a q-spin Potts model to represent stock market dynamics.
result Observed a self-organized gain-loss asymmetry in stock indices.
Local fluctuations of the signed traded volumes and the dependencies of demands: a copula analysisq-fin.TR
We investigate how the local fluctuations of the signed traded volumes affect the dependence of demands between stocks. We analyze the empirical dependence of demands using copulas and show that they are well described by a bivariate copula density function. We find that large local fluctuations strongly …
Researchers have studied the first passage time of financial time series and observed that the smallest time interval needed for a stock index to move a given distance is typically shorter for negative than for positive price movements. The same is not observed for the index constituents, the individual stocks. We use …
Recent studies have revealed a number of striking dependence patterns in high frequency stock price dynamics characterizing probabilistic interrelation between two consequent price increments x (push) and y (response) as described by the bivariate probability distribution P(x,y) [1,2,3,4]. There are two properties, the…
Fear and its implications for stock marketsphysics.data-an
The value of stocks, indices and other assets, are examples of stochastic processes with unpredictable dynamics. In this paper, we discuss asymmetries in short term price movements that can not be associated with a long term positive trend. These empirical asymmetries predict that stock index drops are more common on a…
There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous return-volatility correlation is positive). In this paper, we first confirm the exis…
New method calculates eta invariant without analytic continuation.
problem Spectral asymmetry of non-semibounded systems.
method Direct pseudodifferential technique for curl operator.
result Eta invariant can be traced as spectral projection difference.
Co-clustering for directed graphs: the Stochastic co-Blockmodel and spectral algorithm Di-Simstat.ML
Directed graphs have asymmetric connections, yet the current graph clustering methodologies cannot identify the potentially global structure of these asymmetries. We give a spectral algorithm called di-sim that builds on a dual measure of similarity that correspond to how a node (i) sends and (ii) receives edges. Using…
Paper uses bipartite graph to forecast cross-market returns, revealing asymmetry.
problem Cross-market return predictability and asymmetry between U.S. and Chinese markets.
method Directed bipartite graph capturing time-ordered linkages, hypothesis testing for edge selection, regularized and ensemble machine learning models.
result U.S. returns predict Chinese intraday returns, but not vice versa, revealing asymmetry.
Optimally estimates stability in Lorentzian isoperimetric inequalities.
problem Stability estimates in Lorentzian isoperimetric inequalities.
method Quantitative stability estimates using Fraenkel asymmetry and Lipschitz bounds.
result Optimal stability estimates with universal constants for Lorentzian isoperimetric inequalities.
Chinchilla Approach 2 biases neural scaling law estimates, leading to unnecessary compute costs.
problem Systematic biases in Chinchilla Approach 2's parabolic fits of neural scaling laws.
method Analyzes three sources of error: IsoFLOP sampling grid width, uncentered sampling, and loss surface asymmetry.
result Chinchilla Approach 3 largely eliminates these biases, offering a more convenient or scalable alternative.
This study examines local co-movements in energy, agriculture, and metal markets using copulas.
problem Identifying local dependencies and asymmetries in energy, agriculture, and metal markets.
method Non-parametric mixture copula and copula-based local Kendall's tau approach.
result Increased co-movements in extreme situations, asymmetric local dependence, and diversification potential.
Characterizing asymmetric and bimodal long-term financial return distributions through quantum walksq-fin.ST
Quantum walk model captures asymmetry and bimodality in long-term financial returns.
problem Inadequate classical models for long-term financial return distributions.
method Discrete-time quantum walk model.
result Captures bimodal and asymmetric probability distributions.
Bayesian networks are simplified for categorical variables using staged trees and asymmetry-labeled DAGs.
problem Representing non-symmetric conditional independences in Bayesian networks.
method Formalized relationship between Bayesian networks and staged trees, introduced asymmetry-labeled DAGs, and developed an algorithm to learn staged trees.
result A novel algorithm for learning staged trees that captures non-symmetric independences.