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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.

168,742 papers · 148 categories

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60119179238 · Jun 202019922001200920172026
48 results for market behavior

The study examines collective behavior in banking sectors across mature and emerging markets.

problem Understanding collective behavior in banking sectors across different market types.
method Applied Random Matrix Theory (RMT) to analyze the banking sectors of 4 world stock markets.
result Mature markets exhibit higher collective behavior compared to emerging markets.

We study the relation between the trading behavior of agents and volatility in toy markets of adaptive inductively rational agents. We show that excess volatility, in such simplified markets, arises as a consequence of {\em i)} the neglect of market impact implicit in price taking behavior and of {\em ii)} excessive re…

2000-04-21abs ↗pdf ↗

Empirical study shows carriers ignore past shippers' behavior, focusing only on current actions.

problem Opportunistic behavior by shippers and carriers in dynamic freight markets.
method Empirical analysis of carrier reciprocity in US truckload transportation sector.
result Carriers do not remember shippers' past behaviors but respond to current actions.

Study models human investors' sub-rational behavior in financial markets.

problem Lack of a comprehensive model for human sub-rationality in financial markets.
method Flexible reinforcement learning model incorporating five human sub-rational aspects.
result Model accurately reproduces human behavior and reveals insights into market dynamics.

Study examines if LLMs' trading styles match real market behavior.

problem Lack of behavioral consistency in LLMs' trading strategies.
method Year-long simulations with LLMs, operationalizing behavioral finance drivers, and comparing with financial theory.
result LLMs' strategy switching is only partially consistent with behavioral finance theories.

AI agents in experimental markets exhibit behavioral patterns that aggregate into market dynamics.

problem Understanding AI trading behavior and its impact on market dynamics.
method Experimental asset markets populated by AI agents trained on Large Language Models (LLMs).
result AI agents' behavior leads to market dynamics similar to human traders, including bubbles.

We propose a simple stochastic model of market behavior. Dividing market participants into two groups: trend-followers and fundamentalists, we derive the general form of a stochastic equation of market dynamics. The model has two characteristic time scales: the time of changes of market environment and the characterist…

2003-07-08abs ↗pdf ↗

Scores political leanings in Web3 betting markets.

problem Understanding political motivations in decentralized prediction markets.
method Constructing PBLS from Polymarket data, analyzing 15k addresses, 4k events, 8k markets.
result Validated PBLS through internal and external comparisons, revealing political and profit motives.

Agent-based simulation assesses tradable credit schemes for congestion reduction.

problem Simplistic modeling of TCS impacts in transportation research.
method Agent- and activity-based simulation framework within SimMobility.
result TCS stabilizes network and market performance over time, reducing congestion.

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the …

2017-03-26abs ↗pdf ↗

ABIDES-MARL uses MARL to study market behavior in a realistic financial simulation.

problem Understanding equilibrium behavior in complex financial market games.
method Combines MARL with a realistic LOB simulation to study market behavior.
result Validated approach by solving an extended Kyle model and showing how execution strategies shape market dynamics.

Model explains herding and volatility in urban housing prices.

problem Understanding non-linear price dynamics in urban housing markets.
method Agent-based model with rational households and trend-following behavior.
result Model accurately predicts price variability and herding behavior.

Leverage is strongly related to liquidity in a market and lack of liquidity is considered a cause and/or consequence of the recent financial crisis. A repurchase agreement is a financial instrument where a security is sold simultaneously with an agreement to buy it back at a later date. Repurchase agreements (repos) ma…

2010-11-01abs ↗pdf ↗

We study precursors to the global market crash that occurred on all main stock exchanges throughout the world in October 2008 about three weeks after the bankruptcy of Lehman Brothers Holdings Inc. on 15 September. We examine the collective behavior of stock returns and analyze the market mode, which is a market-wide c…

2011-11-20abs ↗pdf ↗

We present a simple model of a stock market where a random communication structure between agents gives rise to a heavy tails in the distribution of stock price variations in the form of an exponentially truncated power-law, similar to distributions observed in recent empirical studies of high frequency market data. Ou…

1997-12-30abs ↗pdf ↗

Paper finds significant impact of stock market swings on equity risk premium predictability.

problem Predicting equity risk premium based on stock market behavior changes.
method Introduced Bullish Index and used FDMAA for returns analysis; considered 28 indicators.
result Positive shocks in Bullish Index correlate with strong equity risk premium predictability for up to six months, while negative shocks correlate for up to nine months.

Understanding how funding and 4H context regulate crypto markets.

problem Analyzing the chaotic appearance of financial markets.
method Observing interactions between market context and capital conditions in the 4H timeframe.
result Ranges in crypto markets are strategic positioning by informed participants, not indecision.

Researchers adaptively analyze market regimes to reveal investor behavior shifts.

problem Market relationships shift across different regimes, affecting investor behavior.
method Combining Kalman filtering, Markov-switching, and asymmetric response estimation.
result Foreign investors' predictive power increases during crises, while individual investors react more strongly to positive shocks.

Graph Ricci flow reveals hidden hierarchies in stock market correlations.

problem Detecting hidden structures in the complex stock market graph.
method Using graph Ricci curvature and flow techniques to analyze the NASDAQ 100 index.
result Algorithm detects hidden hierarchies, community behavior, and clustering in financial markets.

In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain an…

2015-07-13abs ↗pdf ↗

Behavioral finance has become an increasingly important subfield of finance. However the main parts of behavioral finance, prospect theory included, understand financial markets through individual investment behavior. Behavioral finance thereby ignores any interaction between participants. We introduce a socio-financia…

2014-10-09abs ↗pdf ↗

Log-periodic oscillations have been used to predict price trends and crashes on financial markets. So far two types of log-periodic oscillations have been associated with the real markets. The first type are oscillations which accompany a rising market and which ends in a crash. The second type oscillations, called "an…

2003-07-14abs ↗pdf ↗

Study uses OT to simulate markets, revealing power-law returns are driven by informational effect.

problem Reproduce power-law returns in financial markets using realistic simulations.
method Constructed artificial markets, used optimal transport (OT) to measure similarity, incrementally introduced behavioral components.
result Informational effect of prices is dominant in reproducing power-law returns, and multiple components interact synergistically.

The paper examines short-term volatilities in equity indexes using a ranking procedure.

problem Understanding short-term behaviors of implied volatility in equity markets.
method Using a ranking procedure to model equity index dynamics, the paper investigates the short-term volatilities of derivatives written on indexes.
result The models reconcile the long memory of volatilities and power law of ATM skews in equity markets.

Social interactions and personal tastes shape our consumption behavior of cultural products. In this study, we present a computational model of a cultural market and we aim to analyze the behavior of the consumer population as an emergent phenomena. Our results suggest that the final market shares of cultural products …

2007-07-16abs ↗pdf ↗

Prediction markets can shape political behavior through persistent signals, not just forecast accuracy.

problem The role of prediction markets beyond forecasting.
method Transaction-level evidence from the 2024 U.S. presidential election, Signal Credibility Index (SCI).
result Price signals in prediction markets are more influential due to persistence, breadth of trader types, and cross-platform consensus.

Study examines how traders with asymmetric information and adaptive learning strategies affect market efficiency.

problem Effect of traders' strategic behavior on market efficiency and informational asymmetry.
method Examines a market with boundedly rational, asymmetrically informed traders using multiarmed bandit algorithms.
result Strategically acting traders can lead to more efficient markets than purely competitive ones under certain conditions.

ClusterLOB clusters market events to identify different trading behaviors.

problem Understanding market microstructure and participant behavior in financial markets.
method ClusterLOB uses K-means++ algorithm to cluster market events based on six time-dependent features.
result ClusterLOB identifies three distinct trading behaviors: directional, opportunistic, and market-making participants.

We propose and analyze numerically a simple dynamical model that describes the firm behaviors under uncertainty of demand forecast. Iterating this simple model and varying some parameters values we observe a wide variety of market dynamics such as equilibria, periodic and chaotic behaviors. Interestingly the model is a…

2017-01-23abs ↗pdf ↗

A new approach to the understanding of complex behavior of financial markets index using tools from thermodynamics and statistical physics is developed. Physical complexity, a magnitude rooted in Kolmogorov-Chaitin theory is applied to binary sequences built up from real time series of financial markets indexes. The st…

2001-04-24abs ↗pdf ↗

The market efficiency hypothesis has been proposed to explain the behavior of time series of stock markets. The Black-Scholes model (B-S) for example, is based on the assumption that markets are efficient. As a consequence, it is impossible, at least in principle, to "predict" how a market behaves, whatever the circums…

2019-03-19abs ↗pdf ↗

Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been c…

2009-05-29abs ↗pdf ↗