This paper extends a Kyle model to include price-responsive traders, revealing new dynamics and equilibria.
problem Real-world market dynamics involve price-responsive traders, affecting market equilibrium and insider profits.
method Developed a continuous-time Kyle model with two types of price-responsive traders (momentum and contrarian), leading to a forward-backward Riccati system for equilibrium.
result The model shows that feedback effects can lead to multiple equilibria and amplify price informativeness.
Study of a risk-averse informed trader in a multi-asset market with non-Gaussian prices.
problem Existence of equilibrium in a multi-asset market with non-Gaussian prices and a risk-averse informed trader.
method Constructed equilibrium using Fokker-Planck equation and coupled partial differential equations with an optimal transport constraint.
result Equilibrium exists in a market with multiple assets and non-Gaussian prices.
Analytic solutions found for a financial market model with traders.
problem Analyzing stability and price dynamics in a financial market model.
method Developed a continuous-time financial market model with two types of traders and proved stability conditions.
result Analytic formulae derived for price dynamics and trader profitability.
Brokers and an informed trader compete for liquidity, affecting trading costs and inventory risk.
problem How brokers and an informed trader manage liquidity and trading costs.
method Sequential Stackelberg game, solving for trading strategies, numerical solutions.
result Equilibrium strategies and liquidity prices determined, not Pareto efficient.
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.
A nonlinear differential equation of Sornette-Ide type with noise, for a complex variable, yields endogenous crashes, preceded by roughly log-periodic oscillations in the real part, and a strong increase in the imaginary part. The latter is interpreted as the trader expectation.
Model shows how multiple markets can coexist or fragment based on trader behavior.
problem Understanding market competition and coexistence among multiple trading venues.
method Stylized model of traders making repeated decisions at three markets, analyzed numerically and analytically.
result Parameters like memory length and choice intensity determine whether markets coexist or fragment.
We introduce an autoregressive-type model of prices in financial market taking into account the self-modulation effect. We find that traders are mainly using strategies with weighted feedbacks of past prices. These feedbacks are responsible for the slow diffusion in short times, apparent trends and power law distributi…
This study models AI traders' impact on financial markets using a multi-agent framework.
problem Lack of a comprehensive model to assess AI traders' effects on market price formation and volatility.
method Developed a multi-agent market model with microfoundations of the GARCH model.
result Validated the model through simulations and analyzed AI traders' impact.
Study on CFMMs pricing and hedging, developing models for LP and derivatives valuation.
problem Valuation and hedging of liquidity provider mechanisms in CFMMs.
method Developed a model with two types of traders, simulated their behavior, and calculated PnL.
result Foundations for estimating CFMM derivatives and understanding fair price distribution.
A simple trading model based on pair pattern strategy space with holding periods is proposed. Power-law behaviors are observed for the return variance σ2, the price impact H and the predictability K for both models with linear and square root impact functions. The sum of the traders' wealth displays a positive v…
Study analyzes broker's gain from trade in repeated context-based trading.
problem Maximizing traders' net utility in repeated context-based brokerage.
method Proposes algorithms achieving tight regret bounds in full and limited feedback settings.
result Achieves tight 1/2-approximation result for gain from trade.
Model predicts limit order book dynamics based on market participant interactions.
problem Understanding and predicting the dynamics of the limit order book in financial markets.
method Agent-based model with informed, noise, and market maker traders; deduces limit order book from interactions.
result Link between price dynamics, trade proportions, volume, spread, and equilibrium state.
Study analyzes non-Markovian effects in financial markets over multiple years.
problem Understanding non-Markovian dynamics and trader interactions in financial markets.
method Empirical analysis of self-response functions and trade sign correlators for different stocks over multiple years.
result Significant variations in traders' interactions over time, indicating changes in market mechanisms.
A model simulates how different types of traders react to macroeconomic news.
problem Understanding how various market participants respond to macroeconomic surprises.
method Developed a calibrated data generation process (DGP) with four trader archetypes and a Monte Carlo simulation.
result Higher information and lower risk-averse traders take larger positions and achieve higher average wealth.
Paper models limit order book with informed traders and market makers.
problem Modeling the limit order book with heterogeneous market participants.
method Agent-based model with four types of participants: informed traders, noise traders, informed market makers, and noise market makers. Based on Glosten-Milgrom and Huang-Rosenbaum-Saliba approaches.
result Derived the static limit order book characteristics and compared them with existing models.
We discuss how minimal financial market models can be constructed by bridging the gap between two existing, but incomplete, market models: a model in which a population of virtual traders make decisions based on common global information but lack local information from their social network, and a model in which the tra…
Study reveals asymmetry in market dynamics across different timescales.
problem Understanding asymmetry in market dynamics across different timescales.
method Infer lead-lag networks for multiple timescales to capture causal structure.
result Strong and complex asymmetric influence of timescales on lead-lag networks.
Study quantifies contributions of market participants to volatility using Hawkes processes.
problem Quantifying contributions of different market participants to volatility.
method Leveraged Hawkes point processes to analyze the branching properties of market participant behaviors.
result High-frequency traders are more endogenously driven than other types of agents.
The paper explains stock predictability by integrating rational finance without behavioral finance assumptions.
problem The predictability of stock returns observed in the stock market.
method Developed a statistical model within rational finance to incorporate stock predictability into the Black-Scholes formula.
result Empirical analysis shows asymmetric predictability by spot and option traders, and potential stock return predictors.
Study analyzes bond traders' views on equity market dynamics.
problem Understanding temporal shifts in equity market parameters.
method Utilizes Black-Derman-Toy model and zero-coupon bond pricing.
result Discovers correlations between risk-neutral probability and market variables.
We propose a series of simple models for the microstructure of a double auction market without intermediaries. We specialize to those markets, such interdealer broker markets, which are dominated by professional traders, who trade mainly through limit orders, watch markets closely, and move their limit order prices fre…
Study shows HFT benefits large traders under certain conditions.
problem Influence of high-frequency traders (HFTs) on large traders.
method Analyzes the impact of HFT front-running on large traders under different conditions.
result HFT benefits large traders when there is high-speed noise trading and vague HFT predictions.
Investigates market dynamics with informed traders and high-frequency traders.
problem Trading large orders in a market with multiple high-frequency traders.
method Analyzes a three-period Kyle's model with a normal-speed informed trader and multiple anticipatory high-frequency traders under different inventory pressures.
result Surprising results: improving HFTs' speed or prediction can harm them but benefit the informed trader.
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.
DQN outperforms static policies in a dynamic fee environment for automated market makers.
problem How automated market makers (AMMs) perform under dynamic fees is unknown.
method Constructed a closed-loop simulator with dynamic fees, noise flow, and arbitrage.
result A small DQN policy outperforms static policies in a dynamic fee environment.
Modeling price impacts and trading signals for optimal execution and speculation.
problem Optimal execution and speculation in markets with trade signals.
method Price impact model driven by order flow, stochastic price impact, Meyer-σ-fields signal process, Marcus-type SDEs. result Derivation and numerical solution of HJB equation for optimal execution, enhanced speculative strategies.
Model explains periodic trading in financial markets through game theory.
problem Understanding periodic trading activities in financial markets.
method Mean-field liquidation game with major-minor players.
result Existence and uniqueness of Nash equilibrium established.
The paper extends option pricing theory for markets with informed traders.
problem Discontinuity in option pricing for markets with informed traders.
method New models for option pricing in complete markets considering informed traders' information on stock price direction and return mean.
result The discontinuity puzzle in option pricing is resolved using continuous diffusion price processes.
Paper proposes a new method to simulate realistic markets from data.
problem Lack of accurate market simulators leading to misleading conclusions.
method Proposes a world agent model trained on historical data without agent calibration.
result Models consistently outperform previous methods in realism and responsiveness.
An informed broker optimizes trading strategies in a market influenced by many traders.
problem Optimizing trading strategies for an informed broker in a market with many traders.
method Developed a mean-field game approach to derive equilibrium strategies for both the broker and traders.
result The broker's optimal strategy involves a Stackelberg equilibrium, leading and traders following.
Study Nash equilibrium between broker and trader in a lit exchange with price impact.
problem Optimizing trading strategies between informed and uninformed traders with broker's inventory penalties.
method Characterized Nash equilibrium through FBSDEs, solved explicitly.
result Explicit solution to trading strategies of broker and informed trader.
PRZI traders adapt their quote-prices based on a strategy parameter s, affecting market dynamics.
problem Understanding the dynamics of continuous double auction markets with adaptive traders.
method Introduced a new zero-intelligence trader PRZI that uses a parameterised probability distribution to generate quote-prices. Used a stochastic hill-climber algorithm to adapt strategies based on market conditions.
result The co-evolutionary dynamics of PRZI traders can lead to rich and complex market behaviors, including periods of stability and change.
Study shows unique linear equilibrium in market with constrained trader.
problem Unique equilibrium in financial market with constrained trader.
method Linear equilibrium model with competitive market makers and noise traders.
result Equilibrium uniquely determined by two state variables.
Study on optimal information acquisition in Kyle model with entropy cost.
problem Optimal information acquisition in Kyle model with entropy cost.
method Continuous signals are optimal, and any signal with a logit posterior distribution yields the same ex-ante value.
result Posterior expected payoff becomes normally distributed as information acquisition cost increases.
Modeling market dynamics with informed and uninformed traders and fads.
problem Optimizing market making in a market with fads, informed, and uninformed traders.
method Characterizing the optimal liquidity provision problem in a market with fads, informed, and uninformed traders, considering both complete and partial information.
result The price of liquidity is a function of the proportion of informed traders, and strategies ignoring fads underperform.
Solves a game between brokers and informed traders using stochastic differential equations.
problem Optimizing wealth in a game between brokers and informed traders with private signals.
method Closed-form solutions to a mean-field game using forward-backward SDEs.
result Optimal trading strategies for both brokers and informed traders are found.
High-frequency traders can act as either small informed traders or round-trippers, affecting price discovery and liquidity.
problem Effects of high-frequency trading on price discovery and liquidity.
method Extended Kyle's model with interactions between large informed traders and high-frequency traders.
result High-frequency traders can act as Small-IT or Round-Tripper, impacting price discovery and liquidity.
Deep learning mimics successful traders in financial markets.
problem Tackling profitable trading behavior in financial markets.
method Using deep learning neural networks to replicate adaptive trading behavior.
result Deep learning can outperform human traders and even improve performance.
Traders underestimated risk-free rates, leading to poor investments.
problem Incorrect setting of risk-free rates by traders.
method Analysis of investment decisions and financial models.
result Underestimating risk-free rates led to flawed investment decisions.
Study market efficiency under partial information using SDEs and optimization.
problem Market efficiency under partial information constraints.
method McKean-Vlasov-type SDEs, Wasserstein barycenters, KL divergence, convex optimization, optimal control, nonlinear filtering.
result Convergence of reduced-information market price processes to true price process under increasing information flow.
Study a market with uncertain informed traders, finding price impact depends on both asset value and informed trader count distribution.
problem Uncertain participation of informed traders in a market with limit orders.
method Characterized equilibrium by a fixed point integral equation, analyzed large order asymptotics, solved numerically.
result Equilibrium price impact depends on both asset value and distribution of informed traders, not just expected number of informed traders.
Strategic brokers exploit private information in broker-mediated markets, affecting informed traders' performance.
problem Strategic interactions and information leakage in broker-mediated markets.
method Study of strategic trading behavior and information leakage in a broker-mediated market.
result Brokers hold a strategic advantage over informed traders due to information leakage in trading flows.
Maximizing trading volume in online learning framework between traders.
problem Maximizing the total number of trades between traders with unknown valuations.
method Developed algorithms for brokers to maximize trading volume under different feedback scenarios.
result Achieved logarithmic and poly-logarithmic regret rates for different feedback models.
This paper improves robot traders' market impact sensitivity.
problem Market impact in automated trading systems.
method Critiqued existing methods, introduced MLOFI, and demonstrated new algorithms.
result New imbalance-sensitive trader-agents exhibit market impact effects.
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.
problem Understanding traders' rationality and risk aversion from market volumes.
method Optimal Merton dynamics model to estimate average risk aversion and price of risk.
result Validation of the proposed trading strategy model on real data.
Trading strategy advantage based on information asymmetry.
problem Trading advantage due to information disparity.
method Modeling market information, analyzing risk-neutral distribution, proving value difference.
result First trader's position is strictly more valuable than the second.