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arXiv research

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.

168,695 papers · 148 categories

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48 results for strategic trader

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.

We consider thin incomplete financial markets, where traders with heterogeneous preferences and risk exposures have motive to behave strategically regarding the demand schedules they submit, thereby impacting prices and allocations. We argue that traders relatively more exposed to market risk tend to submit more elasti…

2017-07-17abs ↗pdf ↗

The paper tackles auction market design flaws by randomizing closing times and optimizing transaction fees.

problem Strategic traders exploit accumulated information to delay their orders, distorting auction efficiency.
method Randomizing auction closing times and designing optimal transaction fees policies.
result Policies encourage strategic traders to send orders earlier, improving auction market efficiency.

Informed traders strategically reveal noisier signals, making prices less responsive to public information.

problem How informed traders strategically reveal signals impacts market prices and utility.
method Modeling a market with an informed trader, an uninformed trader, and liquidity providers, proving equilibrium existence.
result In equilibrium, the insider strategically reveals a noisier signal, making prices less responsive to public information.

The paper analyzes trading strategies in a competitive market with incomplete information.

problem Strategic trading under uncertainty when firms lack full knowledge of competitors' strategies.
method Bayesian games framework to incorporate uncertainty and derive optimal trading strategies.
result Uncertainty significantly impacts trading strategies compared to complete information scenarios.

Study examines how traders with asymmetric information and adaptive learning strategies affect market efficiency.

problem Effect of traders' strategic behavior on market efficiency and informational asymmetry.
method Examines a market with boundedly rational, asymmetrically informed traders using multiarmed bandit algorithms.
result Strategically acting traders can lead to more efficient markets than purely competitive ones under certain conditions.

New paper finds strategic trade centralization benefits firms, while naive centralization often harms them.

problem Finding optimal trading strategies in competitive markets.
method Complete solution to finding equilibrium strategies in competition using Fourier Series methods.
result Firms that strategically centralize trades generally benefit, while naive centralization often harms them.

ABIDES-MARL uses MARL to study market behavior in a realistic financial simulation.

problem Understanding equilibrium behavior in complex financial market games.
method Combines MARL with a realistic LOB simulation to study market behavior.
result Validated approach by solving an extended Kyle model and showing how execution strategies shape market dynamics.

This paper examines how wash traders exploit market conditions in Bitcoin, finding strategic timing and spillover effects.

problem Wash trading in cryptocurrency markets to inflate volume and manipulate market conditions.
method Analysis of 18 million Mt. Gox transactions, exogenous demand shock study.
result Wash trading intensifies in low legitimate trading volume and responds to demand shocks, indicating strategic behavior.

This article is a prologue to the article "Why Markets are Inefficient: A Gambling 'Theory' of Financial Markets for Practitioners and Theorists." It presents important background for that article --- why gambling is important, even necessary, for real-world traders --- the reason for the superiority of the strategic/g…

2018-01-07abs ↗pdf ↗

An ability to postpone one's execution without penalty provides an important strategic advantage in high-frequency trading. To elucidate competition between traders one has to formulate to a quantitative theory of formation of the execution price from market expectations and quotes. This theory was provided in 2005 by …

2012-04-06abs ↗pdf ↗

The paper analyzes trade execution strategies for large traders in a stochastic market environment.

problem Analyzing trade execution strategies in a stochastic market with price impact.
method Formulated a Markov game model and used backward induction method of dynamic programming.
result Explicit closed-form execution strategy at Markov perfect equilibrium.

Study shows marketable order routing to wholesalers benefits all traders, leading to lower market depth and price volatility.

problem Determining the preference of retail traders for marketable order routing.
method Two models: one for market makers competing for retail order flow (Bertrand model) and another for price-taking competitive liquidity providers (open exchange model).
result Routing marketable orders to wholesalers is preferred by all traders, leading to mean reverting inventories and lower market depth.

Optimizes trade execution with reinforcement learning for limit orders.

problem Maximizing revenue in a limit order book with market and limit orders.
method Formulated as a dynamic allocation task, uses multivariate logistic-normal distributions for efficient training.
result Outperforms traditional strategies in simulated environments.

The paper studies an oligopolistic equilibrium model of financial agents who aim to share their random endowments. The risk-sharing securities and their prices are endogenously determined as the outcome of a strategic game played among all the participating agents. In the complete-market setting, each agent's set of st…

2012-06-02abs ↗pdf ↗

Study analyzes market equilibrium returns with price impact and transaction costs.

problem Modeling equilibrium returns in markets with strategic order placement and transaction costs.
method Analyzes frictionless and transaction-cost markets, characterizes Nash equilibrium via FBSDEs.
result Equilibrium returns are affected by transaction costs, especially with noise traders.

LLMs mimic human traders in finance, but not as much as expected.

problem Evaluating how LLMs behave in financial markets.
method Adapted experimental design with LLMs and human traders, analyzed in single and mixed model settings.
result LLMs tend to price assets near their fundamental value, but not as much as humans, and show less trading strategy variance.

In illiquid markets, option traders may have an incentive to increase their portfolio value by using their impact on the dynamics of the underlying. We provide a mathematical framework within which to value derivatives under market impact in a multi-player framework by introducing strategic interactions into the Almgre…

2008-12-31abs ↗pdf ↗

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…

2016-10-31abs ↗pdf ↗

AI-Trader benchmarks LLMs in live financial markets, revealing poor trading performance.

problem Challenges in real-time financial decision-making by autonomous agents.
method Fully automated, live evaluation benchmark with minimal human intervention.
result General intelligence does not translate to effective trading, highlighting limitations.

Quantitative analysis of order-splitting behavior in Japanese stock market.

problem Understanding and quantifying the order-splitting behavior of traders in the Japanese stock market.
method Analysis of a large dataset of trading accounts over nine years, clustering traders into order-splitting and random traders, and applying statistical methods to analyze metaorder length and sign correlation.
result The metaorder length distribution follows power laws with exponent α, and the sign correlation exponent γ is approximately α-1, supporting the LMF model.

3S-Trader uses LLMs to optimize stock portfolios by scoring, strategizing, and selecting stocks.

problem Lack of multi-LLM frameworks for adaptive stock scoring, strategy, and selection in portfolio optimization.
method 3S-Trader incorporates scoring, strategy, and selection modules for stock portfolio construction, using historical strategies and market conditions to generate optimized selections.
result 3S-Trader achieves the highest accumulated return of 131.83% on DJIA constituents with a Sharpe ratio of 0.31 and Calmar ratio of 11.84.

We consider a stochastic game between a trader and a central bank in a target zone market with a lower currency peg. This currency peg is maintained by the central bank through the generation of permanent price impact, thereby aggregating an ever increasing risky position in foreign reserves. We describe this situation…

2018-01-23abs ↗pdf ↗

Optimal trading strategy between CEXs and DEXs with priority fees and stochastic delays.

problem Managing latency risk in trading between centralized and decentralized exchanges.
method Developed a mixed control framework combining absolutely continuous controls with impulse interventions, allowing for stochastic execution delays and multiple pending orders.
result Optimal priority fee selection significantly outperforms non-strategic fee selection.

Model predicts option movements using residual transactions for better market timing.

problem Predicting option movements using standard metrics like open interest and trading volume.
method Analyzes residual transactions, integrates machine learning and regression techniques.
result Identifies early indicators of market trends for better option price forecasting.

Understanding how funding and 4H context regulate crypto markets.

problem Analyzing the chaotic appearance of financial markets.
method Observing interactions between market context and capital conditions in the 4H timeframe.
result Ranges in crypto markets are strategic positioning by informed participants, not indecision.

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.

Paper generalizes strategic classification framework and introduces SVC for PAC-learning.

problem Strategic manipulation of testing data to fool classifiers.
method Unified framework for strategic classification, strategic VC-dimension (SVC).
result Characterizes the learnability and computational tractability of linear classifiers.

Study strategic dynamic pricing for buyers with unknown manipulation costs.

problem Strategic buyers manipulate their features to get lower prices, hindering profit maximization.
method Proposes a strategic dynamic pricing policy that incorporates strategic behavior and binary response data.
result Achieves sublinear regret bound of O(T)O(\sqrt{T}) compared to linear Ω(T)Ω(T) regret of non-strategic policies.

New framework reduces strategic manipulation cost for minority groups in fair classification.

problem Strategic manipulation disparities in fair classification.
method Constrained optimization framework that constructs classifiers to reduce strategic manipulation cost for minority groups.
result Empirically, the approach reduces strategic manipulation cost for minority groups over multiple real-world datasets.

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.

Study compares employers with and without anticipating strategic labor force responses.

problem Understanding and optimizing strategic interactions in labor markets.
method Formulation of causal strategic classification, theory, and experiments.
result Performatively optimal hiring policies improve employer and labor outcomes, but can also harm labor force utility.

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 optimal liquidation strategies in lit and dark pools with and without regulation.

problem Optimal liquidation strategies in dark and lit pools with execution uncertainty.
method Design optimal make-take fee policies, solve HJB-Fokker-Planck systems, use BSDEs.
result Explicit solutions for optimal strategies in both competitive and regulated markets.

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.