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.
Evology models US equity mutual funds interactions for investment strategies.
Paper models limit order book with informed traders and market makers.
New method identifies informed traders in prediction markets.
Study shows corporate governance improves stock liquidity with noise traders' participation.
This work models GHG offset credit markets to find optimal strategies for market participants.
We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their b…
We present an analysis of the price impact associated with trades effected by different financial firms. Using data from the Spanish Stock Market, we find a high degree of heterogeneity across different market members, both in the instantaneous impact functions and in the time-dependent market response to trades by ind…
We consider a simple market where a vendor offers multiple variants of a certain product and preferences of both the vendor and potential buyers are heterogeneous and possibly even antagonistic. Optimization of the joint benefit of the vendor and the buyers turns the toy market into a combinatorial matching problem. We…
Using high frequency data, we have studied empirically the change of volatility, also called volatility derivative, for various time horizons. In particular, the correlation between the volatility derivative and the volatility realized in the next time period is a measure of the response function of the market particip…
An interbank market lets participants pool the risk arising from the combination of illiquid investments and random withdrawals by depositors. But it also creates the potential for one bank's failure to trigger off avalanches of further failures. We simulate a model of interbank lending to study the interplay of these …
When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compa…
The paper uncovers two key laws of market impact influenced by volume and participation rate.
The paper analyzes how market prices respond to information processing and non-linear dynamics.
FedAMD framework improves federated learning with partial client participation.
In this paper we formulate the now classical problem of optimal liquidation (or optimal trading) inside a Mean Field Game (MFG). This is a noticeable change since usually mathematical frameworks focus on one large trader in front of a "background noise" (or "mean field"). In standard frameworks, the interactions betwee…
Study quantifies impacts of heterogeneity in FL on smartphone data.
Paper develops framework for AI agents in financial markets.
In this paper, we present a simple stock market model (the market game) which incorporates, as ab initio dynamics delayed majority dynamics, according to which agents (with heterogeneous strategies and price expectations) are rewarded if their actions at time t are the actions of the majority of agents at time t+1. We …
We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative…
Extended model ensures long-term survival of traders in limited stock market participation.
Federated learning enables the creation of a powerful centralized model without compromising data privacy of multiple participants. While successful, it does not incorporate the case where each participant independently designs its own model. Due to intellectual property concerns and heterogeneous nature of tasks and d…
Study resolves the Korean LVRP puzzle by showing HVRP exists but is masked by investor heterogeneity and improper intensity normalization.
FedZKT enables resource-constrained devices to participate in federated learning with heterogeneous models.
We create a formal framework for the design of informative securities in prediction markets. These securities allow a market organizer to infer the likelihood of events of interest as well as if he knew all of the traders' private signals. We consider the design of markets that are always informative, markets that are …
LLMs simulate financial markets, revealing consistent trading strategies and market dynamics.
The study examines collective behavior in banking sectors across mature and emerging markets.
Prediction problems in finance go beyond estimating the unknown parameters of a model (e.g. of expected returns). This is because such a model would have to include parameters governing the market participants' propensity to change their opinions on the validity of that model. This leads to a well--known circular situa…
This paper deals with a stochastic order-driven market model with waiting costs, for order books with heterogenous traders. Offer and demand of liquidity drives price formation and traders anticipate future evolutions of the order book. The natural framework we use is mean field game theory, a class of stochastic diffe…
Model analyzes trading frictions in cap-and-trade markets, showing how they interact to affect market effectiveness.
New game theory approach to bond market liquidity and participant behavior.
Study shows HFT improves market liquidity indicators.
New algorithm reduces communication time in federated learning.
This paper develops a learning framework for optimal strategies in multi-stage decentralized matching markets.
In this paper we develop a new form of agent-based model for limit order books based on heterogeneous trading agents, whose motivations are liquidity driven. These agents are abstractions of real market participants, expressed in a stochastic model framework. We develop an efficient way to perform statistical calibrati…
Paper proposes SCALLION and SCAFCOM for compressed FL with reduced communication.
The paper studies price impacts in asset liquidation markets.
We consider models of financial markets in which all parties involved find incentives to participate. Strategies are evaluated directly by their virtual wealths. By tuning the price sensitivity and market impact, a phase diagram with several attractor behaviors resembling those of real markets emerge, reflecting the ro…
The paper analyzes real-time methods to detect rapidly varying liquidity in markets.
A fair reward system boosts participation in federated learning.
The paper proves an equilibrium in a limited stock market participation model with power utilities.
Bayesian framework explains price formation with learning and market impact.
Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional time series with spectral distances introduced in [A.-H. Sato, Physica A, 382 (2007) 258--270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation …
An asymmetric information model is introduced for the situation in which there is a small agent who is more susceptible to the flow of information in the market than the general market participant, and who tries to implement strategies based on the additional information. In this model market participants have access t…
Study optimizes SREC generation and trading in solar energy markets.
We study dynamics of a simulated world with stock and money, driven by the externally given processes which we refer to as sentiments. The considered sentiments influence the buy/sell stock trading attitude, the perceived price uncertainty, and the trading intensity of all or a part of the market participants. We study…
Proves existence of equilibrium in limited participation economy.
Cryptocurrencies are distributed systems that allow exchanges of native tokens among participants, or the exchange of such tokens for fiat currencies in markets external to these public ledgers. The availability of their complete historical bookkeeping opens up the possibility of understanding the relationship between …
Low redispatch prices boost green hydrogen production cost, encouraging electrolyzer siting.