The existence of stylized facts in financial data has been documented in many studies. In the past decade the modeling of financial markets by agent-based computational economic market models has become a frequently used modeling approach. The main purpose of these models is to replicate stylized facts and to identify …
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48 results for “Stylized Facts”
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.
Study tests 11 stylized facts for modern stock markets, finding support for 8.
problem Whether stylized facts from 2001 still hold for modern markets.
method Replicated 11 stylized facts for intraday returns of Dow 30 stocks using authoritative data.
result 8 of 11 stylized facts supported, 3 not supported.
Stylized Facts and Market Microstructure: An In-Depth Exploration of German Bond Futures Marketq-fin.ST
Study reveals stylized facts in German bond futures markets.
problem Understanding market dynamics in German bond futures.
method Analyzed tick-by-tick data of four German bond futures contracts.
result Uncovered commonalities and unique characteristics across different futures.
Minority Games and stylized factscond-mat.stat-mech
The Minority Game is a generic model of competing adaptive agents, which is often believed to be a model of financial markets. We discuss to which extend this is a reasonable statement, and present minimal modifications that make this model reproduce stylized facts. The resulting model shows that without speculators, p…
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.
Model shows how traders' interactions can create market patterns.
problem Explaining stylized facts in high-frequency trading markets.
method Agent-based model of limit order book trading with zero-intelligence agents.
result Scale-free connectivity between traders reproduces market patterns, while no interaction does not.
Cryptocurrencies evolve through survival of the fittest, modeled with evolutionary finance.
problem Understanding the dynamics of cryptocurrency markets.
method Evolutionary finance concepts applied to toy models of cryptocurrency data.
result Survival of the fittest in cryptofinance is explained through scaling laws.
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.
Simultaneous reproduction of all financial stylized facts is so difficult that most existing stochastic process-based and agent-based models are unable to achieve the goal. In this study, by extending the decision-making structure of Minority Game, we propose a novel agent-based model called "Speculation Game," for a b…
Stylized facts of financial markets and market crashes in Minority Gamescond-mat.stat-mech
We present and study a Minority Game based model of a financial market where adaptive agents -- the speculators -- interact with deterministic agents -- called producers. Speculators trade only if they detect predictable patterns which grant them a positive gain. Indeed the average number of active speculators grows wi…
Historical daily data for eleven years of the fifty constituent stocks of the NIFTY index traded on the National Stock Exchange have been analyzed to check for the stylized facts in the Indian market. It is observed that while some stylized facts of other markets are also observed in Indian market, there are significan…
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.
We study the qualitative and quantitative appearance of stylized facts in several agent-based computational economic market (ABCEM) models. We perform our simulations with the SABCEMM (Simulator for Agent-Based Computational Economic Market Models) tool recently introduced by the authors (Trimborn et al. 2019). Further…
We present some stylized facts exhibited by the time series of returns of the Mexican Stock Exchange Index (IPC) and compare them to a sample of both developed (USA, UK and Japan) and emerging markets (Brazil and India). The period of study is 1997-2011. The stylized facts are related mostly to the probability distribu…
We propose a new method (implemented in an R-program) to simulate long-range daily stock-price data. The program reproduces various stylized facts much better than various parametric models from the extended GARCH-family. In particular, the empirically observed changes in unconditional variance are truthfully mirrored …
Study examines stylized facts in DEX markets vs. traditional exchanges.
problem Comparing stylized facts in decentralized exchanges (DEXs) vs. traditional markets.
method Empirical analysis of 24 most active Uniswap v3 pools.
result New statistical regularities in DEX markets, linked to market structure and activity.
Stylized facts in Web3q-fin.ST
Study compares Web3 tokens to traditional assets, finding similar statistical properties.
problem Understanding statistical properties of Web3 tokens compared to traditional financial assets.
method Statistical analysis of various Web3 tokens across multiple time scales, comparing with traditional financial assets.
result Most Web3 tokens exhibit similar stylized facts to traditional financial assets, including heavy tails and volatility clustering.
Cryptocurrencies show similarities to traditional markets but also have unique characteristics.
problem Understanding the investment potential and characteristics of cryptocurrencies.
method Organized stylized facts and analyzed through empirical asset pricing.
result Cryptocurrencies exhibit similarities to traditional markets but also have distinct characteristics.
Volatility-inspired -LSTM cellq-fin.CP
The paper introduces a new -LSTM cell for volatility forecasting using stylized facts.
problem Lack of explainability and stylized knowledge in neural network volatility modeling.
method Introduces a new -LSTM cell with a stochastic processing layer, designed to incorporate stylized facts about volatility.
result Shows good out-of-sample forecasting performance with the -LSTM cell.
Study macroscopic equity market properties affecting active strategies.
problem Lack of adequate models for active equity strategies.
method Empirical study using CRSP Database, focusing on market capitalizations and returns.
result Highlight stylized facts and open questions in equity markets.
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.
Relevant Stylized Facts About Bitcoin: Fluctuations, First Return Probability, and Natural Phenomenaq-fin.ST
Bitcoin is a digital financial asset that is devoid of a central authority. This makes it distinct from traditional financial assets in a number of ways. For instance, the total number of tokens is limited and it has not explicit use value. Nonetheless, little is know whether it obeys the same stylized facts found in t…
Continuous-time model shows insider trading constraints impact market dynamics.
problem Trading constraints faced by insiders in continuous-time models.
method Proved global existence of equilibrium with terminal trading constraint.
result Equilibrium model aligns with empirical market behaviors.
Volatility clustering, long-range dependence, and non-Gaussian scaling are stylized facts of financial assets dynamics. They are ignored in the Black & Scholes framework, but have a relevant impact on the pricing of options written on financial assets. Using a recent model for market dynamics which adequately captures …
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.
In the past decade there has been a growing interest in agent-based econophysical financial market models. The goal of these models is to gain further insights into stylized facts of financial data. We derive the mean field limit of the econophysical model by Cross, Grinfeld, Lamba and Seaman (Physica A, 354) and show …
Financial markets show a number of non-stationarities, ranging from volatility fluctuations over ever changing technical and regulatory market conditions to seasonalities. On the other hand, financial markets show various stylized facts which are remarkably stable. It is thus an intriguing question to find out how thes…
We introduce a minimal Agent Based Model with two classes of agents, fundamentalists (stabilizing) and chartists (destabilizing) and we focus on the essential features which can generate the stylized facts. This leads to a detailed understanding of the origin of fat tails and volatility clustering and we propose a mech…
Stylized facts can be regarded as constraints for any modeling attempt of price dynamics on a financial market, in that an empirically reasonable model has to reproduce these stylized facts at least qualitatively. The dynamics of market prices is modeled on a macro-level as the result of the dynamic coupling of two dyn…
Study uses RL to simulate realistic market behavior.
problem Traditional market simulators lack realistic dynamic behavior.
method Agent-based simulation with reinforcement learning agents.
result RL agents simulate realistic stylized facts and market behavior.
Prices in financial markets exhibit extreme jumps far more often than can be accounted for by external news. Further, magnitudes of price changes are correlated over long times. These so called stylized facts are quantified by scaling laws similar to, for example, turbulent fluids. They are believed to reflect the comp…
This work presents the results of an empirical research with the target of modeling the stylized facts of the daily expost System Marginal Price (SMP) of the Greek wholesale electricity market, using data from January 2004 to December of 2011. SMP is considered here as the footprint of an underline stochastic and nonli…
Study finds meme stocks have unique price and social media dynamics.
problem Exploring unique properties of meme stocks.
method Regime-switching cointegration model.
result Meme stocks exhibit a distinct 'mementum' compared to other high-volume stocks.
MarketGAN generates financial returns using GANs to match empirical stylized facts.
problem Generating financial returns under data scarcity and preserving stylized facts.
method Generative adversarial learning with a TCN backbone.
result MarketGAN outperforms conventional methods in portfolio applications.
In this work we afford the statistical characterization of a linear Stochastic Volatility Model featuring Inverse Gamma stationary distribution for the instantaneous volatility. We detail the derivation of the moments of the return distribution, revealing the role of the Inverse Gamma law in the emergence of fat tails,…
Study on estimating volatility of volatility using Fourier methods and provides insights into volatility dynamics.
problem Estimating the volatility of volatility (vol-of-vol) accurately and efficiently.
method Used Fourier methodology to estimate integrated volatility of volatility, bias-corrected and without bias-correction, comparing their asymptotic properties and accuracy.
result The bias-corrected estimator reaches the optimal rate , while the uncorrected estimator has a slower rate and smaller asymptotic variance.
We discuss a simple model based on the Minority Game which reproduces the main stylized facts of anomalous fluctuations in finance. We present the analytic solution of the model in the thermodynamic limit and show that stylized facts arise only close to a line of critical points with non-trivial properties. By a simple…
Study financial market graphs with Laplacian constraints.
problem Learning undirected graphs in financial markets.
method Proposes algorithms to estimate graphs accounting for financial data properties.
result Guidelines for estimating graphs in financial markets.
We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time series of a stock and the average correlation of the stock with respect to the other stocks traded in the same market. This result is a robust stylized fact holding for different financial markets. We investigate this re…
Researchers calibrate an adaptive Farmer-Joshi model to recover stylized facts in financial markets.
problem Recovering stylized facts in financial markets using the Farmer-Joshi model.
method Calibrated an adaptive Farmer-Joshi model using genetic and Nelder-Mead algorithms, incorporating agent adaptation.
result The adaptive model recovers additional stylized facts, including auto-correlations and kurtosis, compared to the original model.
We propose and document the evidence for an analogy between the dynamics of granular counter-flows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counter-flows of simulated pedestrians through a door display many stylized facts obser…
Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Modelphysics.soc-ph
We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on th…
Minimal Agent Based Model for Financial Markets I: Origin and Self-Organization of Stylized Factsq-fin.TR
We introduce a minimal Agent Based Model for financial markets to understand the nature and Self-Organization of the Stylized Facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the main most important deviations of price time series from a Random Walk behavior. We fo…
This paper examines Bitcoin's unique market properties and the leverage effect.
problem Exploring stylized facts of Bitcoin returns and its statistical properties.
method Analysis of historical BTC-USD exchange rate data from 2013 to 2020.
result Bitcoin exhibits the leverage effect, distinguishing two regimes in its dynamics.
We present a detailed study of the statistical properties of an Agent Based Model and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the Stylized Facts and their Self-Organization. The key elements are fundamentalist …
Market Simulation Displaying Multifractalitycond-mat.stat-mech
We proposed a market simulation model (micro model) which displays multifractality and reproduces many important stylized facts of speculative markets. From this model we analytically extracted the MMAR model (Multifractal Model of Asset Returns) for the macroscopic limit.