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.
Study reveals patterns in trader clusters over time, improving investment predictions.
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two dimensional grid. Active traders are characterised by the decision to buy, (+1), or sell, (-1), a …
We present a plausible micro-founded model for the previously postulated power law finite time singular form of the crash hazard rate in the Johansen-Ledoit-Sornette model of rational expectation bubbles. The model is based on a percolation picture of the network of traders and the concept that clusters of connected tr…
In an illiquid stock, traders can collude and place orders on a predetermined price and quantity at a fixed schedule. This is usually done to manipulate the price of the stock or to create artificial liquidity in the stock, which may mislead genuine investors. Here, the problem is to identify such group of colluding tr…
This paper outlines an agent-based model of a simple financial market in which a single asset is available for trade by three different types of traders. The model was first introduced in the PhD thesis of one of the authors, see reference [1]. The simulated log returns are examined for the presence of the stylised fac…
A Kyle-inspired model with adaptive agents explains excess volatility and volatility clustering.
The paper explains financial volatility using simple news-driven models.
This paper detects fraudulent trading in the NFT market.
We investigate the statistical properties of the EBS order book for the EUR/USD and USD/JPY currency pairs and the impact of a ten-fold tick size reduction on its dynamics. A large fraction of limit orders are still placed right at or halfway between the old allowed prices. This generates price barriers where the best …
We give a microscopic representation of the stock-market in which the microscopic agents are the individual traders and their capital. Their basic dynamics consists in the auto-catalysis of the individual capital and in the global competition/cooperation between the agents mediated by the total wealth invested in the s…
This study models AI traders' impact on financial markets using a multi-agent framework.
We present an experimental and simulated model of a multi-agent stock market driven by a double auction order matching mechanism. Studying the effect of cumulative information on the performance of traders, we find a non monotonic relationship of net returns of traders as a function of information levels, both in the e…
This study is a detailed analysis of Speculation Game, a minimal agent-based model of financial markets, in which the round-trip trading and the dynamic wealth evolution with variable trading volumes are implemented. Instead of herding behavior, we find that the emergence of volatility clustering can be induced by the …
We introduce a model of super-exponential financial bubbles with two assets (risky and risk-free), in which rational investors and noise traders co-exist. Rational investors form expectations on the return and risk of a risky asset and maximize their constant relative risk aversion expected utility with respect to thei…
We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps are frequent events and…
In this paper we extend the theory of option pricing to take into account and explain the empirical evidence for asset prices such as non-Gaussian returns, long-range dependence, volatility clustering, non-Gaussian copula dependence, as well as theoretical issues such as asymmetric information and the presence of limit…
We solved a stylized fact on a long memory process of volatility cluster phenomena by using Minkowski metric for GARCH(1,1) under assumption that price and time can not be separated. We provide a Yang-Mills equation in financial market and anomaly on superspace of time series data as a consequence of the proof from the…
Quantitative analysis of order-splitting behavior in Japanese stock market.
Study validates Lillo-Mike-Farmer model predicting financial market long-range correlations.
Analyzes NFT market trends, trade networks, and visual features.
A network-based approach identifies financial factors from asset interactions, explaining market dynamics.
We propose a three-state microscopic opinion formation model for the purpose of simulating the dynamics of financial markets. In order to mimic the heterogeneous composition of the mass of investors in a market, the agent-based model considers two different types of traders: noise traders and contrarians. Agents are re…
Study shows HFT benefits large traders under certain conditions.
Modeling financial market dynamics with noise and fundamentalist agents.
Investigates market dynamics with informed traders and high-frequency traders.
This paper aims to develop new techniques to describe joint behavior of stocks, beyond regression and correlation. For example, we want to identify the clusters of the stocks that move together. Our work is based on applying Kernel Principal Component Analysis(KPCA) and Functional Principal Component Analysis(FPCA) to …
The paper extends option pricing theory for markets with informed traders.
An informed broker optimizes trading strategies in a market influenced by many traders.
Study Nash equilibrium between broker and trader in a lit exchange with price impact.
PRZI traders adapt their quote-prices based on a strategy parameter s, affecting market dynamics.
Study shows unique linear equilibrium in market with constrained trader.
Modeling market dynamics with informed and uninformed traders and fads.
Solves a game between brokers and informed traders using stochastic differential equations.
High-frequency traders can act as either small informed traders or round-trippers, affecting price discovery and liquidity.
Traders underestimated risk-free rates, leading to poor investments.
Model shows how multiple markets can coexist or fragment based on trader behavior.
We report successful results from using deep learning neural networks (DLNNs) to learn, purely by observation, the behavior of profitable traders in an electronic market closely modelled on the limit-order-book (LOB) market mechanisms that are commonly found in the real-world global financial markets for equities (stoc…
Brokers and an informed trader compete for liquidity, affecting trading costs and inventory risk.
Study a market with uncertain informed traders, finding price impact depends on both asset value and informed trader count distribution.
Strategic brokers exploit private information in broker-mediated markets, affecting informed traders' performance.
Maximizing trading volume in online learning framework between traders.
This paper improves robot traders' market impact sensitivity.
In a very simple stock market, made by only two \emph{initially equivalent} traders, we discuss how the information can affect the performance of the traders. More in detail, we first consider how the portfolios of the traders evolve in time when the market is \emph{closed}. After that, we discuss two models in which a…
The study reveals traders' risk aversion and a new risk premium from market volumes.
Trading strategy advantage based on information asymmetry.
In this paper it was developed a modification of the known multiagent model Minority Game, designed to simulate the behavior of traders in financial markets and the resulting price dynamics on the abstract resource. The model was implemented in the form of software. The modified version of Minority Game was investigate…
A combination of a priority queueing model and mean field theory shows the emergence of traders' swarm behavior, even when each has a subjective prediction of the market driven by a limit order book. Using a nonlinear Markov model, we analyze the dynamics of traders who select a favorable order price taking into accoun…
Bitcoin option prices reflect both market maker supply and trader demand, especially from those with insider information.