AlphaLogics mines market logic to generate interpretable alpha factors.
problem Complex, opaque alpha factors from factor mining overlook market logic.
method Market Logic Mining, Factor Generation and Optimization, Market Logic Generation and Optimization.
result AlphaLogics improves predictive metrics and risk-adjusted returns over baselines.
MarS simulates financial markets using generative models.
problem Simulating realistic financial market effects.
method Order-level generative foundation model (LMM) for realistic, interactive, and controllable order generation.
result Strong scalability and robust realism in MarS.
Paper generalizes Hardy-Rogers maps for market equilibrium analysis in duopoly markets.
problem Existence and uniqueness of market equilibrium in duopoly markets with non-differentiable, nonlinear response functions.
method Coupled fixed points approach for generalized Hardy-Rogers maps.
result Enriched understanding of market equilibrium in duopoly markets with non-differentiable response functions.
Generative Adversarial Networks simulate realistic market interactions.
problem Lack of agent-level historical data limits market simulation realism.
method Conditional Generative Adversarial Networks (CGANs) trained on real data.
result CGAN-based synthetic market generator outperforms previous methods in market responsiveness and realism.
TRADES generates realistic market simulations for financial modeling.
problem Generating realistic and responsive market simulations for financial tasks.
method TRADES uses a transformer-based denoising diffusion probabilistic engine to generate time series order flows conditioned on market state.
result TRADES improves market simulation metrics by 3.27-3.48 over state-of-the-art (SoTA) methods.
Market-GAN adds context control to financial market data generation.
problem Lack of context labels and precision in generating context-aligned financial data.
method Proposes Contextual Market Dataset and Market-GAN architecture integrating GAN, autoencoder, and supervisors.
result Market-GAN outperforms state-of-the-art models in Dow Jones data generation.
New market makers improve on existing models in DeFi.
problem Improving liquidity and efficiency in decentralized finance.
method Developed a new family of market makers based on generalized means.
result G3Ms offer properties preferable to existing models.
Generates realistic stock market order streams using GANs.
problem Creating high-fidelity stock market data.
method Conditional Wasserstein GAN with auction mechanism and order-book augmentation.
result Generated data is close to real market data.
This research improves capital efficiency and impermanent loss in cryptocurrency markets using multi-token trading pools.
problem Poor impermanent loss and capital efficiency in automated market makers.
method Analysis and construction of a multi-token token proactive market maker (MPMM).
result MPMM shows better impermanent loss and capital efficiency than comparable market makers.
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while …
Almost twenty years ago, E.R. Fernholz introduced portfolio generating functions which can be used to construct a variety of portfolios, solely in the terms of the individual companies' market weights. I. Karatzas and J. Ruf recently developed another methodology for the functional construction of portfolios, which lea…
Financial market dynamics is rigorously studied via the exact generalized Langevin equation. Assuming market Brownian self-similarity, the market return rate memory and autocorrelation functions are derived, which exhibit an oscillatory-decaying behavior with a long-time tail, similar to empirical observations. Individ…
Financial Wind Tunnel generates versatile market data for model testing.
problem Inconsistent market dynamics across different scales and sources.
method Retrieval-augmented diffusion-based simulator integrating macro and micro patterns.
result Enhanced performance and adaptability of downstream models in complex markets.
Paper proposes DigMA to generate controllable financial market orders.
problem Generating realistic financial market orders with controllability.
method DigMA model using conditional diffusion and meta agent.
result DigMA achieves superior controllability and generation fidelity.
Study optimizes SREC generation and trading in solar energy markets.
problem Optimizing solar energy generation and trading in SREC markets.
method Mean-field game approach to solve stochastic game with heterogeneous agents.
result Characterized firms' optimal controls and equilibrium SREC price.
Modeling price formation in intraday electricity markets with renewable generation.
problem Price formation and optimal trading strategies in intraday electricity markets with intermittent renewable generation.
method Developed a tractable equilibrium model using stochastic control theory to identify optimal strategies and exhibit Nash equilibrium.
result Identified optimal trading strategies and exhibited Nash equilibrium in closed form for a finite number of agents and in the asymptotic framework of mean field games.
Study shows market makers can cooperate without communication.
problem Concerns of collusion in AI-driven market-making.
method Formulated as a repeated game, studied with Q-learning.
result Market makers can learn cooperative strategies without communication.
Study tests financial market efficiency using random number generator tests.
problem Check for informational efficiencies in financial markets.
method Analysed binary daily returns as random number generators, split analysis by annual and company levels, investigated longer-term efficiency over Nasdaq-listed companies.
result Information efficiency varies across years and reflects large-scale market impacts.
Open markets are a subset of equity markets with fixed top stocks, changing over time.
problem Understanding the dynamics and characteristics of open markets.
method Analyzing the similarities and differences between open markets and closed equity markets, and exploring specific topics like CAPM and portfolio construction.
result The equivalence of market viability and the existence of a numeraire portfolio holds in open markets, similar to closed markets.
Optimal market making strategy for electronic markets with persistent order flows.
problem Market making on electronic markets with persistent order flows.
method Formulated as a stochastic control problem, characterized by viscosity solutions, and implemented numerically.
result Characterization of an optimal market making strategy.
Market Mill is a complex dependence pattern leading to nonlinear correlations and predictability in intraday dynamics of stock prices. The present paper puts together previous efforts to build a dynamical model reflecting the market mill asymmetries. We show that certain properties of the conditional dynamics at a sing…
Reverse-weighted portfolios outperform in commodity futures markets.
problem Efficiency of commodity futures markets.
method Permutation-weighted portfolios, rank-based methods.
result Reverse-weighted portfolio outperforms price-weighted portfolio.
Generative neural networks improve insurance market risk modeling.
problem Creating realistic market risk scenarios for insurance companies.
method Using generative adversarial networks (GANs) to generate economic scenarios.
result GAN-based models produce similar results to traditional regulatory models.
Two markets should be considered isomorphic if they are financially indistinguishable. We define a notion of isomorphism for financial markets in both discrete and continuous time. We then seek to identify the distinct isomorphism classes, that is to classify markets. We classify complete one-period markets. We define …
TradeFM learns market microstructure from trade events, improving financial model accuracy.
problem Lack of generalizable models for market microstructure.
method Generative Transformer model trained on billions of trade events, using scale-invariant features and universal tokenization.
result TradeFM generates rollouts that match key stylized facts of financial returns and outperforms existing models.
Neuro-symbolic traders suppress market prices, highlighting risks to stability.
problem Understanding and quantifying the influence of AI-generated financial models on markets.
method Developed virtual neuro-symbolic traders using deep generative models and tested them in a virtual market.
result Neuro-symbolic traders suppress market prices compared to historical data, indicating potential market instability.
In a financial market model, we consider variations of the problem of minimizing the expected time to upcross a certain wealth level. For exponential Levy markets, we show the asymptotic optimality of the growth-optimal portfolio for the above problem and obtain tight bounds for the value function for any wealth level.…
In this short note, we study an optimization problem of expected implementation shortfall (IS) cost under general shaped market impact functions. In particular, we find that an optimal strategy is a VWAP (volume weighted average price) execution strategy when the market model is a Black-Scholes type with stochastic clo…
The paper analyzes binary option markets with exogenous information and price sensitivity.
problem Analyzing binary option markets with exogenous information and price sensitivity.
method Derive and analyze a continuous model of binary option markets with exogenous information, using Filippov surfaces and general assumptions on purchasing rules.
result Price always converges when exogenous information is constant, and price sensitivity affects price lag vs. information.
This study examines whether the efficiency of cryptocurrency markets (Bitcoin and Ethereum) evolve over time based on Lo's (2004) adaptive market hypothesis (AMH). In particular, we measure the degree of market efficiency using a generalized least squares-based time-varying model that does not depend on sample size, un…
A Deep Q-Learning framework tackles market-making by incorporating closing auctions.
problem Managing end-of-day risk in market-making models.
method Developed a Deep Q-Learning framework that anticipates closing auctions and continuously refines projected clearing prices.
result The Deep Q-Learning framework outperforms classical market-making models in simulations and real data.
Considered an important macroeconomic indicator, the Purchasing Managers' Index (PMI) on Manufacturing generally assumes that PMI announcements will produce an impact on stock markets. International experience suggests that stock markets react to negative PMI news. In this research, we empirically investigate the stock…
Study on liquidity and market efficiency in auction games with imperfect information.
problem Generating liquidity in illiquid auction markets with imperfect information.
method Characterized Nash equilibria in a two-player game with imperfect information, linking market spreads to signal strength.
result Without incentives, the market is inefficient and does not lead to trades. Quadratic fees indexed on half spread can generate liquidity.
China's stock market is the largest emerging market all over the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependence. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic varia…
Optimized execution model using interbank and internal liquidity.
problem Minimizing market impact in trading.
method Integrates interbank limit and market orders with internal market-making liquidity.
result Reduces market impact and improves execution efficiency.
We present a new framework for Hermite fractional financial markets, generalizing the fractional Brownian motion and fractional Rosenblatt markets. Considering pure and mixed Hermite markets, we introduce a strategy-specific arbitrage tax on the rate of transaction volume acceleration of the hedging portfolio as the pr…
This study uses AI to analyze financial market coverage from YouTube videos.
problem Challenges in analyzing a large number of financial market videos.
method Used Whisper model to generate text from videos, applied natural language processing.
result Highlights dynamics of financial market coverage and identifies trending topics.
Model approximates market prices and returns without prior market dynamics.
problem Simultaneously approximate market prices and log returns.
method GDN model of Kratsios and Papon (2022) for generalized Ornstein-Uhlenbeck process.
result Universal approximation guarantees for conditional distributions and contingent claims.
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…
Study shows how market efficiency changes during the pandemic.
problem Understanding market efficiency during the pandemic.
method Applied time-varying vector autoregression model.
result Market efficiency changes over time and can be improved by enhanced linkages.
A generalization of the Cont-Bouchaud market model to three markets agrees with the correlations netween New York, Tokyo, and Frankfurt observed by Vandewalle et al.
Modeling financial chaos with market makers' risk appetite.
problem Unpredictable price changes in financial markets.
method Using Hamiltonian approach with anharmonic oscillators and nonlinear coupling.
result Market makers' risk appetite determines chaotic dynamics in financial markets.
The paper analyzes how stock market dimensionality changes impact portfolio performance.
problem Impact of dimensional changes on portfolio performance in a changing market.
method Development of self-financing stock portfolios in a stochastic portfolio theory framework with dimensional jumps.
result Quantification of how listing or delisting events and market shocks affect portfolio return.
Uniswap -- and other constant product markets -- appear to work well in practice despite their simplicity. In this paper, we give a simple formal analysis of constant product markets and their generalizations, showing that, under some common conditions, these markets must closely track the reference market price. We al…
DiffLOB models future market conditions for better decision-making.
problem Passive generative models cannot explore hypothetical market scenarios.
method Regime-conditioned diffusion model for counterfactual LOB generation.
result DiffLOB enables realistic and controllable generation of LOB trajectories.
This study optimizes crypto-market trading conditions without assuming convexity.
problem Optimizing crypto-market trading conditions without convexity.
method Rigorous mathematical analysis of constant function market makers under quasilinear trade functions.
result Quasilinear trade functions can replicate convex functions' robustness against arbitrage.
In this paper we explore the usage of deep reinforcement learning algorithms to automatically generate consistently profitable, robust, uncorrelated trading signals in any general financial market. In order to do this, we present a novel Markov decision process (MDP) model to capture the financial trading markets. We r…
Biondi et al. (2012) develop an analytical model to examine the emergent dynamic properties of share market price formation over time, capable to capture important stylized facts. These latter properties prove to be sensitive to regulatory regimes for fundamental information provision, as well as to market confidence c…