Paper validates ABM using stylized financial facts.
problem Validate ABM-generated financial data against real-world data.
method Compare ABM results with stylized financial facts.
result Model successfully replicates stylized financial facts.
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48 results for “financial stylised facts”
High subjective discount and risk aversion contradict financial data.
problem Inconsistent asset pricing with financial stylised facts.
method Analyzing capital market equilibrium restrictions.
result Subjective discount and risk aversion cannot be high simultaneously.
Model explains stylized facts in financial log returns through agent behavior.
problem Understanding stylized facts in financial log returns.
method Agent-based model with three types of traders.
result Model produces log returns with stylized facts like leptokurtosis and volatility clustering.
New method calibrates financial market simulators using neural networks.
problem Calibrating market simulators to specific trading periods.
method Neural density estimators and embedding networks.
result Approach accurately identifies high-probability parameter sets.
Hybrid model simulates market dynamics using neural stochastic background traders.
problem Lack of realistic LOB simulations that combine historical data and dynamic interactions.
method Neural stochastic background trader trained on historical LOB data, embedded in multi-agent simulation.
result Hybrid model recreates stylised market facts and financial herding behaviors.
Anomalous fluctuations in Minority Games and related multi-agent models of financial marketsphysics.soc-ph
We review the recent approaches to modelling financial markets based on multi-agent systems. After a brief summary of the basic stylised facts observed in real-market time-series we discuss some simple agent-based systems which are currently used to model financial markets. One of the most prominent examples is here th…
Researchers validate LMF order-splitting theory using public JSE data.
problem Lack of reproducibility and cross-market validation of LMF theory due to proprietary data.
method Synthetic metaorder reconstruction using publicly available JSE data.
result LMF theory validated using JSE data for 100 largest stocks.
The three-state agent-based 2D model of financial markets as proposed by Giulia Iori has been extended by introducing increasing trust in the correctly predicting agents, a more realistic consultation procedure as well as a formal validation mechanism. This paper shows that such a model correctly reproduces the three f…
XGB-Chiarella model generates realistic intra-day financial price data using agent-based models.
problem Generating accurate intra-day financial price data for research and risk management.
method Agent-based financial market simulation with XGBoost machine learning calibration.
result XGB-Chiarella model accurately reflects real market behaviours and generates realistic price time series.
New financial price model using earning yield derived from CIR process.
problem Excess volatility and equity premium puzzles in financial markets.
method Proposes a new financial price process based on earning yield and Cox-Ingersoll-Ross (CIR) process.
result Derives analytically stylized facts of financial prices and returns, including power law distribution of returns and fat-tailed distribution of prices.
Extends QHawkes to MQHawkes for analyzing financial co-jumps.
problem Capturing endogenous co-jumps in financial markets.
method Develops MQHawkes process with quadratic kernels, investigates stationarity, and derives Yule-Walker equations.
result Volatility distribution exhibits power-law behavior with computable exponents.
Study compares ABM calibration methods, finds Bayesian estimation superior.
problem Criticism of ABM rigour, particularly in calibration practices.
method Comparison of Bayesian and frequentist ABM calibration methods through computational experiments.
result Bayesian estimation outperforms frequentist methods in producing reasonable parameter estimates.
Simulates financial market orders using anomalous diffusion models.
problem Anomalous diffusion in financial market order dynamics.
method Discrete Time Random Walk with Sibuya waiting times, non-uniform sampling, and cubic spline interpolation.
result Demonstrates price impact for different forcing functions and model parameters.
Many learning agents impact a financial market model, showing complex dynamics.
problem Understanding the dynamics of financial markets with multiple learning agents.
method Agent-based model of financial market with multiple reinforcement learning agents interacting.
result Inclusion of learning agents changes market dynamics to match empirical data.
Agent-based model simulates financial market crashes and identifies key factors.
problem Analyzing and understanding flash crashes in financial markets.
method Agent-based modelling approach with calibrated high-frequency financial simulator.
result Model accurately reproduces historical flash crash events and identifies key factors.
New models explain multidimensional rough volatility from microscopic price dynamics.
problem Designing new rough stochastic volatility models for multi-asset scenarios.
method Using Hawkes processes to model microstructural interactions and investigate scaling limits.
result Multivariate rough volatility models arise naturally from microscopic price dynamics.
This work explains crises in markets without external news using bounded rational agents.
problem Inability to model out-of-equilibrium dynamics in economic markets.
method Modeling bounded rational strategic reasoning in multi-agent market games.
result Bounded rational strategic reasoning can lead to endogenously emerging crises.
Bayesian neural network approach improves estimation of complex economic models.
problem Difficulty in estimating complex economic simulation models due to intractable likelihood functions.
method Bayesian estimation using deep neural networks to approximate likelihood functions.
result Proposed methodology yields more accurate estimates across various economic models.
Agent-based model simulates market dynamics with real-time order matching.
problem Realistic simulation of market dynamics with realistic price impact.
method Agent-based model with asynchronous, event-time order matching.
result Realistic price impact curves and stylized facts presented.
Hybrid model combines deep learning and agent-based methods for synthetic LOB generation.
problem Generating realistic financial time series data for model training.
method Combining TABL model with Chiarella model for intraday trading activity simulation.
result Hybrid model generates realistic price dynamics but fails to accurately recreate market microstructure.
A simple learning agent learns to trade in an agent-based market model.
problem Optimal execution of trades in an agent-based financial market model.
method Asynchronous trading through a matching engine, varying initial order sizes and state spaces, calibration of empirical stylized facts and price impact curves.
result Smaller state space agents converge faster in learning and can trade intuitively using spread and volume states.
Do we know if a short selling ban or a Tobin Tax result in more stable asset prices? Or do they in fact make things worse? Just like medicine regulatory measures in financial markets aim at improving an already complex system. And just like medicine these interventions can cause side effects which are even harder to as…
We have discovered 12 independent new empirical scaling laws in foreign exchange data-series that hold for close to three orders of magnitude and across 13 currency exchange rates. Our statistical analysis crucially depends on an event-based approach that measures the relationship between different types of events. The…
In this paper we consider a multivariate model-based approach to measure the dynamic evolution of tail risk interdependence among US banks, financial services and insurance sectors. To deeply investigate the risk contribution of insurers we consider separately life and non-life companies. To achieve this goal we apply …
Proposes a new agent-based model for deep hedging that outperforms existing models.
problem Improving effectiveness of deep hedging strategies.
method Agent-based model with momentum, fundamental, and volatility traders following Heston volatility signal.
result Deep hedging agent trained with Chiarella-Heston model data outperforms baseline models in various transaction cost levels.
TraderTalk: An LLM Behavioural ABM applied to Simulating Human Bilateral Trading Interactionsq-fin.TR
TraderTalk uses LLMs to simulate human trading interactions in financial markets.
problem Simulating realistic human trading interactions in financial markets.
method Hybrid ABM with LLM-generated behaviors for detailed conversations.
result Successfully replicates trade-to-order volume ratios in financial markets.
Fractional reaction-diffusion model explains financial market dynamics.
problem Reproduce realistic price dynamics in financial markets.
method Proposes a fractional reaction-diffusion model with heterogeneous agent frequencies.
result Impact kernel decays as in the diffusive case, inconsistent with market efficiency; can be tuned to match empirical values.
Sparse grid method improves risk measurement for financial and insurance companies.
problem Measuring risk in financial and insurance balance sheets.
method Sparse grid approximation for numerical estimation of loss distribution.
result Sparse grid approach is more efficient and competitive for models with moderate dimension.
Agent-based model predicts microfinance risk shifts in poor economies.
problem Mapping sustainable microfinance credit risk in poor economies.
method Agent-based model using network theory.
result Deteriorating economy and adverse selection cause loan repayment probability shifts.
Examines financial market patterns across 150 years and regions.
problem Evaluating stylized facts in financial markets.
method Testing 11 stylized facts across 150 years and multiple regions.
result Robustness and generalizability of stylized facts confirmed.
Model simulates correlation emergence in two coupled limit order books.
problem Modeling correlation emergence in coupled limit order books.
method Simulated two coupled diffusive limit order books using random walks in the fluid limit, with trader interactions.
result Demonstrated the recovery of an Epps effect from the model.
This paper introduces stylized facts and agent-based modeling in finance.
problem Replicating stylized facts in financial markets.
method Agent-based computational economic market models.
result Introduction of universal building blocks for agent-based models.
We establish several new stylised facts concerning the intra-day seasonalities of stock dynamics. Beyond the well known U-shaped pattern of the volatility, we find that the average correlation between stocks increases throughout the day, leading to a smaller relative dispersion between stocks. Somewhat paradoxically, t…
GANs can learn stylized facts of financial time series, but performance varies by architecture.
problem Capturing stylized facts of financial time series using GANs.
method Examination of GANs' ability to learn stylized facts of financial time series, focusing on univariate and multivariate data.
result GANs can capture stylized facts of financial time series, but performance varies by architecture.
New game model improves financial stylized facts reproduction.
problem Difficulty in reproducing financial stylized facts.
method Agent-based speculation game with unique features.
result Successfully reproduces 10 out of 11 stylized facts.
Paper develops framework for AI agents in financial markets.
problem Systemic implications of AI in finance depend on agent architectures.
method Four-layer architecture and AFMM model for analysis.
result AI agents can improve market efficiency and resilience.
Study of common financial data patterns across stocks.
problem Understanding common patterns in financial data.
method Analysis of stock price data from multiple exchanges.
result Identification of various stylized empirical facts in financial data.
Generates financial time series with stylized facts using diffusion models.
problem Generating realistic synthetic financial time series with statistical properties like fat tails, volatility clustering, and seasonality.
method Utilizes denoising diffusion probabilistic models (DDPMs) with wavelet transformation to convert and generate financial time series.
result Demonstrates that the proposed approach satisfies stylized financial time series properties.
Relevant Stylized Facts About Bitcoin: Fluctuations, First Return Probability, and Natural Phenomenaq-fin.ST
Bitcoin shows similar stylized facts to traditional financial assets.
problem Testing Bitcoin for stylized facts of traditional financial assets.
method Testing Bitcoin for Gaussianity, fluctuation scaling, and persistence.
result Bitcoin exhibits similar statistical properties to traditional financial assets.
This paper introduces the class of volatility modulated Lévy-driven Volterra (VMLV) processes and their important subclass of Lévy semistationary (LSS) processes as a new framework for modelling energy spot prices. The main modelling idea consists of four principles: First, deseasonalised spot prices can be modelled di…
CoFinDiff generates synthetic financial data capturing stylized facts and meeting specified conditions.
problem Limited data availability and difficulty in controlling synthetic financial data generation.
method Conditional diffusion model with cross-attention to incorporate conditions derived from price data.
result Synthetic data generated by CoFinDiff accurately meets specified conditions for trends and volatility.
SFAG generates realistic financial data that passes trading tests.
problem Financial generative models often produce unrealistic and unstable trading outcomes.
method Introduces SFAG, a GAN variant that aligns stylized facts and optimizes with adversarial loss.
result SFAG generates synthetic data that preserves stylized facts and supports robust trading strategies.
Study compares market microstructure between two South African exchanges.
problem Understanding price response dynamics and market microstructure differences between two South African exchanges.
method Comparative analysis of returns distributions, auto-correlations, price impact, and trading costs on different time scales.
result Similar stylized facts emerge as measurement time scale increases, but price responses vary significantly.
Generative adversarial networks with attention improve financial time series simulation.
problem Limited real financial data for training and evaluation of trading strategies.
method Two generative adversarial networks (GANs) using convolutional networks with attention and transformers.
result Attention-based GANs better reproduce stylized facts and smooth returns autocorrelation.
Model explains financial data patterns through investor misperceptions.
problem Understanding stylized facts in financial markets.
method Derives mean field limit of agent-based financial model.
result Kinetic model replicates fat-tails, uncorrelated returns, and volatility clustering.
Herein, we applied statistical physics to study incomes of three (low-, medium- and high-income) society classes instead of the two (low- and medium-income)classes studied so far. In the frame of the threshold nonlinear Langevin dynamics and its threshold Fokker-Planck counterpart, we derived a unified formula for desc…
Significantly reduces Monte Carlo runtime for rough Bergomi model pricing.
problem Calibrating rough Bergomi model with high runtime for Monte Carlo simulations.
method Novel composition of variance reduction methods for log-normal stochastic volatility models.
result Significant runtime reductions (20 times average) across different correlation regimes.
New method simulates stock prices with long-range data accurately.
problem Simulating long-range daily stock-price data accurately.
method Developed an R-program to simulate data that closely matches stylized facts.
result The program accurately reproduces changes in unconditional variance.